Energy Pricing and Sharing Strategy Based on Hybrid Stochastic Robust Game Approach for a Virtual Energy Station With Energy Cells
Shuangrui Yin, Qian Ai, Jiamei Li, Zhaoyu Li, Songli Fan
Abstract
In this paper, a novel energy pricing and sharing strategy is proposed to solve the energy management and market bidding problems of a virtual energy station (VES) in multi-carrier energy systems. First, the energy cell-tissue-based group interaction framework and the multiagent-based communication and control architecture are established in the VES. Second, the general model of an energy cell is built, in which the integrated demand response process and the automatic generation control mode of a combined heat and power unit are designed. Third, according to the classification of energy cells, the aggregation rules of the VES without the participation of third-party agents are proposed, and the internal trading mechanism of the VES led by a higher energy cell is designed based on a Stackelberg game. Moreover, a three-stage hybrid stochastic robust optimization strategy is proposed to address uncertainties in market prices and renewable energy output. Finally, the optimization model is linearized and solved by duality theory, KKT conditions, and column-and-constraint generation (C&CG) algorithm. Simulation results prove the rationality and effectiveness of the framework and business model for the VES.