literature review on solar powered irrigation system

SMART Irrigation System Contribution to Sustainable Development Goals

• First Online: 23 August 2024

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• Diyana Binti Ab Kadir 9 ,
• Muhamad Zuhairi Bin Mohamad Zawawi 9 ,
• Muhamad Amir Fiqri Bin Mohd Asmar 9 ,
• Mohamad Syahmi Firdaus Bin Mohd Safie 9 ,
• Mohd Fathurrahman Bin Mohd Faizal 9 &
• Harith Nafi’ Bin Hanazrie 9  

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 545))

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The paper aims to highlight how SMART Irrigation System using Internet of Things (IoT) contributes towards sustainability development in environment, economy and society and which SDGs they contribute to. However, one of the challenges that this research faces is the understanding of the impact of the implementation of sustainable irrigation practices on the environment, economy, and society. This research shows the theoretical benefits from the implementation of sustainable irrigation practices for those three main aspects. Results show that this project theoretically contributes towards some SDGs like SDG 2, 3, 6, 12 and 15. This leads to a long-term solution such as precise irrigation and less water consumption to produce more quality crops for the environment, economy, and society.

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Diyana Binti Ab Kadir, Muhamad Zuhairi Bin Mohamad Zawawi, Muhamad Amir Fiqri Bin Mohd Asmar, Mohamad Syahmi Firdaus Bin Mohd Safie, Mohd Fathurrahman Bin Mohd Faizal & Harith Nafi’ Bin Hanazrie

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Kadir, D.B.A., Zawawi, M.Z.B.M., Asmar, M.A.F.B.M., Safie, M.S.F.B.M., Faizal, M.F.B.M., Hanazrie, H.N.B. (2024). SMART Irrigation System Contribution to Sustainable Development Goals. In: Alareeni, B., Elgedawy, I. (eds) Opportunities and Risks in AI for Business Development. Studies in Systems, Decision and Control, vol 545. Springer, Cham. https://doi.org/10.1007/978-3-031-65203-5_12

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ORIGINAL RESEARCH article

Adoption impact of solar based irrigation facility by water-scarce northwestern areas farmers in bangladesh: evidence from panel data analysis.

• 1 School of Management, Zhejiang University, Hangzhou, Zhejiang, China
• 2 Agricultural Economics Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
• 3 School of Nontraditional Security Studies, Zhejiang University, Hangzhou, Zhejiang, China
• 4 School of Two Mountains, Lishui University, Lishui, Zhejiang, China
• 5 Department of Management and Finance, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh
• 6 China Academy of Rural Development, Zhejiang University, Hangzhou, Zhejiang, China

Introduction: Fossil fuel and electricity-based irrigation practices contribute to greenhouse gases and add substantial costs to water access. Solar-powered irrigation is spreading globally, notably in developing countries, as a solution to the rising energy and climate concerns related to agriculture. This policy perspective devoted to examining the impact of the solar irrigation facilities (SIF) adoption on irrigation cost and return on investment (ROI) based on seven years of panel data seeks to contribute to the efforts to propel solar irrigation toward delivering on the myriad of promises.

Methods: Panel logistic regression was employed to analyze adoption determinants, while adoption impact was evaluated through the propensity score matching with the difference-in-difference (PSM-DID) method. In addition, the time and panel fixed effect DID and doubly robust DID model was also used for robustness check.

Results: The result reveals that SIF adoption significantly increased ROI by 20% to 30% and reduced irrigation costs by 21% to 30%.

Conclusion: The findings call for further research and analysis on evidence-based best practices for solar irrigation solutions at the farm level so that the dissemination of this revolutionary technology, apart from contributing to the advancement of the energy sector, also plays a vital role in driving us towards establishing a more equitable and sustainable world.

1 Introduction

The world is confronting a reckoning regarding the energy issue. Despite decades of pleas to minimize dependence on non-renewable energy, nations have intensified the usage of coal, oil, and gas to fuel their economies ( WFP, 2022 ). The consequences of the extensive burning of fossil fuels have intensified the carbon emissions issue and created a globalized world in which food and energy systems are highly concentrated—making them extremely vulnerable to disruption. The world now grapples with consecutive waves (i.e., heat waves, the millennium drought, poverty impacts from COVID-19, and ongoi`ng supply chain challenges due to war) that negatively impact agriculture and have been the instigator of a potentially severe food crisis. These interlocking crises have contributed to global energy and food price spikes and have placed agriculture and irrigation in a precarious position where energy-efficient technology use has become obligatory ( UNSDG, 2022 ; WFP, 2022 ).

The impact is severe in developing countries, especially Asia, where diesel and electric-based irrigation plays a vital role in domestic food security and poverty alleviation ( Sunny et al., 2022a ). While Myanmar and Pakistan’s daily consumption sits around 2.7 million liters and 3.5 billion liters of diesel, respectively, Nepal’s Eastern Indo-Gangetic Plains only have 20% of its irrigation pumps non-diesel reliant ( Qureshi, 2014 ; Foster et al., 2019 ; Phillips, 2021 ). Clearly, the region has learned and adapted to the challenges of inconsistent power generation for rural agricultural work, illustrating flexibility and resilience within the sector. However, reliance on such a non-renewable resource may cause some new challenges in the future. In India, for instance, of the total electrical power generated, 18% goes to agriculture; similarly, 5% of the total diesel in the country is allocated for just irrigational purposes ( IRENA, 2016 ). Though not sounding too dire, one must consider what concentrations of which demographic find themselves heavily reliant on diesel as a substitute for the lack of national electrical grid energy supplies. This is a profound question, especially since 1.6 billion people live without electricity in developing countries—most in Sub-Saharan Africa and South Asia ( The World Bank, 2018 ). The struggle to meet energy demands leads to load shedding that disrupts planning and resource management and, more specifically, interrupts the irrigation process ( Hoque et al., 2016 ).

Energy security is one of the major global concerns, as energy deficiencies and resulting economic factors may generate socio-political issues. To ensure food security, enhance energy security, prevent local pollution, and increase climate benefits, the policy manifesto for most developing countries with similar issues has the impetus for adopting reliable, cost-effective, and clean energy irrigation technologies ( Schwanitz et al., 2014 ; Rentschler and Bazilian, 2016 ; Sarker and Ghosh, 2017 ).

Like other developing economies, the agriculture sector is regarded as one of the critical drivers of Bangladesh’s economy. As a catalyst for sustainable growth of the country, the sector accounts for 12.92% of the gross domestic product (GDP) and 38 percent of the labor force ( The World Bank, 2021 ; The World Bank, 2022 ). Around 70% of Bangladesh’s population’s livelihood depends on agricultural activities ( Imdad, 2021 ). The country’s natural inheritance of favorable soil, climate, and groundwater availability has alleviated farmers’ opportunities to grow tropical and temperate crops on over two-thirds of cultivatable land twice or more annually. Rice ( Oryza sativa ) is the staple food that accounts for approximately 75 percent of the total harvested area and contributes around 95 percent of the total food grain ( Shew et al., 2019 ; Alam et al., 2021 ). Irrigation is a fundamental operation unit in rice production and is essential for the agriculture life cycle system ( Ali, 2018 ). Even though insufficient rainfall in the dry season and scarcity of surface water has hampered rice productivity in many parts of Bangladesh, especially the northern regions, groundwater utilization has played a vital role in ameliorating agricultural development ( Biswas and Hossain, 2013 ; Hasnat et al., 2014 ). The development of groundwater policies has resulted in the expansion of Low Lift Pumps (LLP), Shallow Tube Wells (STW), and Deep Tube Wells (DTW) usage in Bangladesh ( BGEF, 2016 ). The first two systems run on diesel, while the latter runs on electricity from the national grid. The maximum capacities of the LLP are 7.5, SWT is 12.5, and DWT is 55 horsepower (hp) ( Hossain et al., 2015 ). These water extraction technologies have greatly aided Bangladesh in attaining near self-sufficiency in rice production. The downside, however, has been the massive energy demand increase ( Sunny et al., 2022a ; Sunny et al., 2022b ). Presently, approximately 1.6 million diesel pumps consume at least one million tons per year to satisfy irrigation needs ( Prothom Alo, 2021 ). When this is estimated in monetary terms, the sum reaches a conservative total of $900 million ( Ershadullah, 2021 ). Between the transportation, added pollution through transportation of the fuel and the use of it at its endpoint, and the potential calamities that could occur environmentally along the production chain - a second thought should be given to diesel as a primary fuel source for extracting ‘clean renewables’ like water. Recent estimates indicate that even though irrigation consumes 4.58% of the total electricity generated in the nation ( ADB, 2018 ), the electricity demand in the forthcoming irrigation season is projected to rise from 14,097 MW to 15,500 MW ( The Business Standard, 2022 ). The national grid can not ensure regular power without frequent outages, voltage flickering, and constantly increased tariffs and rates ( Doby, 2018 ). The result is major disruptions in irrigation activities and, thus, revenue streams. In some situations, farmers have been forced to adapt by irrigating during low-peak hours (at night) when the power is more stable ( Odarno, 2017 ). Other farmers have chosen to take control of their power provision by investing in diesel pumps, which carry their deficiencies. These pumps are at the mercy of fuel prices, technical defects, service gaps, and mismanaged usage and can sometimes be more problematic than the national grid ( Energypedia, 2020 ; Mirta et al., 2021 ).

Concerns for alternatives have been raised regarding agricultural sustainability in defying these challenges. Hence, like other emergent nations,’ Bangladesh has also embraced the idea of sustainable agriculture practices alongside the overarching concept of sustainable development. Sustainable agriculture advocates adopting measures to conserve the natural environment and resources through technically appropriate, economically viable, and socially accepted approaches ( FAO, 1989 ). It also integrates the ideology of enhancing resilience to shocks and stresses over more prolonged periods and addresses more comprehensive economic, social and environmental outcomes from the local to the global level ( Pretty, 2008 ). Sustainable agriculture is central to attaining many sustainable development goals ( United Nations, 2015 ; FAO, 2019 ). The key to achieving agricultural sustainability is by ameliorating productivity through adopting technology and practices that remediate the environment from poor agricultural practices abuse and drive the welfare of the food producers ( Zilberman et al., 1997 ; Pretty, 2008 ). Therefore, besides improving strategic and operational farm management, the government has highlighted up-scaling renewable energy-based irrigation systems. If current climate change estimates were to add sufficient motivation for action, then the proposition holds to establish 50,000 solar irrigation pumps by 2027. The results would be an estimated reduction in greenhouse gas (GHG) emissions by up to 15% by 2030 ( Mirta et al., 2021 ). Apart from that, 10% of conventional energy would be replaced, and fossil fuel reserve depletion would rapidly regress while ensuring sustainable water management in agriculture sectors ( Kanojia, 2019 ; Sajid, 2019 ; Rana et al., 2021a ). Despite the significant potential, solar irrigation technologies promotion has been sluggish, and the penetration of solar pumps faces the challenge of competing against other conventional systems ( SREDA, 2015 ; Rana et al., 2021a ). Given this context, this work attempts to answer the following research questions.

• What key determinants influence our study area farmers to adopt SIF?

• How do SIF adoption impact farmers’ irrigation cost and ROI?

• What are the associated challenges to the sustainability of SIFs and the measures to overcome the challenges?

2 Literature review

Several studies have documented the advantage of solar-based irrigation system adoption over conventional systems. For instance: the performance and reliability test of different types of solar-powered water pumping systems in the United States and Spain revealed that these systems are cheaper alternatives for rural, with high performance, ensure customer satisfaction, and are an environmentally-viable energy source for pumping in irrigation networks ( Chowdhury et al., 1993 ; García et al., 2019 ). A study conducted in northern Benin revealed that compared to non-adopters, commercial-scale solar-powered drip irrigation systems adopters were able to significantly increase production ( Alaofè et al., 2016 ). Likewise, the adoption of solar-based water pumping systems in china has resulted in ameliorating forage productivity, meeting local demand, and minimizing carbon emissions ( Campana et al., 2017 ). Besides, SIF adoption impact analysis in the Philippines revealed that the adoption not only aided in GHG emissions reduction by up to 26.5 tons CO2eq/ha/year but also contributed to the energy sector by savings between 11.4 and 378.5 L/ha of diesel per year with an average of 315% returns on investment ( Guno and Agaton, 2022 ). Furthermore, SIF adoption in Pakistan has significantly contributed to reducing operational costs, increased farmers’ income, reduced 17,622 tons of CO2 emissions per year, and saved 41% of water usage ( Raza et al., 2022 ). In addition, apart from irrigation purpose usage and meeting electricity needs, SIFs adoption contributes to facilitating drinking water requirements in water-scarce regions and contributes toward gender empowerment by alleviating the burden of labor-intensive diesel system operation and allowing women to utilize their time for productive purposes ( IRENA, 2016 ; Agrawal and Jain, 2018 ).

The literature on SIF adoption analysis in the context of Bangladesh revealed that if the economic return is considered based on the internal rate of return (IRR), then the most profitable option would be establishing small-sized SIF (20%), followed by large-sized (10%). On the other hand, the net environmental benefit per kilowatt peak (kWp) is highest (86,000) for the small SIFs, followed by medium SIFs (67,184 kWp) and large SIFs (65,392 kWp) ( Islam and Hossain, 2022 ). Other research findings suggested that SIF adopters could reduce irrigation costs by a maximum of 2.22%, obtain 4.48%–8.16% higher ROI, and reduce nearly 1% of total production cost compared to non-adopters ( Sunny et al., 2022a ). Another study stated that even though the initial investment cost of SIF was found to be higher than a diesel-powered system, the low maintenance and zero fuel costs make it a cheaper option in the long run ( Rana et al., 2021b ).

This study compares to others contributing to literature in several ways. Firstly, this study used panel data to assess the impact of SIF adoption on irrigation cost and return on investment (ROI). As the return on investment variable considers the gross revenue of farm production and the production costs, it can better reflect the efficiency of farm performance ( Kleemann et al., 2014 ; Zheng and Ma, 2021 ). Secondly, we employed propensity score matching (PSM) with the difference in difference (DID or DD) models to estimate adoption impact and address the selection bias issue, which also differs from other related studies ( Barreto and Bell, 1994 ; Coady, 1995 ; Duflo et al., 2011 ; Dong et al., 2012 ; Fanus et al., 2012 ; Martey et al., 2013 ; Zhou and Abdullah, 2017 ; Kumar et al., 2019 ; Kumar et al., 2020 ; Sanap et al., 2020 ). We also used fixed effect DID and doubly robust DID for robustness checking. Finally, examining the role of solar irrigation technology on welfare outcomes is of great significance to policy formulation to tackle future climate vulnerability while enhancing farm productivity, food security, and poverty reduction.

3 Materials and methods

3.1 study area, and sampling procedure.

This study focuses on the drought-prone area of the northern region of Bangladesh that receives merely 372 mm of rain from November to May, compared to 546 mm during the same time in the whole country. The average annual rainfall of this region is 21.83% lower than the country’s average annual rainfall. Inadequate rainfall and limited surface water have created high dependence on groundwater for irrigation in these areas ( Hossain et al., 2021 ; Rahman et al., 2022 ). Nearly 1.6 million diesel pumps ( Prothom Alo, 2021 ) and 3.20 lakh electricity pumps ( Ershadullah, 2021 ) that are operating in the country, a significant proportion is operating in the northern region ( Hossain et al., 2021 ).

