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Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis

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  • Wang, Ge
  • Zhang, Qi
  • Li, Hailong
  • McLellan, Benjamin C.
  • Chen, Siyuan
  • Li, Yan
  • Tian, Yulu

Abstract

Promoting the penetration of distributed photovoltaic systems (PV) at the end-user side is an important and urgent task. This study aims to evaluate the promotion impact of the response capability of smart home consumers on the distributed PV penetration using non-cooperative game theoretical analysis. In the analysis, the Nash equilibrium can be found for consumers with different levels of demand response capability in an electricity market with real-time pricing (RTP) mechanism under different PV installed capacities and battery capacities. As a case study, 5 levels of consumers’ response capability, 32 combinations of PV installed capacities and battery capacities were analyzed and inter-compared using the developed model. The results show that: (i) the consumers with higher response capability are able to accept larger PV capacity because the marginal revenue of new installed PV for smart consumers decreases much more slowly compared to that of a common consumer; (ii) the consumers with higher response capability need less batteries to promote PV economic acceptability; (iii) the consumers with higher response capability can meet the electricity demand in real-time with least expenditure, so they get more ultimate benefit from the games.

Suggested Citation

  • Wang, Ge & Zhang, Qi & Li, Hailong & McLellan, Benjamin C. & Chen, Siyuan & Li, Yan & Tian, Yulu, 2017. "Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis," Applied Energy, Elsevier, vol. 185(P2), pages 1869-1878.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:1869-1878
    DOI: 10.1016/j.apenergy.2016.01.016
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    7. Noor, Sana & Yang, Wentao & Guo, Miao & van Dam, Koen H. & Wang, Xiaonan, 2018. "Energy Demand Side Management within micro-grid networks enhanced by blockchain," Applied Energy, Elsevier, vol. 228(C), pages 1385-1398.
    8. Jeseok Ryu & Jinho Kim, 2020. "Non-Cooperative Indirect Energy Trading with Energy Storage Systems for Mitigation of Demand Response Participation Uncertainty," Energies, MDPI, vol. 13(4), pages 1-14, February.
    9. Jiang, Bo & Muzhikyan, Aramazd & Farid, Amro M. & Youcef-Toumi, Kamal, 2017. "Demand side management in power grid enterprise control: A comparison of industrial & social welfare approaches," Applied Energy, Elsevier, vol. 187(C), pages 833-846.
    10. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    11. Howlader, Abdul Motin & Sadoyama, Staci & Roose, Leon R. & Sepasi, Saeed, 2018. "Distributed voltage regulation using Volt-Var controls of a smart PV inverter in a smart grid: An experimental study," Renewable Energy, Elsevier, vol. 127(C), pages 145-157.
    12. 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.
    13. Shigetomi, Yosuke & Matsumoto, Ken'ichi & Ogawa, Yuki & Shiraki, Hiroto & Yamamoto, Yuki & Ochi, Yuki & Ehara, Tomoki, 2018. "Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan," Applied Energy, Elsevier, vol. 228(C), pages 2321-2332.
    14. Mahmoud Elkazaz & Mark Sumner & Seksak Pholboon & Richard Davies & David Thomas, 2020. "Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation," Energies, MDPI, vol. 13(13), pages 1-23, July.
    15. Motalleb, Mahdi & Ghorbani, Reza, 2017. "Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices," Applied Energy, Elsevier, vol. 202(C), pages 581-596.
    16. Elkazaz, Mahmoud & Sumner, Mark & Naghiyev, Eldar & Pholboon, Seksak & Davies, Richard & Thomas, David, 2020. "A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers," Applied Energy, Elsevier, vol. 269(C).
    17. Yan Li & Ge Wang & Bo Shen & Qi Zhang & Boyu Liu & Ruoxi Xu, 2021. "Conception and policy implications of photovoltaic modules end‐of‐life management in China," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(1), January.

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