Green-fitting scheduling equilibrium model of virtual power plant based on cooperative game with improved shapley value under new-type power system
Shuo Zhang, Luming Pang, Yingzi Li, Yuanli Chen, Kai Li, Meixia Zheng
Abstract
• Build an operation framework of VPP includes various DERs, energy storages, etc. • Propose a dual-objective scheduling model for VPP considering green-fitting degree. • Employ the improved Shapley value method to distribute profits for VPP members. The new-type power system serves as a basic support for achieving the dual carbon goals of China. Simultaneously, the virtual power plant (VPP) emerges as a significant mode for aggregating decentralized resources on the demand side, which has a guaranteed role in the safe and green operation of the new-type power system. This paper firstly analyzes the green operation framework of VPP, which includes photovoltaic, distributed wind power, gas turbine, energy storage and load. Furthermore, considering the economic characteristics and green consumption characteristics of VPP, a dual-objective optimization scheduling model is constructed, aiming to maximize the VPP’s revenue and achieve the highest green-fitting degree between the VPP’s external power purchase curve and the green energy output curve in the power grid. To solve the model effectively, the improved particle swarm optimization algorithm has been employed. Then, the improved Shapley value method is applied to realize the fair and reasonable distribution of VPP internal income. Finally, the validity of the model is verified by comparative scenarios and sensitivity analysis on the fluctuations of wind and photovoltaic power and Time-of-Use electricity price is conducted. The results show that considering both profits and green-fitting degree objectives can enhance the activity of VPP’s internal members and the overall revenue of the VPP.