For this study, multistage sampling techniques were employed. At first, the Dinajpur district was selected for several reasons. Dinajpur is the largest district among all sixteen districts situated in the northern part, and according to the international ‘Köppen climate classification,’ the district has a tropical wet-dry climate. The annual average temperature is 25 °C. The average precipitation from November to March is below 20 mm, April and October are below 100 mm, and the remaining 5 months are over 200 mm ( Encyclopedia, 2018 ). Due to the low precipitation rate, the district is considered one of the top drought-prone areas of Bangladesh ( Afrin et al., 2019 ; Islam et al., 2022a ; Rahman et al., 2022 ), where the food insecurity and poverty rate are high ( BBS and WFP, 2020 ). This district is also one of the top districts where more solar irrigation pumps are installed ( SREDA, 2022 ). We used a simple random sampling method to select 3 of 13 sub-districts from the Dinajpur district in the second stage. The randomly chosen three sub-districts were Birganj, Khanshama, and Kaharol. The combined population of these three sub-districts is 643,431 ( Population and BBS, 2011 ).

We then used Krejcie and Morgans’ ( Krejcie and Morgan, 1970 ) table to determine the optimal sample size. A sample of 384 farmers was determined based on the population size. However, a 5% additional sample was collected to avoid unexpected future issues such as farmers’ discontinuation of SIF or land rented to others. Thus from 50 different solar irrigation sites in three sub-districts, eight farmers were randomly chosen for control and treatment groups. These farmers were interviewed each year between February and April, starting from 2015 till 2021.

The baseline of this study was 2015 and 2016, the treatment period stated in the year 2017, and the end line was 2021. Hence finally, we obtained a panel of (50*8 = 405*7) 2,835 farmers. The Boro season (starting in December and ending in June) was chosen since the maximum rice is produced in this season ( BBS, 2020 ), and irrigation demand is very high. The interview schedule was translated into the local language for implementation. Our interview schedule included farmers’ demographic and socioeconomic characteristics, environmental, agroecology, technology-related knowledge, fee opinion, service quality, and infrastructure-related questions.

3.2 Analytical technique

3.2.1 theoretical framework.

This study is based on the random utility theory developed by McFadden in 1974 ( McFadden and Zarembka, 1974 ), which is consistent with Lancaster’s economic theory of value and neoclassical view that hypothesize individuals would choose alternatives that maximize their utility ( Lancaster, 1966 ; Manski, 1977 ; Hoyos, 2010 ; Hess et al., 2018 ). Based on this theory, we would like to see if solar irrigation adoption compared to other irrigation mediums is beneficial or not.

3.2.2 Empirical approaches of adoption determinants

To estimate the factor that influences our study area farmers’ adoption or non-adoption decision of SIF, we consider the following logistic regression model ( Neuhaus et al., 1991 ):

Where Y i j is the binary outcome variable, X i j is the predictor variable, a is constant, and b * is the population parameter.

3.2.3 Empirical approach of impact assessment

Prior studies on impact assessment suggested that a significant hurdle while conducting related research is constructing appropriate counterfactuals. Because a set of observable and unobservable factors influences the adoption process, failure to do so will cause the corresponding impact estimates to be biased ( Mendola, 2007 ; Wu et al., 2010 ). Therefore, studies have used various methods to assess the impact of technology adoption that considers selection bias ( Mendola, 2007 ; Becerril and Abdulai, 2010 ; Wu et al., 2010 ; Asfaw et al., 2011 ; Asfaw et al., 2012 ; Khonje et al., 2015 ; Alem and Broussard, 2018 ; Khonje et al., 2018 ; Nakano et al., 2018 ; Islam et al., 2019 ; Manda et al., 2020 ).

This study, in mitigating the selection and time-invariant source of bias issue and in measuring the adoption impact of SIF on farmers’ irrigation cost and their return on investment (ROI), has adopted difference in difference estimation with propensity score matching (PSM-DID). This approach compares two populace groups (the treated and the non-treated) based on the time sequence of before and after-action states. The effectiveness of the treatment (a course of action) is considered adequate toward the outcome when the intervention group shows off better or worse trends over their controlled counterpart (considering other influencing factors such as ceteris paribus) ( Islam et al., 2022b ).

The single DID setting proposed by Villa ( Villa, 2016 ) is presented as follows:

Where the baseline period is t = 0   a n d follow-up is t = 1 ; a treated group to which the treatment is delivered is Z i = 1 , and a control group to which the treatment is not provided denotes as Z i = 1 . ( D i ,   t = 0 = 0 Z i = 1,0 ) is the treatment indicator that requires in the absence of any intervention in the baseline for either group, and it commands the intervention to be positive for the treated group in the follow-up D i ,   t = 0 = 1 |   Z i = 1 . For a given outcome variable, Y i t , the population DID treatment effect is given by the difference in the outcome variable for treated and control units before and after the intervention.

If additional covariates are combined with the single DID setting, the model will be:

The DID is a flexible form of causal inference because it can be combined with other procedures, such as kernel propensity score matching ( Heckman et al., 1997 ) and quintile regression ( Meyer et al., 1995 ). Propensity score matching (PSM) helps estimate treatment effects as this method can balance measured covariates across groups (treatment and control) and better estimate the counterfactual for treated individuals ( Rosenbaum and Rubin, 1983 ; Imbens, 2004 ; Austin, 2011 ). Kernel propensity-score weights complement the DID treatment effect model. This matching technique (also known as kernel weighting) is beneficial when other matching strategies are not viable for analyzing survey data with sampling weights or continuous or multilevel categorical treatments ( Garrido et al., 2014 ). Villa ( Villa, 2016 ) suggested that, by following Heckman, Ichimura, and Todds’ study ( Heckman et al., 1997 ; Heckman et al., 1998 ), besides the inclusion of control variables, observed covariates can be used to estimate the propensity score (the likelihood of being treated) and calculate kernel weights. Thus, this alternative approach matches treated and control units based on their propensity score instead accounting for control variables. Each treated unit is matched to the whole sample of control units instead of a limited number of nearest neighbors. To begin, one obtains the propensity score p i for both groups and p i = E   Z i = 1 ,   X i .

As explained by Heckman, Ichimura, and Todd, kernel matching is an averaging method that reuses and weights all the comparison group observations in the treatment sample ( Heckman et al., 1997 ). Comparison individuals are weighted by their distance in propensity score from treated individuals within a range, or bandwidth, of the propensity score ( Garrido et al., 2014 ; Villa, 2016 ). Thus, the kernel weights can be defined,

In Equation 3 , K   . is the kernel function, and h n is the selected bandwidth.

To obtain a kernel propensity-score matching DID treatment effect, the kernel weights (presented in Eq. 3 ) are then introduced into Equation 1 is presented below:

However, in increasing the internal validity of the DID estimand, it is possible to restrict ( Phillips, 2021 ) to the common support (the overlapping region of the propensity for treated and control groups) of the propensity score for both groups. This sample of i units can be restricted to the region defined as,

Blundell and Dias have stated that in case of inability to follow treated and control units over the baseline and follow-up phases, the DID treatment effects can be estimated with repeated cross-sections ( Blundell and Dias, 2009 ). This is very common when a treatment has been administered to specific regional or demographic groups over several cross-sections. The kernel propensity score matching with repeated cross-section DID treatment effects thus can be expressed as,

Here, w i t = 0 c and w i t = 1 c represent the kernel weights for the control group in the baseline and follow-up periods, respectively. w i t = 0 t , on the other hand, symbolizes kernel weights of the treated groups’ baseline period.

Besides, the balancing property of the treated and the control can be tested through DID estimates. Given the availability of observable covariates, it can be shown that in the absence of the treatment, the outcome variable is orthogonal to the treatment indicator given the set of covariates. In other words, the balancing property can be tested in the baseline as,

DID estimation also necessitate satisfying the ‘parallel or common trend’ test. Under the trend assumption, in the absence of treatment, the average outcome changes from any pre-treatment period to any post-treatment period for the treated is equal to the equivalent average outcome change for the controls. In pre-treatment trend differentials, it is customary to adjust the econometric specification to try to accommodate for those differences ( Mora and Reggio, 2015 ).

The parallel trends assumption can be tested graphically or by performing a test on the linear-trends model coefficient that captures the differences in the trends between treated and controls. The specification of the linear-trends model test, adapted from the study conducted by Cai ( Cai, 2016 ), is as follows:

Where Y i k t is the dependent variable; T r e n d is the time trend over the pre-treatment period; T r e a t is a binary variable that equals 1 for households in the treatment group and 0 otherwise; X i k t is a vector of control variables, and the ε i k t is the error term. If the estimated parameter were not statistically significant at conventional levels, it would mean that the treatment and the control households followed parallel trends prior to treatment.

Finally, to grasp the impact of solar irrigation on farmers’ irrigation costs, we consider the following econometric expression:

Irrigation cost,

Besides, the econometric illustration of estimating adoption impact on ROI can be expressed as:

In Equations 9 , 10 , the variable ‘ Y ′ is the outcome variable for ‘Irrigation cost’ and ‘ROI,’ respectively. ‘Year’ represents time trend. “Treatment” represents treated and control groups. The “Year*Treatment” variable denotes the DID estimand; “Explanatory variables” represent respondents’ socio-economic characteristics, and ε symbolizes the random-error term.

3.3 Measurement of key variables

Table 1 in below, presents the DID basic variables Year and Treatment ( Card and Krueger, 1994 ; Villa, 2016 ). The “Year” variable denotes the pre-treatment, treatment start, and follow-up periods. The end line of the research is the year 2021. The “Treatment” variable is the segmentation by the treatment and control groups.

TABLE 1 . Variables used in different models.

The outcome variables for this study are irrigation cost and ROI. The irrigation cost for solar and electricity-based irrigation system adopters was calculated based on the fee that individual farmers paid per 50 decimals. For diesel irrigation adopters, the cost was calculated based on diesel machine rent that the farmer pays each season and the total diesel cost per 50 decimal. However, for a farmer who owns a diesel machine, the cost was calculated based on the total amount of diesel used per 50 decimal and the repairing cost that an individual farmer paid each season. All cost is measured in Taka (the Bangladeshi currency) and then converted to logarithmic forms to calculate the cost increase or decrease percentage. On the other hand, the ROI is the ratio of total return to the variable costs, calculated based on the study conducted by the Bangladesh Rice Research Institutes (BRRI) agricultural economic division entitled ‘Estimation of costs and return of MV rice cultivation at the farm level’ ( BRRI, 2021 ).

The explanatory variables chosen for this study were based on the existing literature on technology adoption ( Albrecht and Ladewig, 1985 ; Caswell et al., 2001 ; Pandey and Mishra, 2004 ; Simtowe and Zeller, 2006 ; Tiwari et al., 2008 ; Deressa et al., 2011 ; Idrisa et al., 2012 ; Genius et al., 2013 ; Reza and Hossain, 2013 ; Challa and Tilahun, 2014 ; Mottaleb et al., 2016 ; Chuchird et al., 2017 ; Ntshangase et al., 2018 ; Sunny et al., 2018 ; Zeng et al., 2018 ; Sarker et al., 2021 ; Sunny et al., 2022a ; Sunny et al., 2022b ; Sunny et al., 2022c ), and their description are given in Table 1 .

3.4 Data analysis

The Chi-square and F-test were performed to check if any significant difference exists between the treatment and control groups. Panel logit regression using the “xtlogit” command was performed to determine the influential factors of adoption. In order to satisfy the pre-requisite of DID estimation parallel trend test was conducted. This test asserts that the group participating in the program would have experienced a similar change in the outcome variable between the pre-program and the post-program periods as those not participating. If this assumption holds and we can credibly rule out any other over-time changes that may confound the treatment, then the estimators are highly reliable (( Lechner, 2011 ). We used the ‘diff’ command to estimate PSM-DID ( Villa, 2016 ). We chose kernel matching with the Epanechnikov kernel function and used the bandwidth .03 and .06 ( DiNardo and Tobais, 2001 ; Caliendo and Kopeinig, 2008 ; Islam et al., 2019 ). The bootstrapped application was applied with 1,000 repetitions of resampling ( Wooldridge, 2012 ). Besides checking overlap and common support, we also conducted balancing tests on the differences in means after matching. For the robustness check, the ‘xtdidregress’ command was used to estimate the time and panel fixed effect DID and ‘drdid’ for estimating doubly robust DID ( StataCorp, 2021 ; Sant’Anna and Zhao, 2020 ). All the analysis was performed through software for statistics and data science (STATA) version 17.0. Finally, these analysis results have been presented using frequency tables and cross-tabulations.

4 Result and discussion

4.1 basic household characteristics of the survey respondents.

Prior studies have suggested that the technology adoption among smallholder farmers is generally influenced by their socio-economic, environmental, and institutional profiles ( Albrecht and Ladewig, 1985 ; Feder et al., 1985 ; Alauddin and Tisdell, 1988 ). Descriptive statistics of respondents’ important socio-economic characteristics were analyzed to understand the factors affecting adoption decisions. Among the total respondents, 51.4% belong to the treatment group. The χ2 and F-test result in Table 2 below indicates significant differences between treatment and control groups based on irrigation cost, ROI, educational background, land ownership, farmlands typology, farming experience, knowledge level, fee opinion, soil water retention condition, irrigation machinery ownership, close acquaintances’ adoption, environmental awareness, and secondary income status.

TABLE 2 . Descriptive statistics of the treatment and non-treatment groups.

The mean irrigation cost of the control group is higher than the treatment group, but their ROI is lower than the treatment group. Among the total respondents, 47.98% of the treatment group respondents’ age is higher than 30 years, and the treatment group respondents’ literacy rate is nearly 2.7% higher than the control group. 79.75% of farmers cultivate on mid-low land, while 5.43% do not possess land ownership rights. The average farming experience and the farm size for control group farmers is 7.34% higher and .87% larger than the treatment group. Among 42.89% of households with more than four members, 22.50% belong to the treatment and the rest, 20.39%, belong to the control group. Even though 40.04% of treatment and 35.41% of control group farmers hold proper knowledge of SIF technology, 56.65% of total respondents, including 61.49% control and 52.06% treatment respondents, did not know SIFs adoption aids the environment. Regarding fee opinion, 22.47% of control and 30.51% of treatment group farmers, compared to the rest (47.02%), think the acquisition cost is not high. 45.68% of our respondent farmers have also reported owning other irrigation machinery. Among 1,059 respondents whose close acquaintances have adopted SIF holds, 13.44% belong to the control and 23.92% to the treatment group. In addition, 85.61% of farmers’ seasonal off-farm income is more than 25,000 Taka.

4.2 Determinants of adoption

The factors influencing farm households’ adoption of solar irrigation facilities were analyzed through panel data logit models, and the results are presented below ( Table 3 ). The marginal effects were estimated, as the coefficient result does not express the probability or magnitude. The calculated Variance Inflation Factor (VIF) ranged from 1.06 to 1.84—well below the conventional threshold of 10, suggesting no issue of multicollinearity ( Maddala, 1983 ).

