Retail competition among multi-type retail electric providers in social networks

被引:1
|
作者
Li, He [1 ]
Fang, Debin [1 ,2 ]
Zhao, Chaoyang [3 ]
机构
[1] Wuhan Univ, Res Ctr Complex Sci & Management, Wuhan 430072, Peoples R China
[2] Wuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China
[3] Gen Off CPC Guizhou Prov Comm, State Secrets Bur, Guizhou 550005, Peoples R China
基金
中国国家自然科学基金;
关键词
Electricity retail market; Social learning; Network externalities; Electricity service quality; DEMAND;
D O I
10.1016/j.eneco.2024.107411
中图分类号
F [经济];
学科分类号
02 ;
摘要
Liberalization of the electricity retail market has intensified the competition among different types of retail electricity providers (REPs), leading REPs to pay more attention to electricity consumers' (ECs') preferences for electricity service quality, such as reliability and flexibility. In addition, social learning also greatly influences consumers' electricity purchase strategies. Therefore, this paper models the price and service quality competition among multi-type REPs in a two-layer electricity retail market network that integrates electricity trading and consumer social learning. Firstly, we construct a two-layer network that transforms the dynamic process of ECs switching REPs and changing neighbors into the reconfiguration of the network structure. The upper layer is a bipartite network to express the dynamic transaction between REPs and ECs, while the lower layer is a random network to represent the learning interaction between ECs. Secondly, considering network externalities, we model a retail competition based on price and ECs' preferences for electricity service quality in the network above and get the equilibrium solutions in different scenarios by simulating the electricity consumption data of 600 London households. The results demonstrate that network externalities hinder the transmission of price signals, and the density of the EC network affects the market game result, while the update speed of the EC network has little effect. This study provides theoretical support for multi-agent decision-making in the electricity retail market.
引用
收藏
页数:19
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