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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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    1. Steven A. Gabriel & Antonio J. Conejo & J. David Fuller & Benjamin F. Hobbs & Carlos Ruiz, 2013. "Complementarity Modeling in Energy Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4419-6123-5, December.
    2. Steven A. Gabriel & Antonio J. Conejo & J. David Fuller & Benjamin F. Hobbs & Carlos Ruiz, 2013. "Optimality and Complementarity," International Series in Operations Research & Management Science, in: Complementarity Modeling in Energy Markets, edition 127, chapter 0, pages 31-69, Springer.
    3. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    4. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    5. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    6. Su, Wencong & Huang, Alex Q., 2014. "A game theoretic framework for a next-generation retail electricity market with high penetration of distributed residential electricity suppliers," Applied Energy, Elsevier, vol. 119(C), pages 341-350.
    7. Bhatt, Jignesh & Shah, Vipul & Jani, Omkar, 2014. "An instrumentation engineer’s review on smart grid: Critical applications and parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1217-1239.
    8. Kriett, Phillip Oliver & Salani, Matteo, 2012. "Optimal control of a residential microgrid," Energy, Elsevier, vol. 42(1), pages 321-330.
    9. Tung, Ching-Pin & Tseng, Tze-Chi & Huang, An-Lei & Liu, Tzu-Ming & Hu, Ming-Che, 2013. "Impact of climate change on Taiwanese power market determined using linear complementarity model," Applied Energy, Elsevier, vol. 102(C), pages 432-439.
    10. Tanaka, Kenichi & Yoza, Akihiro & Ogimi, Kazuki & Yona, Atsushi & Senjyu, Tomonobu & Funabashi, Toshihisa & Kim, Chul-Hwan, 2012. "Optimal operation of DC smart house system by controllable loads based on smart grid topology," Renewable Energy, Elsevier, vol. 39(1), pages 132-139.
    11. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    12. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    13. Valenzuela, Jorge & Thimmapuram, Prakash R. & Kim, Jinho, 2012. "Modeling and simulation of consumer response to dynamic pricing with enabled technologies," Applied Energy, Elsevier, vol. 96(C), pages 122-132.
    14. Zhang, Qi & Mclellan, Benjamin C. & Tezuka, Tetsuo & Ishihara, Keiichi N., 2013. "An integrated model for long-term power generation planning toward future smart electricity systems," Applied Energy, Elsevier, vol. 112(C), pages 1424-1437.
    15. Kopsakangas Savolainen, Maria & Svento, Rauli, 2012. "Real-Time Pricing in the Nordic Power markets," Energy Economics, Elsevier, vol. 34(4), pages 1131-1142.
    16. Martin, Nigel & Rice, John, 2013. "The solar photovoltaic feed-in tariff scheme in New South Wales, Australia," Energy Policy, Elsevier, vol. 61(C), pages 697-706.
    17. White, Lee V. & Lloyd, Bob & Wakes, Sarah J., 2013. "Are Feed-in Tariffs suitable for promoting solar PV in New Zealand cities?," Energy Policy, Elsevier, vol. 60(C), pages 167-178.
    18. Yan, Ruifeng & Saha, Tapan Kumar & Modi, Nilesh & Masood, Nahid-Al & Mosadeghy, Mehdi, 2015. "The combined effects of high penetration of wind and PV on power system frequency response," Applied Energy, Elsevier, vol. 145(C), pages 320-330.
    19. de La Tour, Arnaud & Glachant, Matthieu & Ménière, Yann, 2013. "Predicting the costs of photovoltaic solar modules in 2020 using experience curve models," Energy, Elsevier, vol. 62(C), pages 341-348.
    20. Hsu, Chiung-Wen, 2012. "Using a system dynamics model to assess the effects of capital subsidies and feed-in tariffs on solar PV installations," Applied Energy, Elsevier, vol. 100(C), pages 205-217.
    21. Yoza, Akihiro & Yona, Atsushi & Senjyu, Tomonobu & Funabashi, Toshihisa, 2014. "Optimal capacity and expansion planning methodology of PV and battery in smart house," Renewable Energy, Elsevier, vol. 69(C), pages 25-33.
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    Cited by:

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    5. Fan, Songli & Ai, Qian & Piao, Longjian, 2018. "Bargaining-based cooperative energy trading for distribution company and demand response," Applied Energy, Elsevier, vol. 226(C), pages 469-482.
    6. Juha Koskela & Pertti Järventausta, 2023. "Demand Response with Electrical Heating in Detached Houses in Finland and Comparison with BESS for Increasing PV Self-Consumption," Energies, MDPI, vol. 16(1), pages 1-25, January.
    7. Yosuke Shigetomi & Asuka Ishigami & Yin Long & Andrew Chapman, 2024. "Curbing household food waste and associated climate change impacts in an ageing society," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    8. 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.
    9. 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.
    10. 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.
    11. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. Nurcan Yarar & Yeliz Yoldas & Serkan Bahceci & Ahmet Onen & Jaesung Jung, 2024. "A Comprehensive Review Based on the Game Theory with Energy Management and Trading," Energies, MDPI, vol. 17(15), pages 1-29, July.
    19. 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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