TABLE 3 . Factors affecting the adoption of solar irrigation facility: Panel logit estimates.

The estimated marginal effect for the age variable indicates that the receptiveness toward solar irrigation technology increase by .27% if the farmers’ age is below 30 years. Similar findings from prior work ( Sunny et al., 2018 ; Sunny et al., 2022a ) suggested that younger farmers’ more vehement nature invigorates them in trying newer innovations. In contrast, higher experience farmers’ cautiousness in technology choices is more highly associated with their knowledge of the technology and the expected return against investment aspects.

Land typology results demonstrate that farmers cultivating in mid-high land are 19.8% more likely to adopt SIF than low-midland cultivators. A prior study states that at higher relative landscape positions, water tends to drain more quickly ( Krupnik et al., 2017 ), and Boro rice cultivation requires an adequate and timely water supply ( Sunny et al., 2022c ). Therefore, farmers cultivating in mid-high land are more likely to adopt SIF.

The negative marginal effect value signified that the adoption chance of SIF decreases to .15% when a household size is more than four people. Similar findings suggested that the consumption need of a larger household tends to compete with the investment of new technology adoption ( Sunny et al., 2022a ).

As expected, the marginal effect value suggests that farmers possessing proper SIF knowledge have a .9% higher probability of adopting the technology. Our result matches with prior study findings that suggested knowledge about a specific technology helps farmers to develop insights into the consequences of each option and can counterbalance the negative effect of a lack of years of formal education in the overall decision to adopt a technology ( Sunny et al., 2018 ).

The marginal effects result of the ‘Fee opinion’ predictor indicates that farmers who urge for more reduced service fees are .07% more likely to adopt SIF. Our descriptive statistics also revealed that approximately 54% of control farmers believed that solar irrigation service fees were excessive. Therefore, the relevant authorities must take appropriate measures regarding acquisition fees so that the scheme can attract more farmers and operational organizations and farmers’ possibility of achieving higher economic returns does not diminish.

The negative and significant ‘Soil fertility’ predictor indicates that a farmer with the greater belief that their farmland soil is fertile is .06% less likely to adopt SIF. This result is coherent with findings stating that soil fertility perceptions for Bangladeshi farmers are not fundamentally based on scientific classifications of soil composition (e.g., soil nutrient composition) but on perceived yield ( Sunny et al., 2022b ).

The marginal effect of “secondary income” indicates that the likelihood of adoption is .67% higher for farmers with higher secondary income than their counterparts. This result confirms earlier studies’ findings that higher off-farm income influences new technology adoption ( Rahman et al., 2021 ; Sunny et al., 2022b )). However, farmers having no cash constraints during the cropping season have .37% less probability of being SIF adopters. This finding is meaningful because loan availability does not indicate that the farmers have utilized that money for irrigation purposes and not to avail other essential inputs (i.e., fertilizer, pesticide, and herbicides) ( Rizwan et al., 2019 ; Ouattara et al., 2020 ).

Finally, the marginal effect indicates that farmers knowing that SIF acceptance will aid in carbon footprint reduction are .12% more likely to adopt SIF. This result matches previous research outcomes suggesting that environmental knowledge positively impacts environmental attitudes and environmental attitudes influence behavioral intentions towards the environment. Thus, behavioral intentions toward the environment positively affect pro-environmental behavior ( Liu et al., 2020 ).

4.3 Impacts of SIF adoption

Before finalizing, we tested the appropriateness of the models. Hence, we first checked the parallel trend assumption through the graphical representation. The observed means and the linear-trends model over the pretreatment periods indicate that the trends are parallel ( Figures 1A,B ). Besides, the insignificant F value for the ROI (.73) and Irrigation cost (.32) in Table 4 also suggested the appropriateness of employing the difference-in-differences method. Besides, within the PSM-DID framework, we check the matching quality based on the common support. The common support is the overlap interval of the propensity scores for the treated and control groups. The findings revealed a significant overlap in the propensity scores of treatment and control group respondents, suggesting better matching quality condition is met showed in Figure 2 ; Figure 3 (before and after matching). The balancing test was also performed to compare the balance of the pre-existing variables between the treatment and the control groups after matching. The test result indicated that the mean bias reduces from 12.7 to 4.2 after matching, which indicates that the propensity score matching method reduces the differences between treatment and control groups and eliminates the biases ( Table 5 ; Table 6 ).

FIGURE 1 . Graphical representation of parallel trends for ROI (A) and Irrigation Cost (B) .

TABLE 4 . Parallel test assumption table.

FIGURE 2 . The common support of propensity scores.

FIGURE 3 . The kernel matching of propensity scores.

TABLE 5 . The bias of the mean of the explanatory variables before and after kernel matching.

TABLE 6 . Sample matching methods and the results of balance tests.

Tables 7 below represent the PSM-DID estimates for the impact of SIF adoption on ROI and irrigation cost. The findings show that ROI increased by 20%–30% and irrigation costs reduced by 21%–30% for treatment group farmers (adopters) compared to the control group. The findings match studies documenting solar irrigation adoption benefits in water-stressed areas ( Hossain and Karim, 2020 ; Sunny et al., 2022a ).

TABLE 7 . Impacts of SIF adoption: PSM-DID model estimation.

The positive impact of adoption has significant contributions to the energy sector. The recent energy crisis is not unexpected when considering global geopolitical matters. About 320,000 pumps are run by electricity to irrigate crops on a total of 54.48 lakh hectares in the dry season, which consumes approximately 2000 MW of electricity ( Kanojia, 2019 ). Due to Bangladesh’s energy crisis, the government has decided not to sanction new electricity connections for irrigation. A recent cost comparison study shows that with falling prices, solar irrigation systems have become competitive with grid electricity, while with increasing diesel prices, diesel-based irrigation is getting more expensive ( Haque, 2022 ). Hence, Bangladesh must strongly take initiatives to keep the agricultural sector free from the negative impact of global diesel and other fossil fuel prices’ oscillation and availability issues. The country uses between 15% and 20% of the grid electricity for irrigation purposes. Hence, installing enough solar-based irrigation systems to offset this loss and utilize this energy in other sectors seems more logical.

Studies in India revealed that solar irrigation system adoption not only satisfies farmers’ water requirement for irrigation but also provides an incentive to economies for their energy and contributes to the energy sector by supplying unused energy to the grid ( Patil, 2017 ). Another study revealed that the total power needed for irrigation in southern Europe is 16 GW; substituting this with solar power could offset over 16 million tons of CO2 yearly ( Gillman, 2017 ). Likewise, adopting a solar irrigation system in Spain has increased yield by 35% and reduced energy consumption by 478 MW h annually, delivering 52 TEUR/year financial savings ( Danfoss, 2020 ). Therefore, scale-up SIF adoption can contribute significantly to enabling a sustainable supply of food, energy, and water, particularly in water-stressed areas.

4.4 Robustness checks

We conducted several robustness checks to confirm our main results using fixed effect DID and doubly robust DID estimation methods presented in Table 8 .

TABLE 8 . Impacts of SIF adoption: DID robustness estimation.

Even though Table 7 result in the above slightly differs from Table 8 results in terms of the magnitude of the ATT, the results are similar in terms of ATT’s sign and effect. Both tables’ results suggested that SIF significantly increases ROI and reduces irrigation costs, confirming that the PSM-DID estimates are robust.

4.5 Adopters’ perception of service quality and operators’ view on associated challenges

Table 9 below shows that before 2018 none of the farmers complained about service quality. However, 7.3% of adopters in 2018, 11.7% in 2019, 10.7% in 2020, and 20% in 2021 stated dissatisfaction with the site operators’ behavior and performance. These farmers reported that many site operators practice partiality by providing water to their close acquaintances first, and sometimes they do not care about farmers’ priority.

TABLE 9 . Farmers’ opinion of service quality.

Likewise, around 4.9% of farmers in 2018, 7.8% in 2019, 13.7% in 2020, and 15.1% in 2021 were unhappy with the solar irrigation systems’ performance as the system fails to supply adequate water in the cloudy period and to mitigate the issue, diesel pumps require reinstating. Similarly, 2.9% in 2020% and 4.9% in 2021 expressed disappointment with the service providers’ indifferent attitude toward valuing farmers’ views delaying support issues.

Since farmers were not satisfied with site operators, it would be worth knowing what their counterparts think. Among 30 site operators, 63% stated that not allowing adopted farmers to pay less is the main reason for their dissatisfaction. Further, 23.33% expressed that it becomes difficult to satisfy everyone when water requirements are high in the dry season. The rest, 13.33%, indicated that delay in repairing work due to a lack of skilled workforce is associated with dissatisfaction.

While discussing the challenges, five site operators reported that from 2020 they have been encountering steeling issues with cables and solar panels. They reasoned that the diffusion of solar irrigation facilities hampers diesel and electric pump owners’ businesses, making them unhappy. Apart from highlighting the need to deal with theft, these findings also urge initiatives for solar technicians’ skill development training in remote areas.

5 Conclusion and policy implications

This study examines the impact of solar irrigation facilities adoption on rural household welfare indicators (i.e., irrigation cost and ROI), using panel studies data on 2,835 households from 2015 to 2021. The results of the ATT estimates exhibited a positive impact of SIF adoption on irrigation cost and ROI.

This study’s finding has practical policy implications. Firstly, the beneficial effect of SIF adoption highlighted the need for the government, investors, and shareholders greater focus on designing more appropriate schemes through experimentation and multiple iterations. However, to do so, ministries and agencies responsible for reforming and implementing customs duties, tariffs, and tax incentives need to reassess the market condition and find a solution to minimize the bureaucratic complexity for technology producers and distributors. It should be cognizant that the benefactors’ loan repayment and the sustainability of the operating company depend on generating satisfactory revenue, which is only possible through appropriate site selection. Therefore, before finalizing the site, the responsible organizations should extensively study farmers’ seasonal crop-choosing patterns, future underground pipeline expansion plans, soil slope, potential customers’ attitudes regarding acquisition cost and perceptions towards SIF, and the market price of water-intensive crops. Because shifting the solar site from one place to another would not be cost-effective once the installation is done. Anecdotal evidence from service providers and site operators suggested that our study area farmers’ crop cultivation patterns depend on earlier years’ crop market prices. Likewise, private actors and public agencies need more information and tools to access water resource availability and soil water retention condition to enable more effective and sustainable solar irrigation investment planning. National implementing and regulatory agencies require more robust monitoring capacities. At the same time, the education sector needs to contribute to solar development efforts through training programs and capacity building to expand solar energy and solar irrigation. It is also essential to understand that the schemes to scale up of adoption process must be appealing enough to create strong demand from farmers.

Secondly, respondents’ concern regarding SIF performance indicates solar panels’ efficiency issues. Even though the project report states that these’ panels’ estimated shelf life is 10 years, the farmers are experiencing considerable efficiency decreases in the first 5 years of use. Thus, it seems that there is a need to extensively investigate, develop, and improve the technologies involved while emphasizing the technology’s quality and after-sales service support. Likewise, substituting polycrystalline solar panels with copper bismuth oxide absorber-based thin-film solar cells or mono-crystalline panels will avoid reinstating diesel irrigation systems on peak time and can enhance the SIFs efficiency. These adjustments, nevertheless, need extra funding. Therefore, authorities should consider raising the tenure and grace period from 10 years to at least 20 years and facilitating lower interest rates than the banks offer for general projects.

Thirdly, SIF adoption, apart from contributing to farmers’ wellbeing, can play a vital role in resolving future energy crises if the government speeds up the grid-tied Solar System expansion process. Because due to coal and furnace oil supply-chain disruptions, the future electricity production cost is anticipated to rise compared to the present.

Besides, initiatives introducing insurance schemes or safety nets to hedge against potential theft or production risk are expected to boost farmers’ and investors’ confidence and downside risk. In addition, focusing on region-specific installation of the small, medium, and high-capacity SIFs and strict prohibition of mixed types installation in the same region to avoid internal conflicts between services providers should include in policy priority.

Our findings also pointed to the significance of creative management strategies emphasizing field demonstration programs and campaigns to raise environmental consciousness and benefit recipients rather than just adoption. To better understand farmers’ risk management practices, we also call for more research on how people of different ages perceive SIF and their knowledge of environmental severity.

Finally, implementing farm or community-level evidence-based best practices on solar irrigation solutions while considering the watershed scales and founded on principles of natural resource sustainability and equity will advance us towards achieving a sustainable food production sector.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.

Author contributions

FS and MI planned, designed, analyzed and interpreted the data. FS, TK, and JL wrote the first draft. JL, MR, and HZ critically reviewed the manuscript that went through multiple revisions by FS, TK, MI, and MR. All authors read and approved the final manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenrg.2022.1101404/full#supplementary-material

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Keywords: Energy, Solar Irrigation, Adoption Impact, Panel Data, Difference-in-Difference method, PSM-DID, Fixed effect DID, Doubly robust DID

Citation: Sunny FA, Islam MA, Karimanzira TTP, Lan J, Rahman MS and Zuhui H (2023) Adoption impact of solar based irrigation facility by water-scarce northwestern areas farmers in Bangladesh: Evidence from panel data analysis. Front. Energy Res. 10:1101404. doi: 10.3389/fenrg.2022.1101404

Received: 17 November 2022; Accepted: 30 December 2022; Published: 12 January 2023.

Reviewed by:

Copyright © 2023 Sunny, Islam, Karimanzira, Lan, Rahman and Zuhui. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Juping Lan, [email protected]

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Smart solar powered irrigation system.

Alao Olujimi  |  Izang Aaron *  |  Oyinloye Adebayo  |  Amusa Afolarin  |  Erihri Jonathan

© 2022 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license ( http://creativecommons.org/licenses/by/4.0/ ).

OPEN ACCESS

The desire of man to be in control of everything around him in recent times is born out of the rapid development of smart technologies as everything now depends on the internet. Irrigation system is also becoming smart by using modern technologies, which is more advantageous than traditional irrigation methods. In this work, a smart irrigation system is developed that automates the irrigation process powered by solar energy. This proposed system can optimize the use of water based on different data, such as soil moisture level, weather prediction, and soil temperature. A soil moisture sensor that utilizes IoT technology will be inserted into the farmland to detect the moisture level and then notify the farmer about the current condition of the soil through a developed mobile application. Furthermore, the system can automatically turn ON the motor pump from the mobile app to irrigate the farm when the moisture level and soil temperature are below 50% and will automatically turn OFF the pump after fulfilling the demand of the soil when the moisture level and temperature is above 75%. The whole proposed system is controlled by a microcontroller and a DC power is generated from the solar panel which helps to keep the system working at any time of the day. All these features will make the irrigation system much smarter, more economical, and more eco-friendly. In conclusion, this system is recommended for use by farmers who lives in areas with low access to constant water supply.

irrigation system, internet of things (IoT), microcontroller, moisture level, solar powered

The most abundant source of energy in use today is solar energy. Solar energy is not only a solution to the current energy crisis and lack of light, but it is also an environmentally benign source of energy.

