Optimized Operation of Electricity Sales Companies Considering the Insurance Mechanism and User Demand Response

Qianhui WEN; Zhenbo WEI; Yonglin ZHANG; Zheng LIANG; Yongxiang HE

doi:10.12204/j.issn.1000-7229.2023.01.006

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Electric Power Construction ›› 2023, Vol. 44 ›› Issue (1) : 47-54. DOI: 10.12204/j.issn.1000-7229.2023.01.006

Energy Power Economy and Market Mechanism Driven by Dual Carbon Targets?Hosted by Professor WEN Fushuan and Professor LIU Dunnan?

Optimized Operation of Electricity Sales Companies Considering the Insurance Mechanism and User Demand Response

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Abstract

The uncertainty of the electricity purchase and sale sides is the key factor restricting the operation of the electricity sales company. This paper uses the third-party insurance mechanism to avoid market fluctuations and demand response to improve returns, and puts forward an optimized operation model for electricity sales companies under the spot market. Firstly, the deviation assessment model and premium model are established, the deviation assessment model of the user limit penalty mechanism and demand response contract on the user utility in the bilateral long association contract are quantified, and the optimal operation model is verified with the data of local users. The example results show that the electricity sales company can guide the users to respond positively through the stepped demand response incentive mechanism; the introduced insurance mechanism can effectively disperse and transfer the risk of electricity fluctuation, and realize the win-win value between the electricity sales company and the users.

This work is supported by National Natural Science Foundation of China(No. 52077146).

Key words

demand response / user utility / market insurance / electricity sales company / deviation assessment

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Qianhui WEN , Zhenbo WEI , Yonglin ZHANG , et al . Optimized Operation of Electricity Sales Companies Considering the Insurance Mechanism and User Demand Response[J]. Electric Power Construction. 2023, 44(1): 47-54 https://doi.org/10.12204/j.issn.1000-7229.2023.01.006

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With the liberalization of the power sales market， a large amount of social capital has entered the market， and the number of power sales companies has increased dramatically. In the fierce market competition， how to ensure the self-revenue and improve the users power consumption satisfaction is an urgent problem for sales companies. For this reason， a power pricing strategy based on different power consumption of power users is constructed. Firstly， according to the load curve， the similarity and difference of different users behavior are analyzed and then the user is subdivided. A customized time-sharing electricity price model is established to obtain the optimal pricing strategy for the sales company and its users to maximize revenue. Finally， the model is solved by the genetic algorithm and the cross-section algorithm applying to the actual load data of the power users， and the effectiveness of the proposed electricity price decision model is proved.

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