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Demand response management of community integrated energy system: A multi-energy retail package perspective

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  • Gao, Hongjun
  • Zhao, Yinbo
  • He, Shuaijia
  • Liu, Junyong

Abstract

The community integrated energy system (CIES) is becoming an effective way to improve the energy utilization efficiency and reduce the carbon emission. Demand response in a CIES may be more challenge with the participation of multi-energy consumers. In this paper, we propose a novel multi-energy retail package mechanism, which provides a new perspective for demand response management in CIES. Firstly, we describe the operation rules of the energy retail package mechanism proposed in this paper, aiming at promoting the electricity and gas loads peak shaving and the electricity load valley filling in electricity-gas CIES. Secondly, a bi-level optimization model is built to optimize a set of packages with different response requirements and discounts for different consumers. The lower model adopts Multinomial Logit theory to simulate the consumer's package selecting and energy use behavior when facing different energy retail packages while the upper model optimizes package parameters with the objective of maximizing CIES operator increased benefit. Finally, the effectiveness of the energy retail package mechanism designed in this paper for demand response management is verified through example analysis.

Suggested Citation

  • Gao, Hongjun & Zhao, Yinbo & He, Shuaijia & Liu, Junyong, 2023. "Demand response management of community integrated energy system: A multi-energy retail package perspective," Applied Energy, Elsevier, vol. 330(PA).
  • Handle: RePEc:eee:appene:v:330:y:2023:i:pa:s0306261922015355
    DOI: 10.1016/j.apenergy.2022.120278
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    as
    1. Ansarin, Mohammad & Ghiassi-Farrokhfal, Yashar & Ketter, Wolfgang & Collins, John, 2020. "The economic consequences of electricity tariff design in a renewable energy era," Applied Energy, Elsevier, vol. 275(C).
    2. Cui, Qiong & Ma, Peipei & Huang, Lei & Shu, Jie & Luv, Jie & Lu, Lin, 2020. "Effect of device models on the multiobjective optimal operation of CCHP microgrids considering shiftable loads," Applied Energy, Elsevier, vol. 275(C).
    3. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    4. Günther, Claudia & Schill, Wolf-Peter & Zerrahn, Alexander, 2021. "Prosumage of solar electricity: Tariff design, capacity investments, and power sector effects," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 152.
    5. François Bourguignon & Martin Fournier & Marc Gurgand, 2007. "Selection Bias Corrections Based On The Multinomial Logit Model: Monte Carlo Comparisons," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 174-205, February.
    6. Chen, Xi & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming & Yang, Ming & He, Suoying & Liang, Jun, 2020. "Optimal operation of integrated energy system considering dynamic heat-gas characteristics and uncertain wind power," Energy, Elsevier, vol. 198(C).
    7. Chen, Yongbao & Xu, Peng & Chu, Yiyi & Li, Weilin & Wu, Yuntao & Ni, Lizhou & Bao, Yi & Wang, Kun, 2017. "Short-term electrical load forecasting using the Support Vector Regression (SVR) model to calculate the demand response baseline for office buildings," Applied Energy, Elsevier, vol. 195(C), pages 659-670.
    8. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    9. Alexandre Lucas & Luca Jansen & Nikoleta Andreadou & Evangelos Kotsakis & Marcelo Masera, 2019. "Load Flexibility Forecast for DR Using Non-Intrusive Load Monitoring in the Residential Sector," Energies, MDPI, vol. 12(14), pages 1-19, July.
    10. Li, Lanlan & Gong, Chengzhu & Tian, Shizhong & Jiao, Jianling, 2016. "The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers: Evidence from multi-agent simulation," Energy, Elsevier, vol. 96(C), pages 48-58.
    11. Mendes, Gonçalo & Ioakimidis, Christos & Ferrão, Paulo, 2011. "On the planning and analysis of Integrated Community Energy Systems: A review and survey of available tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4836-4854.
    12. Zhou, Zhe & Moura, Scott J. & Zhang, Hongcai & Zhang, Xuan & Guo, Qinglai & Sun, Hongbin, 2021. "Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective," Applied Energy, Elsevier, vol. 289(C).
    13. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
    14. Zheng, Shunlin & Sun, Yi & Li, Bin & Qi, Bing & Zhang, Xudong & Li, Fei, 2021. "Incentive-based integrated demand response for multiple energy carriers under complex uncertainties and double coupling effects," Applied Energy, Elsevier, vol. 283(C).
    15. Koirala, Binod Prasad & Koliou, Elta & Friege, Jonas & Hakvoort, Rudi A. & Herder, Paulien M., 2016. "Energetic communities for community energy: A review of key issues and trends shaping integrated community energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 722-744.
    16. Sioshansi, Ramteen, 2016. "Retail electricity tariff and mechanism design to incentivize distributed renewable generation," Energy Policy, Elsevier, vol. 95(C), pages 498-508.
    17. Lin, Wei & Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Xu, Xiandong & Yu, Xiaodan & Zhao, Bo, 2018. "A two-stage multi-objective scheduling method for integrated community energy system," Applied Energy, Elsevier, vol. 216(C), pages 428-441.
    18. Wenshi Wang & Houqi Dong & Yangfan Luo & Changhao Zhang & Bo Zeng & Fuqiang Xu & Ming Zeng, 2021. "An Interval Optimization-Based Approach for Electric–Heat–Gas Coupled Energy System Planning Considering the Correlation between Uncertainties," Energies, MDPI, vol. 14(9), pages 1-24, April.
    19. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    20. Wu, Wanlu & Cheng, Yuanyuan & Lin, Xiqiao & Yao, Xin, 2019. "How does the implementation of the Policy of Electricity Substitution influence green economic growth in China?," Energy Policy, Elsevier, vol. 131(C), pages 251-261.
    21. Sezgen, Osman & Goldman, C.A. & Krishnarao, P., 2007. "Option value of electricity demand response," Energy, Elsevier, vol. 32(2), pages 108-119.
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