Solar energy is a renewable energy source that helps and does not have a negative or hazardous effect on the environment, solar energy brings a reduced low operational cost long term as there is no need for a variable cost that will be experienced as a result of using fuels. There is no emission of greenhouse gas released into the atmosphere this makes it one of the best sources of energy in use. Solar energy is limitless, it supplies more energy than we will ever need.  Additionally, photovoltaic generating is cited as an effective method for harnessing solar energy [1]. Solar panels, which are made up of a number of photovoltaic cells, are frequently used in communities to drive water heaters, street lights, and other residential appliances [2]. Solar panel prices have steadily declined, which promotes their use in a variety of industries worldwide, including in Nigeria.

Farmlands have recently experienced rapid fertilizer growth and erratic water supply, according to reports from several locations. Due to this, there is significant water and electrical waste during agricultural irrigation processes [3]. Because rain is unpredictable and there is a shortage of water on the ground, irrigation techniques must be done properly [4]. Agriculture is always influenced by soil moisture levels. The quantity and quality of the soil's water content directly influence agricultural production, and this relationship holds regardless of the type of crop being grown [5]. Large amounts of water are wasted when water is used improperly. However, electrical energy is also a significant issue in Africa, particularly in Nigeria [6].

Due to constant water withdrawal from the soil, it has been observed that the moisture level of the soil is decreasing daily. As a result, a proper irrigation system must be carefully planned to avoid this issue. Another issue is the requirement to regularly check the irrigated area to carry out the necessary maintenance and to report fertilization needs [7].

In the past, cost-effective irrigation systems have been created, but they either required large budgets or only utilized conventional, non-renewable sources of electricity. Irrigation systems have always been in place and most have been carried out or supported by non-renewable energy sources that affect the environment. The purpose of agriculture primarily is to provide food to elongate human life, fuels used in irrigation emit gasses harmful to the environment and the agricultural practices themselves. The most logical way is to find means of preserving the environment to better suit agricultural needs. This is where solar energy serves as a better source of power for irrigation agriculture [8]. Large farms must put out enormous effort to maintain all crops by irrigation [9]. As opposed to earlier irrigation systems that did not provide water to all crops, this technique is employed in irrigation systems for farming processes to maintain all crops [10]. Farmers in Nigeria may find a solar-powered irrigation system to be a good alternative at this time due to the country's current energy issue. Once a small investment is made, this green method of energy production offers free energy.

In this study, we suggest a solar-powered automatic irrigation system that uses to transfer water from a bore well to a tank, use water pumps. A microcontroller and a moisture sensor work together to automatically manage the tank's output valve, which controls the amount of water that flows from the tank to the field. Irrigation system that distributes water to all the crops in the best possible way. The other sections of this study comprise of the related works section, the method adopted in this study, the operational block diagram of the smart solar powered irrigation system showing all its components, the circuit diagram that shows the operation of the system and the implications for managers and concluding aspect.

This section provides a quick overview of the efficacy of the smart solar power irrigation system. A detailed description of closely related works and the research gaps in each are provided in Section 2.1.

2.1 Related works

Ashwini [11] studies on smart irrigation systems that utilize IoT to monitor crop fields, uncontrolled water use is causing the groundwater level to drop day by day. In addition, a lack of rain and a shortage of land water cause the amount of water on Earth to decrease. Water scarcity is one of the main issues facing the globe today. In every field, water is a must. Water is crucial in daily life as well. One industry where enormous amounts of water are needed in agriculture. Water waste is a significant issue in agriculture. if extra water is applied to the fields. There are numerous ways to prevent or reduce water waste in agriculture. The system's goals are to a) conserve energy and water resources; b) operate both manually and automatically, and c) determine the water level. In comparison to population growth, the agricultural yield has performed badly due to climatic changes and lack of accuracy. Most canal systems used for irrigation include pumping water into fields at regular intervals.

Due to some crops' sensitivity to the amount of water in the soil, this form of irrigation has a negative impact on crop health and results in a low yield. Unlike a conventional irrigation approach, a smart irrigation system controls the water that is supplied. Smart IoT Fuzzy irrigation system was researched by Kokkonis et al. [12]. In order to continuously monitor the environmental conditions of arable areas, this approach uses inexpensive off-the-shelf sensors and actuators. The approach suggests a comprehensive solution to increase both the quantity and quality of agricultural products. Continuous monitoring is done of soil humidity, moisture content, and air temperature. The humidity of the earth is managed using a servo valve. The system's high-level architecture and each of its component elements is shown and studied. It is built using open-source programming languages and environments like Linux, PHP, and MySQL. Additionally, a brand-new fuzzy computational approach for water irrigation is suggested. Multiple ground humidity sensors' measurements of soil moisture, air temperature, and humidity are used as inputs for the algorithm. The fuzzy system includes three levels for each of the inputs. The algorithm's result determines when the irrigation system's central servo valve opens.

Venkatapur and Nikitha [13] suggested an irrigation system that is powered by solar photovoltaic panels rather than an expensive electric power source. An algorithm was designed with a threshold value of temperature and soil moisture programmed into a microcontroller gateway for efficient and optimal water consumption.

Parameswaran and Sivaprasath [10] put forth a solution to assist farmers in irrigating their land effectively using an automated irrigation system depending on soil moisture. A humidity sensor measures the soil's moisture content, and a microcontroller uses this information to control the solenoid valve. A personal computer is used to update the server's or localhost's irrigation status.

Akubattin et al. [14] created a method to track and regulate the temperature and moisture of the soil inside a greenhouse. The Raspberry Pi-controlled system determines whether to water the plant or turn the greenhouse's fans on based on the amount of moisture in the soil.

Zhang et al. [6] created a system that comprises of a microcontroller, a wireless radio frequency (RF) module, and a data transmission unit (DTU). Expandability is improved by using the RF module in the acquisition terminal. Relay stations gather soil moisture data, which the DTU then sends to the monitoring center through the GPRS network.

Kumar et al. [7] presents an innovative method that uses soil moisture sensors to control the water flow in dry areas. The moisture-dependent principle underlies the sensor's operation. The resistance between two sites in the earth is created utilizing inexpensive components and techniques.

Abayomi-Alli et al. [15] Create an automatic irrigation system that uses solar energy. This will offer a financially sensible replacement for the conventional irrigation technique. The goal of this project is to create a system that uses solar energy for intelligent irrigation and enables more effective water conservation on fields. The created system is transportable and made to fit into the current water infrastructure. The system makes use of NRF module-based wireless communication technology. A Bluetooth network-enabled Android app can be used to easily operate the system. In the user interface, users can choose between automatic control utilizing wireless sensors or manual control for planned irrigation.

Gutiérrez et al. [16] created a GPRS, Zigbee, and radio connectivity-based autonomous solar irrigation system. The wireless sensor unit and the wireless information unit are the two main components of the system, and they are connected by radio transceivers. The ZigBee technology is used to configure the wireless sensor, which includes power supplies, sensors, and a microcontroller. To set up a dispersed sensor network for the automated irrigation system, several wireless sensors can be used on-site.

To determine the volumetric water content of the soil, Gokhale et al. [17] introduced a soil moisture sensor. The soil's dielectric constant, also known as soil bulk permittivity, is the foundation of the sensor. In his plan, LM35 wrapped-in was used to measure the soil's temperature. Using an Arduino Uno, the temperature and soil moisture levels are detected, and the analog values are translated properly. The results are then shown on the LCD and relayed wirelessly over Bluetooth to the control room, which is a few miles distant from the farms.

Vishwanathan et al. [18] proposed a novel soil moisture sensor-based method for managing solar irrigation systems in agriculture. The technology automatically determines the appropriate irrigation activity and notifies the user based on the sensed data. The system also emphasizes how the sensors' communication processes consume solar energy. The workings of the system and its component specifics were also covered in the study.

Rehman et al. [19] featured a user-friendly interface, a wireless automatic watering system, and system status information notification. In order to give the user a choice between manual and automatic operation, the system was developed. Additionally, it provides a data history of system operations.

Sharma [20] proposed a wireless sensor technology as a means of automating the Indian agricultural systems. The recommended system was able to control a number of variables, including humidity, soil moisture, and soil pH, by using wireless sensor nodes that serve as inputs to the peripheral interface controller. (PIC). This data is continuously monitored by the controller, and an inbuilt GSM modem sends the farmer SMSes.

In the end, the research's findings from all related literatures reviewed indicate that irrigation techniques and processes in agriculture and other related fields need to be automated and improved especially in developing countries around the world. Additionally, the findings discovered that using solar energy is the most comprehensive and effective way to create an environment free of harmful gases, - which is closely related to agriculture. Using a renewable energy source is one of the best moves that will have a great lasting effect on agriculture yield and transform how the sector is regarded. In recent years, there has been a great movement and shift towards conserving the environment using renewable energy resources which most related works has tried to implement. But most related works did not consider security issues faced by farmers when trying to access their farmland and the mobility of famers and the need to have access to irrigation from anywhere they are. Therefore, because smart solar irrigation is seen as a tool for promoting the growth of planted crops, therefore finding a practical, long-lasting solution was essential. The aforementioned issues were considered in our work which considered and emphasized that building small and compact yet effective smart solar-powered irrigation system is a need that has now been solved.

2.2 Method adopted in research work

The notion of adaptation from manual and conventional irrigation and monitoring was used in the creation of the System. The input and output components, as well as the necessary hardware and software, must first be classified according to functions. Work is facilitated by the networked use of microcontrollers, sensors, and actuators in embedded design. In this project, the motor is managed by a microcontroller. The C programming language and the MicroC IDE are used to create it. In order to determine whether watering is necessary, two moisture sensors assess the amount of moisture in the soil, calculate the average moisture value, and send the appropriate signal to the microcontroller. Up until the necessary moisture level is reached, the plants receive water from the water pump. The battery serves as the necessary power source.

The solar panel is used to recharge the battery which provides the required power. To determine whether the soil is wet or dry, a moisture sensor is utilized. The input signals are then passed to the microcontroller, which manages the entire circuit. When the soil is dry, the microcontroller issues an instruction to the relay, turning on the motor and supplying the field with water. The motor is turned off when the ground becomes damp.

Two functional units make up the suggested system: a solar pumping unit and a smart irrigation device. The solar pumping device uses solar energy to run the pump. Photovoltaic cells positioned next to the pump set use solar energy to generate electricity. For managing the batteries, a controller circuit is created.

A smart irrigation system, on the other hand, has a solenoid valve that is electronically controlled. This valve, which is used to control the flow of voltage, is controlled by a soil moisture monitoring device. This voltage signal is transmitted to the sensing device, where it is compared to the reference voltage that the farmer can adjust in accordance with the needs of the crop.

The required amount of water is directly proportional to the difference between these voltages. The motor, whose rotating angle depends on the voltage differential, is then provided a signal from the sensing unit. Through solenoid valves, the motor regulates the water flow rate. As a result, the moisture difference is proportional to the volume of water flowing through the microcontroller. It is also connected to a mobile application run by the Global System for Mobile Communication (GSMC), which sends SMS to the user so they can monitor the situation in real time from a distance. The system will automatically open the solenoid valves if the moisture value is less than the current value. The pipe's solenoid valves will automatically close after opening for a predetermined period of time. Because the complete system will be activated once every hour, a plant may more easily keep the moisture it needs. The tank's water level sensor will also monitor the water level there, and if it falls below a predetermined threshold, the system will start the motor pumping water from the well. For each occurrence, the client receives an SMS with information about the water level, motor status, and moisture level. Because all nodes are powered by solar energy from solar panels and because the solar pumping unit pumps water through solenoid valves, the system will have less problems with energy supply. As a result, the fluctuation in moisture differential is inversely related to the field's water flow. The Global System for Mobile Communication (GSMC), which is utilized by farmers for real-time monitoring from a distance, is further connected to the microcontroller.

Photovoltaic cells in the proposed system use sunshine to power it. To determine whether the soil is dry or wet, this method uses soil moisture sensors that are buried beneath the surface. The soil’s moisture is tested to know whether there is water in the soil, this is used to determine when the soil lacks water and will be good for irrigation and when to stop pumping water in order not to have excess water in the soil and destroy the crops. The brain of the device that regulates the entire system is a microcontroller. When the moisture level in the soil decreases, the soil moisture sensor sends a signal to the relay unit, which is connected to the motor. When the soil is dry, the engine will automatically turn on, and when the soil is moist, it will automatically turn off. The sensor placed beneath the soil measures the soil's moisture content and provides a signal to the electronic decision-making unit's microcontroller informing it whether the field needs water or not.

The instructions from the program stored in the microcontroller come before the signal from the sensor, which is received through the comparator's output. The motor automatically turns ON when the soil is dry, and when moisture reaches its present level in a wet state, the motor shuts OFF. On an LCD, the motor's ON and OFF states are shown. A solar photovoltaic cell, a renewable energy source, powers the entire system. These cells transform solar energy into electricity that may either be utilized immediately or stored in a battery. Electric devices are powered by electricity.

A solar panel, charge controller, battery, Ethernet shield, relay, soil moisture sensor, humidity sensor, and DC pump are all components of the Smart Irrigation System. Solar energy serves as a source and produces electricity. A charge controller uses these charges to store them in the battery. The Arduino, humidity sensor, soil moisture sensor, and DC pump all require power from the battery, which is provided by a charge controller. With the aid of a relay and an Arduino, the DC pump can be turned ON and OFF based on readings from soil moisture sensors and humidity sensors. Using an Arduino and Ethernet shield, these data are supplied to the mobile app, which then uses the internet to transmit notifications. The suggested system's operational blocking diagram is shown in Figure 1.

Figure 1. The smart solar powered irrigation system operational block diagram

3.1 The operational block diagram components

The components used to design the smart solar-powered irrigation system are explained in this section.

The soil moisture sensor determines if there is enough water in the soil, if there is, no action is performed, but if there isn’t the soil moisture sensor sends a signal to the microcontroller powered by the battery recharged by the energy trapped from the sunlight through the solar panels. the microcontroller then sends a signal to the water pump that an action is needed, the water pump then pumps water from the reservoir, to the soil and if the soil moisture sensor detects that there is enough water in the soil, the pumping stops. the WIFI allows for a display to be connected to the system to get readings and see the analytics of the performance and also for manual control of the system.

3.1.1 ARM microcontroller

In the realm of digital embedded systems, the ARM-Cortex microcontroller is the most widely used, and most industries only use ARM microcontrollers since they offer a wealth of features that can be used to develop products with cutting-edge looks. The ARM microcontrollers are high-performance, cost-conscious components utilized in a variety of applications, including automobile body systems, wireless sensors and networking, and industrial instrument control systems.

The 32-bit RISC microcontroller known as the ARM, or Advanced RISC Machine, is a type of RISC computer. The Acorn computers company first made it available in 1987. The ARM is a group of microcontrollers created by many producers, including STMicroelectronics, Motorola, and others. Several variants of the ARM microcontroller architecture are available, including ARMv1, ARMv2, etc. and each one has its advantages and disadvantages.

Because the ARM processors have a smaller instruction set than other processors, which enables a smaller size for the IC, they contain fewer transistors. being also space-efficient as a result. These CPUs are found in the majority of electronic gadgets, including tablets, smartphones, and other mobile devices.

