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A stochastic framework to evaluate the impact of agricultural load flexibility on the sizing of renewable energy systems

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  • Kocaman, Ayse Selin
  • Ozyoruk, Emin
  • Taneja, Shantanu
  • Modi, Vijay

Abstract

Pumping of water for agriculture can be a flexible component of electric demand. In this study, a framework that involves scenario based stochastic programming models is developed to examine the effect of load shifting on the renewable energy system sizing for agricultural load. With the help of this framework, alternative load shifting policies are evaluated to observe how the intrinsic flexibility of agricultural load reduces the amount of investments while designing a renewable system. Using real data from India’s Gujarat region, solar and wind cases are evaluated separately to understand the coherency between these sources and the agricultural demand. The value of using a dispatchable source to help with the intermittency of the renewable sources in the systems is discussed. It is also shown that energy storage can be a convenient control mechanism for the integration of renewables; however, is an expensive substitute for demand response programs for agricultural load. Benchmarks for the incentive amounts that can be provided for alternative load shifting policies are presented.

Suggested Citation

  • Kocaman, Ayse Selin & Ozyoruk, Emin & Taneja, Shantanu & Modi, Vijay, 2020. "A stochastic framework to evaluate the impact of agricultural load flexibility on the sizing of renewable energy systems," Renewable Energy, Elsevier, vol. 152(C), pages 1067-1078.
    • Handle: RePEc:eee:renene:v:152:y:2020:i:c:p:1067-1078
    DOI: 10.1016/j.renene.2020.01.129
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    1. Stadler, Michael & Cardoso, Gonçalo & Mashayekh, Salman & Forget, Thibault & DeForest, Nicholas & Agarwal, Ankit & Schönbein, Anna, 2016. "Value streams in microgrids: A literature review," Applied Energy, Elsevier, vol. 162(C), pages 980-989.
    2. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    3. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.
    4. Wang, Jiadong & Wang, Jianhui & Liu, Cong & Ruiz, Juan P., 2013. "Stochastic unit commitment with sub-hourly dispatch constraints," Applied Energy, Elsevier, vol. 105(C), pages 418-422.
    5. Viana, Matheus Sabino & Manassero, Giovanni & Udaeta, Miguel E.M., 2018. "Analysis of demand response and photovoltaic distributed generation as resources for power utility planning," Applied Energy, Elsevier, vol. 217(C), pages 456-466.
    6. Behboodi, Sahand & Chassin, David P. & Crawford, Curran & Djilali, Ned, 2016. "Renewable resources portfolio optimization in the presence of demand response," Applied Energy, Elsevier, vol. 162(C), pages 139-148.
    7. Selin Kocaman, Ayse & Abad, Carlos & Troy, Tara J. & Tim Huh, Woonghee & Modi, Vijay, 2016. "A stochastic model for a macroscale hybrid renewable energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 688-703.
    8. Yuan, Shengxi & Kocaman, Ayse Selin & Modi, Vijay, 2017. "Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente," Renewable Energy, Elsevier, vol. 105(C), pages 167-174.
    9. Nyholm, Emil & Odenberger, Mikael & Johnsson, Filip, 2017. "An economic assessment of distributed solar PV generation in Sweden from a consumer perspective – The impact of demand response," Renewable Energy, Elsevier, vol. 108(C), pages 169-178.
    10. Ludwig Kuznia & Bo Zeng & Grisselle Centeno & Zhixin Miao, 2013. "Stochastic optimization for power system configuration with renewable energy in remote areas," Annals of Operations Research, Springer, vol. 210(1), pages 411-432, November.
    11. Wang, Xiaonan & Palazoglu, Ahmet & El-Farra, Nael H., 2015. "Operational optimization and demand response of hybrid renewable energy systems," Applied Energy, Elsevier, vol. 143(C), pages 324-335.
    12. Moura, Pedro S. & de Almeida, Aníbal T., 2010. "Multi-objective optimization of a mixed renewable system with demand-side management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1461-1468, June.
    13. Katzenstein, Warren & Fertig, Emily & Apt, Jay, 2010. "The variability of interconnected wind plants," Energy Policy, Elsevier, vol. 38(8), pages 4400-4410, August.
    14. Erdinc, Ozan & Paterakis, Nikolaos G. & Pappi, Iliana N. & Bakirtzis, Anastasios G. & Catalão, João P.S., 2015. "A new perspective for sizing of distributed generation and energy storage for smart households under demand response," Applied Energy, Elsevier, vol. 143(C), pages 26-37.
    15. Anna, Petrenko, 2016. "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(1), March.
    16. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty," Applied Energy, Elsevier, vol. 182(C), pages 500-506.
    17. Falsafi, Hananeh & Zakariazadeh, Alireza & Jadid, Shahram, 2014. "The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming," Energy, Elsevier, vol. 64(C), pages 853-867.
    18. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    19. Kocaman, Ayse Selin & Modi, Vijay, 2017. "Value of pumped hydro storage in a hybrid energy generation and allocation system," Applied Energy, Elsevier, vol. 205(C), pages 1202-1215.
    20. Ghasemi, Ahmad & Enayatzare, Mehdi, 2018. "Optimal energy management of a renewable-based isolated microgrid with pumped-storage unit and demand response," Renewable Energy, Elsevier, vol. 123(C), pages 460-474.
    21. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    22. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    23. Peker, Meltem & Kocaman, Ayse Selin & Kara, Bahar Y., 2018. "Benefits of transmission switching and energy storage in power systems with high renewable energy penetration," Applied Energy, Elsevier, vol. 228(C), pages 1182-1197.
    24. Stodola, Nathan & Modi, Vijay, 2009. "Penetration of solar power without storage," Energy Policy, Elsevier, vol. 37(11), pages 4730-4736, November.
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