消费者
计算机科学
斯塔克伯格竞赛
需求响应
可再生能源
点对点
网格
智能电网
数学优化
分布式发电
博弈论
分布式计算
环境经济学
微观经济学
电
经济
工程类
数学
几何学
电气工程
作者
Yuanxing Xia,Qingshan Xu,Pengwei Du
标识
DOI:10.1016/j.jclepro.2023.139053
摘要
With the development of distributed renewable energy resources (RERs) in smart cities, the peer-to-peer (P2P) transactive energy market has become an effective way for RER owners to consume the surplus produced power. Nevertheless, the influence of grid usage costs in P2P energy trading has not been considered in prosumers’ strategic behaviors. To solve this issue, we analyze the network usage of P2P energy transactions and model a Nash–Stackelberg game to simulate the trading process of market participants. Firstly, we assume the prosumers can join the P2P energy market and determine their roles freely. The market manager adjusts the grid usage prices to influence the prosumers’ exchanged energy amounts. We then establish a monolithic VCG mechanism to inhibit the prosumers’ strategic behaviors while reducing the computational difficulty of the VCG mechanism. Finally, we develop a best-response (BR)-based algorithm to solve one energy prosumer’s cost minimization subproblem at a time to seek market equilibrium. Since the energy prosumers and market manager interact on the trading amount, the prosumers’ responses are modeled as bi-level mixed-integer nonlinear programming (BLMINLP). We employ the generalized Benders decomposition method to reduce the solution difficulty. Case studies verify the theoretical properties and show the practicability of the proposed algorithms.
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