3.1.2 Soil moisture sensor

Soil moisture sensors calculate the volumetric water content of the soil. Because the direct gravimetric measurement of free-soil moisture necessitates the removal, drying, and weighing of a sample, soil moisture sensors measure the volumetric water content indirectly by using some other property of the soil as a proxy for the moisture content, such as electrical resistance, dielectric constant, or interaction with neutrons. Since the relationship between the measured property and soil moisture can vary depending on the environment, including the kind of soil, temperature, and electric conductivity, calibration of the relationship is required. Reflected microwave radiation is used in agriculture and hydrology for distant sensing and is influenced by soil moisture. Portable probing instruments can be used by both farmers and gardeners. Soil moisture sensors are generally used to describe sensors that measure the volumetric water content. Another class of sensors that gauge the water potential quality of soil moisture includes tensiometers and gypsum blocks. The term "soil water potential sensors" is another name for these devices.

3.1.3 WIFI (IoT module)

An Internet of Things (IoT) module is a tiny electronic component installed in physical items that connect to wireless networks and transmit and receives data. The IoT module, also known as a "radio chip" or "IoT chip," incorporates the same data circuits and technologies as mobile phones but lacks features like a display and keyboard. The fact that IoT modules offer always-on connectivity is another important point of differentiation. This feature results from the fact that IoT apps must automatically transfer data in real time without a send button being pressed.

They must function consistently for ten years or more in order to support the business case and expense of the technology. They are designed for exceptional durability and longevity.

3.1.4 Water sprinkler

An irrigation sprinkler is a tool used to irrigate lawns, gardens, golf courses, and other locations. It is also known as a water sprinkler or just a sprinkler. They are also utilized for cooling and dust management in the air. Sprinkler irrigation is a technique for putting water under control in a way that mimics rainfall. Pumps, valves, pipes, and sprinklers are only a few of the possible components of the network used to distribute the water.

Sprinklers for irrigation can be utilized in residential, commercial, and agricultural settings. It can be useful for uneven terrain with poor water supplies and sandy soil alike. At regular intervals, the rotating nozzle-topped perpendicular pipes are joined to the primary pipeline. Water escapes from the revolving nozzles when air is inflated through the main pipe. The crop receives a spray of it. Water is piped to a more central place inside the field for overhead high-pressure sprinklers or guns to disperse during sprinkler or overhead irrigation.

3.1.5 Water pump

Water pumps are devices for moving water, and because they transport water from its source to the fields and crops, they are essential to agriculture. A hose, sprinklers, or other types of irrigation can all be utilized with water pumps.

Water pumps come in a broad variety, ranging from basic manual pumps to ones propelled by electricity or fossil fuels.

3.1.6 Lead acid battery

Lead-acid batteries were the first rechargeable batteries used in commercial applications, developed in 1859 by the French physician Gaston Planté. We still don't have any affordable alternatives to cars, wheelchairs, scooters, golf carts, or UPS systems 150 years later. In situations where newer battery chemistries would either be prohibitively expensive, the lead-acid battery has maintained its market share.

Fast charging is not possible with lead-acid batteries. 8 to 16 hours is the usual charge time. To avoid sulfation, a periodic completely saturated charge is necessary, and the battery must always be stored charged. Battery sulfation results from being left in a depleted state, making a recharge possibly impossible.

3.1.7 Osyphotrone photovoltaic solar panel

Using semiconducting materials that show the photovoltaic effect, a phenomena researched in physics and photochemistry, photovoltaics (PV) converts light into electricity. However, employing solar energy as a primary source necessitates the installation of energy storage systems or high-voltage direct-current power lines that add to the expense. The best-known application of photovoltaics is as a way to produce electricity by employing solar cells to convert solar energy into an electron flow through the photovoltaic effect. Solar cells use sunshine to generate direct current electricity that can be used to power devices or recharge batteries.

3.1.8 Solar charge regulator

A solar charge controller regulates the flow of power from the solar array into the battery bank. The deep cycle batteries are not overcharged during the day because of this, and it also stops the batteries from being drained at night by power running backwards to the solar panels. Although some charge controllers have other features like lighting and load management, regulating electricity is their main responsibility.

The Figure 2 below shows the circuit diagram of the smart solar powered irrigation system. This diagram was designed in line with the operational block diagram.

Figure 2 . The circuit diagram of the smart solar powered irrigation system

4.1 System operation

When the soil is dry or when the user so chooses, the Smart Solar-powered irrigation system can pump water to irrigate the soil. The system was tested using the temperature sensor and the soil moisture sensors, which are tools used to detect the soil's temperature as well as the amount of water present in the soil, after the components had been connected and the codes had been written. The ARM Microcontroller receives data from the soil moisture sensor via the programs that have been developed to assign different signals to each component, and the battery that powers the circuit board to which all components are linked is charged by the solar panel.

If the soil moisture sensor requires a response, the microcontroller then sends the information to the pump, which subsequently pumps the water to the soil based on the data the soil moisture sensor is sending it. which means that if the soil is adequately moist, the soil pump does not turn on to irrigate the soil if the water level is below the expected level.

In this research, a smart irrigation system, powered by solar energy was achieved. The system design uses an IoT technology able to monitor and track its operations. By actualizing the proposed framework there are different benefits for the government and the agriculturists/farmers. By using the programmed irrigation system, it optimizes the utilization of water by diminishing wastage and diminishes human intercession for farmers. The overabundance of vitality created utilizing solar panels can be given to the framework with little alterations within the framework circuit.

This research work is very important to people with unreliable access to energy, as it contribute to rural electrification and reduce energy costs for irrigation and also it provides job opportunities, basically to businesses within your locality that deal exclusively in solar panels.

Maintaining the water content or soil moisture is crucial in the world of agriculture. Water usage issues could hinder plant growth and cause farmers to stop farming. This is the primary issue that led to the creation of this project. This technology records data on the amount of moisture in the soil and maintains moisture levels within acceptable ranges. A sensor, specifically a moisture sensor, can be used to measure the amount of moisture. The water pump turns ON or OFF in accordance with the amount of moisture that has been measured. For farmers who do not have unlimited time to water their crops or plants, gardeners and farmers are the main beneficiaries of this research. Additionally, it protects farmers who squander food. water during irrigation. The system can be extended to nurseries where manual administration is distant and few in between.

The managerial implications of the smart solar powered irrigation system is that the system conserves electricity by reducing the usage of grid power which will cost more. It will also offer rural famer a lower cost of running irrigation systems that require the use of fuel to run the traditional method with generator to power the system. Lastly the system also conserves water by reducing water losses due the manual irrigation method.

[1] Jasim, A.M. (2020). An IOT based smart agricultural field monitoring and irrigation system. Journal of Global Scientific Research, 1: 307-316. [2] Kestikar, C.A., Bhavsar, R.M. (2012). Automated wireless watering system (AWWS). International Journal of Applied Information Systems (IJAIS), 2(3): 40-46. [3] Ale, D.T. (2015). Development of a smart irrigation system. International Journal of Science and Engineering Investigations, 4(45): 27-31. [4] Khan, J., Arsalan, M.H. (2016). Solar power technologies for sustainable electricity generation–A review. Renewable and Sustainable Energy Reviews, 55: 414-425. https://doi.org/10.1016/j.rser.2015.10.135 [5] Gutiérrez, J., Villa-Medina, J.F., Nieto-Garibay, A., Porta-Gándara, M.Á. (2013). Automated irrigation system using a wireless sensor network and GPRS module. IEEE Transactions on Instrumentation and Measurement, 63(1): 166-176. https://doi.org/10.1109/TIM.2013.2276487 [6] Zhang, D.N., Zhou, Z.N., Zhang, M. (2015). Water-saving irrigation system based on wireless communication. Chemical Engineering Transactions, 46: 1075-1080. https://doi.org/10.3303/CET1546180 [7] Kumar, A., Kamal, K., Arshad, M.O., Mathavan, S., Vadamala, T. (2014). Smart irrigation using low-cost moisture sensors and XBee-based communication. In IEEE Global Humanitarian Technology Conference (GHTC 2014), pp. 333-337. https://doi.org/10.1109/GHTC.2014.6970301 [8] Kabir, E., Kumar, P., Kumar, S., Adelodun, A.A., Kim, K.H. (2018). Solar energy: Potential and future prospects. Renewable and Sustainable Energy Reviews, 82: 894-900. https://doi.org/10.1016/j.rser.2017.09.094 [9] Hartung, H., Pluschke, L. (2018). The benefits and risks of solar powered irrigation. Rome (Italy): Food and Agriculture Organization. [10] Parameswaran, G., Sivaprasath, K. (2016). Arduino based smart drip irrigation system using Internet of Things. International Journal of Engineering Science and Computing, 5518(5): 5518-5521. [11] Ashwini, B.V. (2018). Surveillance of crop field with smart irrigation system. International Journal of Advanced Research in Computer Science, 9(1). http://dx.doi.org/10.26483/ijarcs.v9i1.5249 [12] Kokkonis, G., Kontogiannis, S., Tomtsis, D. (2017). A smart IoT fuzzy irrigation system. IOSR Journal of Engineering, 07(06): 15-21. http://dx.doi.org/10.9790/3021-0706011521 [13] Venkatapur, R., Nikitha, S. (2017). Review on closed loop automated irrigation system. The Asian Review of Civil Engineering, 6(1): 9-14.  [14] Akubattin, V., Bansode, A., Ambre, T., Kachroo, A., SaiPrasad, P. (2016). Smart irrigation system. International Journal of Scientific Research in Science and Technology, 2(5): 343-345. [15] Abayomi-Alli, O., Odusami, M., Ojinaka, D., Shobayo, O., Misra, S., Damasevicius, R., Maskeliunas, R. (2018). Smart-solar irrigation system (SMIS) for sustainable agriculture. In International Conference on Applied Informatics, pp. 198-212. https://doi.org/10.1007/978-3-030-01535-0_15 [16] Gutiérrez, J., Villa-Medina, J. F., Nieto-Garibay, A., Porta-Gándara, M.Á. (2013). Automated irrigation system using a wireless sensor network and GPRS module. IEEE Transactions on Instrumentation and Measurement, 63(1): 166-176. https://doi.org/10.1109/TIM.2013.2276487 [17] Gokhale, P., Bhat, O., Bhat, S. (2018). Introduction to IOT. International Advanced Research Journal in Science, Engineering and Technology, 5(1): 41-44. http://dx.doi.org/10.17148/IARJSET.2018.517 [18] Vishwanathan, A., Farkade, M., Jha, S., Dubey, P., Pandit, Y. (2016). IoT based irrigation system for methodical agricultural practices. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 5(6): 5156-5161. http://dx.doi.org/10.17577/IJERTCONV8IS14062 [19] Rehman, A.U., Asif, R.M., Tariq, R., Javed, A. (2017). GSM based solar automatic irrigation system using moisture, temperature and humidity sensors. In 2017 International Conference on Engineering Technology and Technopreneurship (ICE2T), Kuala Lumpur, Malaysia, pp. 1-4. https://doi.org/10.1109/ICE2T.2017.8215945 [20] Sharma, A. (2011). A comprehensive study of solar power in India and World. Renewable and Sustainable Energy Reviews, 15(4): 1767-1776. https://doi.org/10.1016/j.rser.2010.12.017

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Solar Based Automatic Irrigation System

7 Pages Posted: 13 Oct 2021 Last revised: 3 Nov 2021

Akhil Adharsh

Kakatiya Institute of Technology and Science, Warangal

Date Written: June 18, 2021

This study was conducted with few objectives of design a microcontroller based solar powered automatic irrigation system (AIS) model. To quantify the paddy field water content of and as well to provide adequate water supply in the right paddy field areas. In agricultural areas this may help for the production of crops as well can prevent the wastage of energy. To provide an efficient design to the farmers is the main objective of this paper.

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Applying pump affinity laws to an isolated solar-powered pumping station  †.

1. Introduction

2. materials and methods, 2.1. design parameters, 2.2. calculation methodology.

• Calculation of incident radiation (diffuse, direct, and reflected) on the generator plane, considering type of structure, inclination and azimuth of the structure, latitude and longitude of the location, and directional properties of diffuse radiation.
• Calculation of effective radiation considers the incident radiation on the generator while accounting for the effect of dirt on the photovoltaic module’s angle of incidence and the power losses due to shadows on the photovoltaic generator; it considers the losses due to the spectral response of the photovoltaic cell type.
• Calculation of the system manometric head: the system resistance curve is calculated based on the pump discharge pipe data as a function of the instantaneous flow rate. Thus, the total manometric head is adjusted according to a 2nd-degree polynomial regression of the form H m = A + B · Q − C · Q 2 (1) where H m is the manometric head in meters (m) and Q is the flow rate in m 3 /h.
• Calculation of the system characteristic curve ( P vs. Q ), based on the pump’s technical data at 50 Hz (H-Q curve, hydraulic P2, motor P2, voltage, number of poles, rpm, efficiency, power factor, etc.), and the system resistance curve, using similarity laws and successive iterations, a system characteristic curve representing the pumped flow (pump operating point considering the system resistance curve) as a function of the power at the pump terminals (motor P1) can be obtained. The pumped flow highly depends on the solar power. Therefore, the pumped flow was represented against the power. A regression to a 2nd-order polygon presented a good adjustment and was taken as an estimate to ease the calculations: Q = a + b · P 2 (2) where the power at the pump terminals ( P ) is in kW and the flow rate ( Q ) is in m 3 /h.

3. Results and Discussion

• Capital cost (solar panels): (163 × 10) × 260 = 423,800.00 €;
• Operational costs (energy): 0.40 kWh/m 3 × 2.59 × 10 6 m 3 × 0.16 = 163,706.92 €.

4. Conclusions

Author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Díaz, J.A.R.; Poyato, E.C.; Pérez, M.B. Evaluation of Water and Energy Use in Pressurized Irrigation Networks in Southern Spain. J. Irrig. Drain. Eng. 2011 , 137 , 644–650. [ Google Scholar ] [ CrossRef ]
• Meah, K.; Fletcher, S.; Ula, S. Solar photovoltaic water pumping for remote locations. Renew. Sustain. Energy Rev. 2008 , 12 , 472–487. [ Google Scholar ] [ CrossRef ]
• Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration—Guidelines for Computing Crop Water Requirements ; FAO: Rome, Italy, 1998; Volume 300. [ Google Scholar ]

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Martínez-Solano, F.J.; Pons-Ausina, J.F.; Iglesias-Rey, P.L.; López-Patiño, G. Applying Pump Affinity Laws to an Isolated Solar-Powered Pumping Station. Eng. Proc. 2024 , 69 , 7. https://doi.org/10.3390/engproc2024069007

Martínez-Solano FJ, Pons-Ausina JF, Iglesias-Rey PL, López-Patiño G. Applying Pump Affinity Laws to an Isolated Solar-Powered Pumping Station. Engineering Proceedings . 2024; 69(1):7. https://doi.org/10.3390/engproc2024069007

Martínez-Solano, F. Javier, Josep Francesc Pons-Ausina, Pedro L. Iglesias-Rey, and Gonzalo López-Patiño. 2024. "Applying Pump Affinity Laws to an Isolated Solar-Powered Pumping Station" Engineering Proceedings 69, no. 1: 7. https://doi.org/10.3390/engproc2024069007

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• Open access
• Published: 27 August 2024

Virtual power plants: an in-depth analysis of their advancements and importance as crucial players in modern power systems

• Sobhy Abdelkader 1 , 2 ,
• Jeremiah Amissah 1 &
• Omar Abdel-Rahim 1 , 3  

Energy, Sustainability and Society volume  14 , Article number:  52 ( 2024 ) Cite this article

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Virtual power plants (VPPs) represent a pivotal evolution in power system management, offering dynamic solutions to the challenges of renewable energy integration, grid stability, and demand-side management. Originally conceived as a concept to aggregate small-scale distributed energy resources, VPPs have evolved into sophisticated enablers of diverse energy assets, including solar panels, wind turbines, battery storage systems, and demand response units. This review article explores the evolution of VPPs and their pivotal roles as major stakeholders within contemporary power systems. The review opens with a definition of VPPs that clarifies both their fundamental traits and technological foundations. A historical examination of their development highlights major turning points and milestones that illustrate their transforming journey.

