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Residential demand response considering distributed PV consumption: A model based on China's PV policy

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  • Lu, Qing
  • Yu, Hao
  • Zhao, Kangli
  • Leng, Yajun
  • Hou, Jianchao
  • Xie, Pinjie

Abstract

Household distributed photovoltaic (PV) can supply clean power directly to the end users. With the rapid growth of the distributed PV installed capacity, the problems of PV grid connection and PV consumption are becoming more and more serious in China. It is an effective means to improve the efficiency of PV system by promoting the home self-consumption of PV generation. In this study, a residential demand response model considering distributed PV consumption based on dynamic electricity price is proposed. The household users are classified into several types with different power consumption preferences in this model. Both the comfort and economy of power consumption are quantified to describe the users' satisfaction. The model is established with two goals, maximizing the users' satisfaction meanwhile minimizing PV power into the grid. Then a solution algorithm based on NSGA-II is proposed to solve the model. Finally, an example study based on China's PV policy is presented, and the results show that the model has certain advantages in improving the users' satisfaction and increasing the rate of self-consumption of PV generation. In addition, sensitivity analysis of the provincial government's PV subsidies in China is also carried out and the relevant policy recommendations are presented.

Suggested Citation

  • Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
  • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:443-456
    DOI: 10.1016/j.energy.2019.01.097
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    3. Shali Wang & Jiaxi Wu & Yunan Peng & Jane Xu & Lisa Leinonen & Yuyu Wang & Zheng Meng, 2022. "Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China," Sustainability, MDPI, vol. 14(14), pages 1-30, July.
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    7. Cristea, Ciprian & Cristea, Maria & Birou, Iulian & Tîrnovan, Radu-Adrian, 2020. "Economic assessment of grid-connected residential solar photovoltaic systems introduced under Romania’s new regulation," Renewable Energy, Elsevier, vol. 162(C), pages 13-29.
    8. Chen, Han & Chen, Wenying, 2021. "Status, trend, economic and environmental impacts of household solar photovoltaic development in China: Modelling from subnational perspective," Applied Energy, Elsevier, vol. 303(C).
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    10. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
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    12. Delong Zhang & Yiyi Ma & Jinxin Liu & Siyu Jiang & Yongcong Chen & Longze Wang & Yan Zhang & Meicheng Li, 2022. "Stochastic Optimization Method for Energy Storage System Configuration Considering Self-Regulation of the State of Charge," Sustainability, MDPI, vol. 14(1), pages 1-19, January.
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