斯塔克伯格竞赛
可再生能源
数学优化
计算机科学
热电联产
需求响应
双层优化
电
电力市场
利润(经济学)
纳什均衡
最优化问题
发电
工程类
经济
微观经济学
电气工程
功率(物理)
数学
物理
量子力学
作者
Ghulam Mohy‐ud‐din,Kashem M. Muttaqi,Danny Sutanto
标识
DOI:10.1109/tia.2022.3195965
摘要
This article proposes a cooperative energy transaction model for a virtual power plant (VPP) developed as a bilevel optimization program based on the Stackelberg game in the deregulated electricity markets. The VPP integrates multiple renewable energy hubs consisting of electric vehicle charging stations with photovoltaic and battery energy storage systems. The proposed model derives co-optimized strategic decisions for the VPP operator in the day-ahead (joint active power, reserve, and reactive power) markets while considering the balancing market operation. The proposed model is reformulated as a mathematical program with equilibrium constraints (MPECs) using the Karush–Kuhn–Tucker conditions and the strong duality theorem. For an efficient solution, the MPEC is approximated as a mixed-integer linear program by applying the Fortuny-Amat transform on the complementarity and slackness conditions and the binary expansion on the bilinear terms. The uncertainties of the renewables, loads, and prices are modeled using stochastic scenarios. Finally, comparative case studies of a VPP in an IEEE 33 node active distribution network show that the proposed model improves the profit by strategic cooperative energy transactions.
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