The methodology used for this article entailed a thorough examination to identify relevant studies, articles, and scholarly works related to virtual power plants. Academic databases were used to gather relevant literature. The literature was organized into categories helping to structure and present information in a logical flow based on the outline created for the review article . The discussions in the article show that the various functions that VPPs perform in power systems are of major interest. VPPs promote the seamless integration of renewable energy sources and provide optimum grid management by aggregating distributed energy resources, which improves sustainability. One of the important components of this evaluation involves taking market and policy considerations. Examining worldwide market patterns and forecasts reveals that VPP usage is rising, and that regulatory frameworks and incentives have a bigger impact on how well they integrate.

Overcoming obstacles is a necessary step towards realizing full VPP potential. For VPPs to be widely adopted, it is still essential to address technological and operational challenges as they arise. Diverse stakeholders must work together to overcome market obstacles and promote the expansion of the VPP market. This analysis highlights the potential for VPPs to propel the evolution of contemporary power systems toward a more sustainable and effective future by highlighting areas for future research and development.

There is an urgent need for creative and sustainable alternatives as the world’s need for energy rises, while fossil fuel-based power generation methods are increasingly scrutinized for their environmental effects [ 1 ]. Centralized alternating current power networks have been widely installed and used worldwide since the 1880s. Evaluations from the 2023 statistical global energy review [ 2 ] revealed that about 82% of the world’s primary energy source comes from fossil fuels like coal oil, and natural gas but their utilization produces greenhouse gas emissions that harm the environment and cause climate warming which has triggered the current global climate crisis [ 3 ]. The contribution of the different sources to world energy consumption is shown in Fig.  1 .

Global energy sources data

On the other hand, energy demand has grown significantly as a result of global economic growth. The demand for electricity has increased steadily over the past decades, by an average of 15%, and is anticipated to increase by 30% by 2040 [ 4 ]. This calls for innovative ideas to support the demand while looking out for the environment. Therefore, distributed energy resources (DERs) must be considered to lessen the detrimental environmental impacts of fossil fuels [ 1 ]. DERs are decentralized energy systems that produce, consume and store energy and are preferably located close to where electricity is consumed. These resources include batteries, wind turbines, solar panels, etc. DERs have been integrated in the power system networks (PSN) and have reduced the effects of energy generation from fossil fuels, furnishing stakeholders with economic and technical benefits [ 5 ]. While DERs offer power systems opportunities, they also bring with them challenges because of their intermittent and stochastic nature. DERs are often described as stochastic and intermittent due to their inherent characteristics and the factors that influence their generation. This nature of DERs is caused by elements including weather changes, operational uncertainties like maintenance, and equipment performance, which can result in unanticipated variations in DER generated or connected output. Instability in the grid is brought on by the rising use of DERs on the demand side, which worsens load demand fluctuations. As a result, real-time monitoring and dispatching are essential for the grid’s safe operation [ 6 , 7 , 8 , 9 ]. Furthermore, the power system needs more adaptability, which can be provided by several mechanisms, such as demand-side management, and energy storage systems (ESS). The only way to properly use these sources to increase their grid contributions is through optimal coordination between different agents [ 10 ].

Over the years, various research has been conducted to address the above challenges and many solutions have been proposed. VPPs have emerged as a ground-breaking solution in an era of energy transition and growing emphasis on sustainable power generation, altering the landscape of contemporary power systems [ 11 ]. VPPs have evolved as key players in promoting efficiency, flexibility, and resilience in the energy industry thanks to their capacity to integrate a variety of energy supplies and improve grid management [ 12 , 13 ].

A VPP is an energy management system that aggregates and coordinates diverse array of DERs, including photovoltaics, wind turbines, battery energy storage systems (BESS), and demand response technologies. The primary function of a VPP is to optimize the collection of these DERs in response to grid conditions, energy demand, and market signal. Through advanced control algorithms and real-time monitoring capabilities, VPPs dynamically adjust energy dispatch schedules, balances supply and demand, and enhance grid stability and reliability.

It is important to note that the concept of VPPs shares some basic similarities with that of the smart grid. However, unlike the VPP which focuses on the aggregation and optimization of DERs, smart grid, on the other hand, encompasses a broader range of functionalities aimed at modernizing the entire electricity supply chain. It can be said that the VPP augment the operation of the smart grid by providing ancillary support like supply and demand balancing to the smart grid.

The combination of these various resources enables the VPP to function as a cohesive and adaptable entity, to be able to react in real-time to grid signals and market conditions [ 14 , 15 ]. In the late 1990s, a pioneering shift in energy research and innovation emerged with the exploration of aggregating distributed resources into a unified virtual power entity, laying the groundwork for the conceptualization and development of VPPs [ 13 ]. Since then, VPPs have evolved from theoretical notions to real-world applications owing to technical developments, and breakthroughs in communication technology. The adoption of VPPs has been hastened by the spread of smart grid technologies and the rise of renewable energy resources (RERs), making them a crucial component of contemporary power systems [ 12 , 16 ].

It is impossible to overstate the importance of VPPs as significant participants in contemporary power systems. VPPs are essential for facilitating the seamless integration of intermittent renewable resources into power grids as they shift from fossil fuel-based generation to renewable-dominated systems [ 3 , 17 , 18 ]. In addition, VPPs can control electricity consumption patterns to correspond with variations in renewable generation. Demand-side management improves grid reliability and efficiency by lowering peak demand and reducing grid congestion [ 19 , 20 ]. VPPs also significantly contribute to the optimization of the energy market. VPPs are crucial actors in the developing electricity market because of their involvement in energy trading and the provision of ancillary services, which help to stabilize prices and maintain system resilience [ 11 , 21 ]. A typical architecture of a VPP is shown in Fig.  2 . With the aid of technology like cloud computing, a VPP aggregates various power consumers, ESS, and power generators to provide flexible adjustments. A communication protocol is used by the components of a VPP to transfer data to the VPP communication system. This communication protocol enables efficient coordination for the VPP to adjust energy production which allows supply to the grid with dependable cost-effective electricity via the electricity market [ 22 ]. The data acquisition platform aids in gathering information about the generation, consumption, and state of charge of the portfolio of DERs for optimal decision-making.

Architecture of a VPP

From the above discussion, it is clear that VPPs have become an important player in modern power systems, providing a dynamic and revolutionary method of managing energy. The idea of VPPs has recently received a lot of interest in energy systems. Studies have provided insightful information by highlighting their potential to transform the way we produce, distribute, and use power. It is critical to understand that this dynamic and developing discipline poses several notable issues, gaps, and areas that require added research.

In the review presented in [ 23 ], an overview of VPP operations, including the integration of DERs, controlled loads, and EVs for resource aggregation and cooperative optimization as well as market and grid operations, is the goal. The evaluation did however not discuss regulatory and policy issues that might affect how widely VPPs are used and implemented in the power market.

Also, the difficulties, solutions, and prospects related to the conceptual review of the conversion of a microgrid to a VPP have also been covered by [ 24 ]. The overview examines RERs integration, opportunities for VPPs in the field of smart distribution systems, and effective management mechanisms. The management mechanism, however, did not discuss the optimization of the DERs for optimal operation. Authors in [ 25 ] gave a thorough overview of the VPP concept and its potential advantages in integrating DERs to assist grid security and stability. Resource optimization, as a main part of the VPP operation, is not covered in this study. Also, Ref. [ 11 ] provided an overview of VPP models and how they interacted with various energy markets. Finding the most profitable VPP scheme to be implemented in each regulatory environment is the focus. DER integration challenges, which affect the operation of VPPs in the energy markets, are not considered in this study. In [ 26 ], the idea of VPPs to participate in various energy markets is proposed. The model evaluates the VPP's technical and commercial prospects. Engaging in various energy markets revolves around sharing of data between the VPP and operators of the markets. The issue of data privacy and cybersecurity was not included in this study. Authors in [ 27 ] provided a review with a focus on integrating DERs into the electricity grid. The assessment gave a summary of the development and use of VPP for carbon reduction in the Chinese power system. The study, however, did not cover technologies that can improve the management and operation of VPPs, notably in addressing the intermittent and volatile nature of DERs. In the domain of energy management, authors of [ 28 ] provided a summary of resource scheduling in VPPs and addressed questions on scheduling procedures. However, despite concentrating on both technical and economic elements of scheduling in VPPs, this analysis did not address potential influences like the state of the energy markets that could have an impact on the scheduling issue. The case of a multi-energy coupled VPP has been presented in [ 29 ]. The purpose of this study was to address the advantages of multi-energy linked VPPs engaging in various energy markets. The issue of enhanced communication technology, data privacy and cybersecurity are some of the challenges which were not featured in this study.

The idea and structure of VPPs are concisely described in [ 30 ] with regard to its two main goals—energy management and power markets. Solutions are suggested to alleviate the problems with DER uncertainties that were highlighted. In order to create future sustainable power grids, authors of [ 3 ] have presented a comprehensive overview of the cutting-edge VPP technology. The study discusses recent technological advancements as well as the significant economic benefits of VPPs. However, this study did not cover the legislation that specifies how VPPs can access and participate in the energy markets. Below are some of the gaps found in existing literature:

Analysis of cybersecurity and data privacy as crucial elements in the VPP development.

Environmental and sustainability focus. The SDGs that VPPs could support, and how the support can be achieved.

Rigor analysis of legislation or regulations which will dictate the operation of the VPP.

Considering the above research gaps in literature, this review article advances the knowledge of energy systems by providing a thorough analysis of VPPs, their historical development, and their crucial roles as essential stakeholders in modern power systems. There will be focus on technical and market operations, real-world case studies, the identification of challenges and prospects, the emphasis on technical and market operations highlight the relevance and transformative potential of VPPs in creating sustainable and effective energy ecosystems. The contributions of this paper can be summarized as follows:

Comprehensive understanding of VPPs to provide readers with a concise definition, key traits, and core values of VPPs.

Tracing historical developments of VPPs from their theoretical roots to their current popularity.

Emphasis on VPPs as key stakeholders in modern power systems. This emphasis highlights the vital role that VPPs play in ensuring grid stability, fostering the integration of RES, and promoting sustainability.

Integration of technical and market aspects by providing a comprehensive analysis of VPP operation. This integration is crucial as it shows that VPPs actively participate in energy markets and actively optimize energy resources, which facilitates effective electricity trading and grid balancing.

Application of cybersecurity and data privacy techniques that protect the VPP from cyber threats, assuring grid stability, data integrity, and consumer trust in the ever-changing energy sector.

Real-world case studies of VPP deployments to offer insights and experiences.

Discussion of the regulatory frameworks that control how VPP operates.

Identification of challenges, providing recommendations, and prospects.

VPP advancements

The traditional centralized power generation model is being replaced by a decentralized, adaptable, and sustainable system thanks to VPP, which represents a revolutionary paradigm in the energy sector. Early theoretical ideas from the late twentieth century established the foundation for the development of VPPs and their eventual prominence in modern power systems [ 31 , 32 ]. This part of the paper will focus on the evolutionary journey of VPPs, highlighting the early concepts, key milestones, and technological advancements that shaped their development into critical enablers of modern energy ecosystems.

The embryonic stage (1990s–2000s)

Although the idea of VPPs was initially put forth in the 1997 [ 13 ] by Dr. Shimon Awerbuch, it did not really take off until the early 2000s. Early academic publications proposed the idea of coordinating and optimizing a portfolio of distributed energy resources to increase operational effectiveness and grid reliability. However, due to limited technological capabilities and a lack of enabling legal frameworks, the practical deployment of VPPs remained primarily theoretical at this point. Also, the absence of developed distributed generating technology, the high cost of communication and control systems, and the regulatory uncertainties surrounding VPPs were some of the causes of lack of practical deployment. References [ 33 , 34 , 35 , 36 , 37 , 38 ] provides a description of the early years concept of the VPP, its difficulties, including consumer resistance to participating, economic viability in infrastructure setup, investors' perceptions of risk, and grid operators' reluctance to adopt the unique strategy.

The breakthrough stage (2010s–2020)

The growth years presented milestones and key turning points in VPP deployment from the early years. At this point, the VPP has encountered rapid growth as a result of increasing interest in adoption of distributed generation technology, decreasing communication and control system costs, and expanding regulatory backing for VPPs. In a declaration on the future of the European electricity market that was issued in 2011, the European Commission emphasized the potential of VPPs to increase grid flexibility and integrate renewable energy. This communication aided in increasing policymakers’ and stakeholders’ understanding of VPPs [ 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. Later, in March 2023, it was amended in Strasbourg, France, by recommending an expansion of the EU electricity market structure to further integrate RESs, improve customer protection and industrial competitiveness [ 46 ]. Notable milestones of the growth years include grid integration [ 47 ], market participation [ 48 ], technological advancement, and demand response programs[ 49 ], allowing aggregated DERs to respond to grid signals and enhance grid stability [ 50 ]. This marked the initial practical application of VPPs, showcasing their ability to support grid operations.

The future (2021 and beyond)

The demand for flexible grids and the incorporation of RESs is anticipated to drive further growth of VPP. VPPs are viewed as one of the techniques to lower carbon emissions and increase energy efficiency [ 51 ]. The key drivers for this growth are the increasing deployment of distributed generation technologies (DGT), falling cost of communication and control systems, growing regulatory support for VPPs, and also prosumers who want to receive incentives for their surplus generation [ 45 ].

In summary, it is evident that early theoretical insights were followed by practical and revolutionary applications in modern power systems as VPPs evolved. The development of VPPs into essential enablers of decentralized, flexible, and sustainable energy ecosystems has been shaped by significant turning points and milestones, as well as technological development and innovations. A thorough summary is provided in Table  1 for further reading.

VPP planning, roles, and sustainability

VPP planning is a crucial and multifaceted process that entails strategic design, coordination, and optimization to provide effective and dependable energy management. The main goal of VPP planning is to maximize the advantages for both grid operators and consumers while optimizing the potential of varied DERs and guaranteeing their seamless integration with the power grid. The planning approach necessitates a thorough comprehension of the energy landscape, individual DER capabilities, market dynamics, and regulatory frameworks.

To ensure that VPPs perform as planned and expected, their technological constraints must be recognized and measured [ 55 ]. Before interacting with external and internal elements, the VPP schedules and plans its operations. It is also a good performance criterion for the VPP to keep accurate data to engage the electricity market and reap favorable effects by analyzing the uncertainties resulting from elements like weather and producing forecasts with a high level of assertiveness [ 56 ]. The issue of forecasting will be discussed later in the section dedicated to the roles of VPPs. The VPP operations may be constrained by infrastructure, technological, and technical limits [ 57 ]. The model shown in [ 26 ] emphasizes the importance of effectively measuring and managing controllable loads in heating, ventilation, and air conditioning (HVAC) systems. Also, it emphasizes the significance of photovoltaic (PV) and BESS influences in determining the viability and adaptability of a VPP. VPPs can improve their coordination with all stakeholders by developing a methodical technique for evaluating and controlling power availability at time intervals. Surely, this enhances the performance of the VPP and enables a more seamless interaction with the power grid.

VPP planning also includes economic and legal factors in addition to the technical ones. The aspects of technical and economic frameworks of the VPP will be delved deeper in the sections dedicated to the technical and economic aspects of VPPs. It is important to note that good operational planning directly affects good economic outcomes [ 55 ]. The economic viability of the VPP and its prospective revenue streams, including energy trading [ 58 ], demand response participation [ 59 ], and the supply of ancillary services [ 21 ], are assessed using financial models and cost–benefit analysis [ 60 ]. Collaboration with grid operators, legislators, and other stakeholders is also necessary for successful VPP planning to overcome regulatory obstacles and build an environment that facilitates VPP integration. To ensure effective planning, the VPP should be continuously monitored and improved to respond to shifting grid conditions and market dynamics [ 61 ]:

VPP planning opens the way for a more resilient, and sustainable energy future by integrating technological, economic, and regulatory factors. It has enormous potential to optimize resource use, improve grid stability, and contribute to the global quest for a reduction in carbon emissions produced by energy systems. It is therefore imperative that stakeholders comprehend the complexities of VPP planning to influence the energy industry’s future and advance the cause for greener and a more sustainable and effective energy future. This planning phase can be summarized as: aggregating existing and new energy resources.

Ownership structure: The internal ownership structure of VPPs can vary depending on the specific implementation and stakeholders involved. It may involve collaboration between multiple stakeholders including energy producers, consumers, and aggregators.

Regulating and market considerations governing energy markets and grid operations.

Implementation of an energy management system to provide functionalities such as real-time monitoring, forecasting, dispatching, and scheduling energy resources to meet grid requirements and maximize economic benefits.

Agreement formulation such as power purchase agreements.

Profit sharing mechanisms taking into consideration factors such as investment contributions, operational cost, risk allocation, etc.

Compensation structures for various stakeholders involved in the VPP including incentives for demand response participations from consumers.

The way electricity is produced, controlled, and used has been revolutionized by VPPs as explained in the previous sections. VPPs are flexible and dynamic entities that perform a variety of roles in modern power systems. Because of the variety and importance of their tasks, they are key players in creating an energy ecosystem that is sustainable, effective, and resilient. The following are the main responsibilities of VPPs in power systems.

Aggregation of DERs: Various DERs, such as solar panels, wind turbines, ESS, EVs, and demand response loads are gathered by VPPs. VPPs construct an adaptable and manageable portfolio of assets by combining these decentralized resources into a single virtual entity. Through this aggregation, grid management is improved, enabling the VPP to maximize DER usage in response to grid signals. The DERs’ activity within the VPP is managed and coordinated by the VPP operators. The main responsibility is resource optimization and involvement in energy markets.

The authors of [ 62 ] described the aggregator concept as a central control node that collects information from both the power grid and controlled loads. A load aggregator can also serve as a conduit between the controllable loads and the grid operator, allowing the regulated management to consider user and grid benefits simultaneously. When interfacing with the power market, aggregators are employed in power charging models for EVs to help optimize the batteries’ charging as well as the modeling of driving patterns and price estimates [ 63 ]. As DERs are dispatched depending on compensation rates and power levels, an aggregator can stand in for them to maximize profits [ 64 ]. Furthermore, in [ 65 ], for a power market with bilateral contracts, the aggregator has the facility to select between various power plants based on power-cost-based offers.

Grid stabilization and reliability: VPPs make a major contribution to the reliability and stability of the grid. VPPs maintain a stable and steady supply of electricity while minimizing the possibility of blackouts and voltage variations by balancing energy generation and consumption from various DERs [ 66 ]. They are able to provide ancillary services like frequency regulation and voltage management, which are essential for preserving grid stability [ 67 ]. The general stability and dependability of the electrical system are the responsibility of grid operators. In accordance with grid norms and standards, the grid operators work with VPP operators to incorporate DERs.

Renewable energy integration: In 2016, in Paris, an emission reduction plan was enacted which has made the use of DERs very essential [ 68 , 69 , 70 ]. This integration is the VPP operator’s responsibility. This is accomplished by coordinating the operation of diverse RERs, such as solar panels, wind turbines, and such that they work as a unified system. However, due to their erratic nature, integrating RESs into the power systems presents its own challenges [ 71 , 72 ]. These challenges come about because of generation fluctuations due to weather conditions and time of the day. The variability adds complexity to power system operations. For instance, rapid changes in wind speed or cloud cover can result in fluctuations in generation, requiring grid operators to make quick adjustments to maintain system stability. VPPs take on this problem by combining several RESs and using intelligent management processes, they make it easier for the integration of the RESs effectively. They ensure the integration of these RESs to provide a steady supply of electricity while lowering reliance on conventional fossil fuel-based power plants.

Authors in [ 72 ] proposed a solution for integration of RESs into the grid to maintain power quality. This is important because RESs are becoming increasingly popular due to their environmental benefits, but they can also introduce power quality issues. This is a challenge that a VPP is sought to address. Large scale penetration of RESs means a hike in capital and operational cost. Authors in [ 73 ] discussed a mechanism that could aid in lowering the high cost of RESs integration and bringing electricity prices into affordable band. Spreading the benefits of renewable integration into the spheres of agriculture, where in [ 74 ], authors have created a mechanism to encourage energy-efficient agriculture by minimizing dependency on fossil fuels for water-table pumping. Through the aggregation and optimization of DERs, VPPs enable farmers to reduce their dependency on fossil fuels while enhancing energy efficiency and resilience in agricultural practices. This synergy not only fosters economic sustainability for farmers, but also contributes to the broader goal of renewable energy integration, paving the way for a greener energy future.

Successful integration depends on several important aspects. Forecasting methods that accurately estimate the patterns of RESs generation must be put in place [ 75 , 76 ]. This allows better grid management and optimization of the DERs. The VPP employs such tools to better manage the generation of DERs. A summary of various forecasting techniques provided in the literature is listed in Table  2 . Analysis of forecasting models to aid in the integration of RESs in the context of VPPs has been provided in [ 77 ].

Moreover, for optimal integration of RESs, the power grid must be modernized with smart technologies. Real-time monitoring, control, and communication between DERs and grid infrastructure are made possible using smart approaches like the VPP [ 16 , 78 , 79 ]. This improves the reliability and effectiveness of the grid. Additionally, VPPs provide beneficial grid functions, such as frequency regulation [ 67 ] and voltage control [ 80 ] in addition to balancing energy supply and demand [ 81 ]. These services boost the grid’s dependability and resilience even more, promoting a stronger energy infrastructure that can handle the rising proportion of RESs.

The VPP approach to integrating RESs into the power grid is a cutting-edge strategy that is revolutionizing the way energy is produced, distributed, and consumed. VPPs offer an effective response to the problems caused by intermittent renewables by utilizing the combined potential of DERs and modern technology. VPPs will unquestionably be essential in advancing the transition to a cleaner, more dependable, and efficient energy system as the world progresses toward a sustainable energy future.

DER technologies applied in VPPs

In VPPs, various DERs are used, including solar panels, wind turbines, ESS, EVs, and demand response loads. These DERs are aggregated and optimized within the VPPs, allowing for efficient management and coordination [ 55 ]. By harnessing the collective capacity of diverse DERs, VPPs enhance grid stability, enable renewable energy integration, and support demand response strategies, contributing to a more sustainable and flexible energy ecosystem. A VPP should ensure that DER integration keeps the system operating properly by ensuring the stakeholders’ continual consumption requirements [ 92 ]. Various DER technologies applied in VPPs in the reviewed literature are summarized in Table  3 .

Out of the 15 References evaluated regarding DER technologies used in VPPs, it is evident from Table  3 that wind turbines and solar panels hold the largest share, as shown in Fig.  3 . It proves how easily the technology of wind turbines and solar panels have been embraced. However, more renewables should be added to the energy mix to hasten the shift to a less carbon-oriented energy landscape.

DER application in literature

VPP sustainability focus

One of the viable ways to address numerous Sustainable Development Goals (SDGs) of the United Nations (UN) and contribute to a more sustainable energy future is through VPPs. By encouraging the integration of RESs and boosting energy efficiency, VPPs, as a fundamental enabler of the energy transition, contribute significantly to achieving SDG 7 (Affordable and Clean Energy). VPPs promote the integration of sustainable energy into the power grid by aggregating and optimizing DERs thereby lowering greenhouse gas emissions and addressing climate change (SDG 13—Climate Action).

Additionally, through promoting technological advancements and innovation in the energy industry, VPPs provide a substantial contribution to SDG 9 (Industry, Innovation, and Infrastructure). VPPs promote grid modernization and improve overall energy infrastructure by integrating smart grid technologies, advanced analytics, and artificial intelligence. These developments result in more effective and adaptable energy systems, advancing the objectives of SDG 9 to develop robust infrastructure and encourage sustainable industrialization.

However, while VPPs offer considerable potential for achieving various SDGs, several challenges must be addressed to ensure their long-term sustainability. Access to VPP technologies must be equally available, as this can influence SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). For VPPs to be deployed in a way that supports SDG goals for eradicating poverty and minimizing inequality, marginalized people and neglected areas must be able to benefit from them. In simple terms, it is essential to make sure that everyone has an equal opportunity to profit from VPPs to realize SDG 1 and SDG 10. This calls for figuring out ways to make technology more accessible and inexpensive for everyone, especially those living in rural or underdeveloped areas. By doing this, VPPs may contribute to the development of a more just and sustainable energy future in which everyone, regardless of financial situation, has access to safe and dependable energy.

Furthermore, the environmental impact of VPPs [ 108 ] and their associated technologies require careful consideration to achieve SDG 12 (Responsible Consumption and Production). Lithium-ion batteries, which are used in ESS, are one example of a crucial mineral and material whose demand is on the rise, prompting questions regarding responsible sourcing, recycling, and end-of-life management. It is not a surprise that there has been extensive literature on ways to increase the lifespan of lithium-ion batteries [ 109 ]. Authors in [ 110 ] proposed a precise lifespan model for the battery cells used in VPP applications. To reduce the negative environmental and social effects of VPP deployment, sustainable methods must be implemented in material sourcing and VPP operation.

Moreover, numerous steps can be taken to guarantee the sustainability of a VPP itself. Stakeholders must work together to build supporting regulatory frameworks and financial incentives for VPP development. VPPs will become more widely available and long-lasting if investments are encouraged in their research, development, and implementation. This will also encourage technological breakthroughs and cost reductions. Also, a successful integration of VPPs into the energy economy depends on raising consumer awareness and engagement. The acceptance of VPP technology can be increased by educating consumers about the advantages of VPP participation, such as lower energy costs and increased grid reliability [ 111 , 112 ].

To sum up, VPPs have a significant potential to help achieve several SDGs pertaining to renewable energy, tackling climate change, and sustainable infrastructure. They support SDGs 7 and 9 by fostering the integration of RESs and improving energy efficiency. To achieve more general sustainability goals, it is necessary to address issues with fair access to VPP advantages and responsible use and production. VPPs are critical enablers of a greener, more inclusive, and resilient energy future and can help accomplish specific SDGs by establishing supportive policies, encouraging innovation and consumer engagement. Using VPP's revolutionary potential in promoting the UN’s sustainability agenda [ 113 ] requires advocating for and making contributions to their sustainable deployment and optimization.

Cybersecurity and data privacy

The protection of the grid’s stability and dependability is one of the main justifications for prioritizing cybersecurity in VPP application. As crucial nodes in the grid, VPPs coordinate the functioning of DERs and provide a constant and reliable supply of electricity. A cyber-attack on a VPP has the potential to impair energy production, distribution, and grid management, resulting in power outages [ 114 ] and large financial losses.

The efficient operation of VPPs depends on data integrity [ 115 ]. For making decisions about the generation, distribution, and use of energy, VPPs depend on accurate data. Cybersecurity measures guard against data alteration or manipulation, ensuring that VPP operators have reliable data for maximizing energy resources and delivering crucial grid services. In order to increase consumer and prosumer confidence in VPP services, data privacy procedures on data collection and usage are essential [ 116 ].

VPPs are desirable targets for cybercriminals because of their crucial functions in grid management and their strength in the marketplace. VPPs are shielded by cybersecurity from a variety of dangers, such as malware and hacker attempts [ 117 ]. To address the cybersecurity issues, various approaches have been suggested and has been categorized by [ 118 ] as human and non-human approaches. Human approaches like updates and incremental patches installation aids in robust security posture, addressing vulnerabilities in software, but also require reboots causing downtime to regular operations. Engaging in customer interactions also creates awareness to recognize and respond to potential threats. However, allocating time and resources may be challenging for organizations with limited budgets and manpower.

Non-human approaches like the adoption of blockchain technology reduce the risk of single point failure as the technology operates on a decentralized network. This enhances resilience, making it more challenging for attackers to compromise the entire system. Another non-human approach is cloud computing which typically encrypts data during transmission and storage. This safeguards sensitive information from interception or unauthorized access.

Data privacy and cybersecurity are essential elements of VPP operations. They protect against cyberthreats, guarantee data integrity, enhance grid stability [ 119 ], promote consumer trust, enable regulatory compliance, and support the viability of VPPs financially. To ensure a secure, dependable, and sustainable energy future, cybersecurity and data privacy must be prioritized as VPPs continue to develop and broaden their role in contemporary energy systems [ 120 ].

Regulation and compliance

The operation of VPPs is greatly influenced by legislative or regulatory activities. This section will cover the regulatory structure that governs VPPs, emphasizing significant importance and their effects on the energy industry.

In the domain of grid integration standard and requirements, regulating bodies establish grid codes and integration standards that the VPP must adhere to when connecting to the electrical grid. The safe and dependable grid integration of DERs is ensured by these standards. The basis for secure VPP functioning is grid codes and standards. A manual for connecting DERs to the utility grid is provided by the IEC 62786. DER planning, operation, protection, and connectivity to distribution networks are the key applications. A global agreement on the use of DER in electrical power systems is being sought through the IEEE 1547 set of standards. This standard has received widespread acceptance on a global scale in outlining the requirements for the design, implementation, testing, and security of all sorts of DERs. Due to the increased penetration of DERs and the need to maintain system stability, the IEEE 1547 has recently been updated to IEEE 1547-2018 and IEEE 1547.1-2020 [ 121 ]. A crucial series of standards released to control the grid’s interconnection and operability is the IEEE 2030. It is modified to implement cutting-edge communication and information technologies that provide interoperability solutions for the promotion of DER connectivity.

The European Committee for Electrotechnical Standardization (CENLEC), which is made up of 34 European Nations, oversees standardization efforts to increase commercial viability and foster technological growth. The CENLEC released the EN 50549-1 and EN 50549-2 DER integration standards with the goal of addressing all DER capabilities that are necessary for operation in tandem with distribution networks [ 121 ].

Also, there may be regional variations in regulations governing the integration of DERs with the grid [ 121 ]. For example, Canadian standards C22.3 No. 9 and C22.2 No. 257 offer technical advice for DER integration with the grid at medium and low voltage under 50 kV and low voltage systems under 0.6 kV, respectively. The British standard BS EN50438:2007 also offers technical advice for DER interconnection. The VDE-AR-N 4105 standard in Germany also offers technical recommendations for connecting DERs and low voltage systems. The JEAG.9701-2001 standard in Japan offers technical recommendations for distributed generating grid-connection. The standard permits DER owners to sell surplus energy to utility grids and mandates that power grids supply DER owners with backup power.

Various environmental and sustainability regulations may pertain to different jurisdictions [ 122 ], and they may provide incentives or requirements for VPPs to assist the integration of RERs and the reduction of emissions. In certain regions, these rules may have an impact on how VPPs function. The level of support for VPPs that use RERs may vary depending on the targets and incentives that jurisdictions set for renewable energy [ 123 ].

VPP operators and stakeholders must negotiate a complicated regulatory environment that is unique to their locations. It is essential for the implementation and operation of VPPs to comprehend and follow local legislations. Furthermore, as VPPs become more crucial to the world’s energy landscape, regulators and industry participants must cooperate to unify rules and encourage uniformity in grid integration techniques across various jurisdictions.

Technical aspects of VPPs

The technical operations of a VPP involve a series of complex and coordinated processes to efficiently manage and optimize the aggregated DERs within the VPP. According to Ref. [ 124 ], the technical features of VPPs provide dynamic interaction for the integration of power distribution based on auxiliary services. These technical operations can vary depending on the specific architecture and goals of the respective VPP. This section of the paper delves into the technical intricacies of VPPs and explores their roles as key enablers in the transition toward a sustainable and resilient energy future. Some of these technical aspects of the VPPs are emphasized below:

Resource optimization and scheduling: In a VPP, resource optimization and scheduling of various DERS are essential to achieve efficient and reliable energy management [ 28 , 125 ]. It is also important to note that advanced algorithms and real-time data analytics [ 76 ] as summarized earlier in Table  2 are employed to forecast energy generation and demand profiles, ensuring dynamic resource optimization. The VPP intelligently dispatches DERs based on grid conditions and market signals, balancing supply and demand to enhance grid stability and maximize revenue generation [ 126 ]. By coordinating diverse DERs, VPPs optimize energy use, contribute to renewable integration, and support grid flexibility, making them crucial enablers in the transition to a sustainable resilient energy ecosystem.

A summary of the relevant literature in accordance with resource optimization and scheduling is provided in Table 4 .

Load balancing and grid support/ancillary service: The load balancing and grid support functions of a VPP are very crucial [ 135 ]. The VPP dynamically modifies energy generation and consumption to fit grid demands by aggregating and optimizing various DERs. While storing excess energy during times of low demand, the VPP can supply additional power from DERs during times of peak demand to balance out high demand. This load-balancing ability makes VPPs essential for guaranteeing a dependable and resilient electricity supply since it improves grid stability, lowers grid stress, and adds to overall grid support.

In addition to its role of aggregating and optimizing DERs, a VPP offers a range of essential ancillary services. These services include frequency regulation. This is achieved by maintaining grid frequency within acceptable bounds through rapid power adjustment [ 136 , 137 , 138 , 139 ]. VPPs also provide voltage support by injecting or absorbing reactive power to stabilize voltage levels [ 80 , 140 , 141 ].

Moreover, VPPs contribute to peak regulation, managing demand during high load periods to alleviate grid stress [ 142 , 143 , 144 ]. The comprehensive suite of ancillary services offered by VPPs ensures grid stability, enhances reliability, and facilitates the integration of RESs, making them vital assets in modern power systems.

Demand response and load management: A VPP inherent components of demand response and load control enable effective energy usage. By actively communicating with connected consumers to alter electricity consumption in response to grid circumstances and price signals, VPPs participate in demand response. In order to avoid peak demand times and lessen grid load, VPPs optimize the scheduling of operations and equipment that consume a lot of electricity [ 59 , 81 , 96 ]. This demand-side flexibility not only supports grid stability, but also empowers consumers to actively participate in energy conservation, contributing to a sustainable energy ecosystem [ 66 , 145 ]. The VPP’s ability to efficiently balance energy supply and demand through demand response and load management strategies makes it a pivotal stakeholder in modern power systems.

The technical aspects of VPPs represent a dynamic and transformative force in the energy sector. VPPs provide effective renewable energy integration, grid stability, and demand response capabilities by aggregating and optimizing various DERs.

Market/economical aspect of VPP

VPPs provide an appealing scenario for the future of energy systems in terms of their commercial and financial prepositions. VPPs can completely alter the economics of electricity generation and consumption as they are dynamic aggregators of various DERs. VPPs maximize the use of DERs, optimize income generation, and improve participation in the energy market [ 11 ]. The VPP does this via real-time data analytics, complex forecasting algorithms, and clever energy trading methods. As a result of their capacity to offer a versatile and dispatchable portfolio of assets (DERs), VPPs are better equipped to meet swiftly to dynamic market conditions, such as energy pricing and demand patterns. VPPs deliver a strong economic case for sustainability, affordability, and resilience in the energy ecosystem by making it possible to efficiently deploy renewable sources of energy, support demand response programs, and provide ancillary services to the grid. VPPs technology’s commercial implications hold significant promise for developing a more effective, competitive, and customer-focused energy landscape as it continues to advance.

Currently, the majority of jurisdictions have already started deregulation or liberalization and competition-opening process in their individual power markets [ 11 ]. In order to finance new infrastructure investments, increase the economic efficiency of power company operations, and particularly lower the ultimate prices of electricity delivery, deregulation or privatization has been advocated [ 146 ]. A vertical structure as stipulated by [ 146 ], where all activities were merged, was replaced with an organization where generation, transmission, distribution, and commerce work separately as a result of this reform in the energy sector.

Additionally, the large integration of renewables into the power grid that characterizes the contemporary energy landscape suggests a greater need for the system’s balancing mechanism due to the random nature of the RESs generation schedule. One significant benefit of VPPs is that they boost their shared profit by selling energy on behalf of the DER owners to improve the balancing mechanism when they access the wholesale electricity markets. The participation of VPPs in various electricity markets is covered in this section.

Day-ahead market: Day-ahead market refers to the buying and selling of electricity on the day before the actual production and delivery. VPPs actively participate in the day-ahead market by supplying their aggregated portfolio of DERs for electricity trading. VPPs forecast energy generation trends for the next day using advanced forecasting and data analytics. Based on these insights and market prices, VPPs strategically bid these aggregated resources to optimize revenue generation [ 84 , 147 , 148 , 149 , 150 , 151 ].

Ancillary service market: VPPs actively participate in the ancillary services market by providing critical assistance to the electric grid. The VPP does this by dynamically altering the output of their aggregated DERs. VPPs respond in real-time to grid signals to maintain stability, assure a continuous power supply, and improve grid reliability. With this, VPPs play an important role in supporting grid operations and optimizing grid performance. Several studies have incorporated the ability to engage in ancillary services markets into VPP modeling in order to enable regulation that ensures the security of electricity supply [ 26 , 143 , 150 , 152 , 153 , 154 , 155 , 156 ].

Reserve market: In the reserve market, VPPs actively participate by offering their combined output of DER as a reserve capacity to support the grid’s reliability. VPPs reserve a portion of their generated power from the DERs, ready to be dispatched within short notice to address sudden changes in electricity demand and supply or even an outage of grid operator’s outage of generators. By participating in the reserve market, VPPs offer a valuable and flexible solution for grid operators to maintain grid reliability. As VPP technology advances, their involvement in the reserve market will become ever more vital in contributing to the efficient and secure operation of the electric grid. Various strategies to make ideal or optimal reserve market decisions have been studied in several papers. According to the findings of these studies, the reserve market is more significant at times of peak demand since a contingency can have a higher impact [ 26 , 127 , 157 , 158 , 159 , 160 ].

Intra-day/real-time market: The VPP actively participates in the intra-day market by precisely adjusting the energy traded in the day-ahead market. The VPP strategically optimizes its DER dispatch and offers flexible resources in response to dynamic market prices and grid needs [ 11 ].

Although intraday markets enable VPPs to adjust scheduled energy after the day-ahead market, an exchange power imbalance may still emerge as the dispatch time approaches. VPPs can thus participate in real-time balancing markets to avoid penalties. The goal of the real-time market is to reduce the imbalance errors and their associated cost. The various electricity markets in which the VPP participates are provided in Table 5 to outline the key characteristics. Figure 4 also gives a graphical analysis of the key characteristics of the electricity market that the VPP operates in.

Electricity markets characteristics

Real-world implementation of VPPs

VPPs in the real world provide fascinating insights on their revolutionary impact on contemporary power systems. VPP implementations around the world demonstrate their adaptability in maximizing DERs. These examples elaborate on the value of VPPs in grid stability, renewable generation, and demand response. VPP projects are becoming more common, proving their potential to revolutionize energy systems. The VPP market is expected to grow from $1.3billion in 2019 to $5.9billion in 2027, with a compound annual growth rate of 21.3% from 2020 to 2027 [ 25 ]. In Norway, Statkraf is the world’s largest VPP with a capacity of 10GW from over 1000 aggregated assets. Recently, Tesla announced to scale up the south Australia VPP which connects assets from 4000 to 50,000 homes, which will make it the world’s largest VPP [ 172 ]. Storing and distributing power from residential and commercial customers, Tesla’s Powerpacks and Powerwall promote grid dependability and the integration of renewable energy. These real-world examples demonstrate how important VPPs are in creating a global energy ecosystem that is robust, efficient, and sustainable. Selected real-world applications [ 124 , 172 ] are summarized in Table  6 .

Applications of VPPs in the real world have offered an important lesson that will guide their development, deployment, and scalability. Key insights from these applications include the following but not limited to:

Flexibility and scalability: The significance of developing flexible and scalable systems has been shown by the successful VPP deployments. VPPs support a variety of DERs and adjust to shifting market dynamics and grid conditions.

Integration of DERs: For the VPP to operate at its best, several DERs must be integrated into a single, coordinated system. Advanced data analytics and control algorithms are essential for managing DERs efficiently and maximizing their contributions, as demonstrated by real-world applications.

Interoperability and interconnection: VPPs generally operate in sophisticated energy ecosystems with a variety of stakeholders. Smooth VPP integration and operation require interoperability and seamless interconnection with grid operators, and other market participants.

Market participation: The significance of active market participation has been emphasized by real-world VPP applications. Using effective energy trading techniques and intelligent bidding in electricity markets. VPPs can maximize income production and assist the integration of RESs at a fair price.

The ongoing development and deployment of VPPs can be improved by taking lessons from these practical applications, ensuring that they continue to contribute to a sustainable, effective, and decentralized energy future.

However, despite the successes chalked up by these projects, there are still challenges that must be addressed. Cybersecurity threats, consumer engagement, data management and analytics, achieving a positive return on investment and profitability are some of the model challenges that these projects face. Collaboration between stakeholders is necessary to overcome these obstacles.

Conclusions

VPPs have become transformative solutions revolutionizing the modern energy landscape. Applications in the real world have sounded their importance and have also demonstrated the adaptability and advantages of VPPs. VPPs have shown that they can promote the integration of renewable energy sources, aggregate and optimize a variety of DERs, and facilitate effective demand response.

Flexibility and scalability, which enable seamless adaptability to shifting grid conditions and market dynamics, have been shown to be essential for successful VPP adoption. VPPs have been able to improve cost-effective renewable energy integration and optimize revenue generation through active market participation and smart bidding tactics. Additionally, for VPPs including residential or commercial participants, consumer engagement and education are crucial for assuring buy-in and demand response programs.

Embracing the lessons learnt in the referenced literature, a VPP stands as a pivotal enabler in our journey towards a sustainable, decentralized, and resilient energy future. There can be an effective and customer-focused energy ecosystem that leads the path for a greener and more sustainable society by fully utilizing VPPs and maximizing their important contributions.

The ability of VPPs to maximize DERs, boost renewable energy integration, and improve grid stability makes them a crucial element in reaching a sustainable energy future. A VPP has the undisputed potential to change the energy landscape. The successful operation of VPPs in the modern era depends on a judicious blend of cutting-edge technology, supportive regulatory frameworks, and seamless connectivity with the existing electricity infrastructure. The aggregation and control of various DERs can be optimized by using real-time data analytics, artificial intelligence, and smart grid technologies. However, VPPs must overcome several obstacles, such as data security, grid interconnection, and scalability to realize their full potential. In a dynamic energy environment, taking care of these issues is essential to ensure the proper operation of VPPs.

Also, the development of flexible regulatory frameworks that support VPP implementation and market involvement is essential for the efficient operation of VPPs. The seamless integration of VPPs into current energy markets and the promotion of novel business models are made possible by clear regulations on market access, price structures, and grid services. Overall, an effective operation of VPPs in this era and beyond will depend on the following:

Advanced technological integration such as data analytics, smart grid technologies which are vital real-time data processing, accurate forecasting, and efficient optimization.

Regulatory support to encourage supportive and accommodative regulatory frameworks that will promote VPP deployment, and market participation.

Implementation of robust data security measures to protect sensitive information, guarantee consumer privacy, and safeguard against potential cyberattacks.

Implementing these recommendations will help shape and harness the potential of VPPs to transform the energy industry. With correct planning, VPPs will significantly contribute to the modern era’s goals of energy resource optimization, grid stability enhancement, and improved integration of RESs.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during this work.

Abbreviations

Artificial Neural Network

Biogas/biomass power

Battery energy storage system

Combined heat and power

Convolutional Neural Network

Controlled load

• Distributed energy resources

Distributed generation

Distribution system operator

Energy storage system

European Union

Electric vehicles

Gas turbine

Heat pump power

Heating, ventilation, and air conditioning

Internet of Things

Long short-term memory

Mixed Integer Linear Programming

Model predictive control

Nuclear power

Pumped hydro storage

Programmable logic control

Power System Network

Particle Swarm Optimization

Photovoltaic

Renewable energy resources

• Renewable energy sources

Sustainable Development Goals

Thermal power

Transmission system operator

United Nations

Virtual power plant

Wind turbine

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Virtual Power Plants: The Future of Renewable Power? https://www.linkedin.com/pulse/virtual-power-plants-future-renewable-ashik-kalam . Accessed 19 Sept 2023

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Authors express their sincere gratitude to Professor Farrag of School of Computing, Engineering and the Built Environment at Glasgow Caledonian University for proofreading and providing valuable insights in enhancing the accuracy, clarity, and readability of this manuscript.

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Sobhy Abdelkader, Jeremiah Amissah & Omar Abdel-Rahim

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Abdelkader, S., Amissah, J. & Abdel-Rahim, O. Virtual power plants: an in-depth analysis of their advancements and importance as crucial players in modern power systems. Energ Sustain Soc 14 , 52 (2024). https://doi.org/10.1186/s13705-024-00483-y

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