Journal of System Simulation ›› 2025, Vol. 37 ›› Issue (5): 1129-1141.doi: 10.16182/j.issn1004731x.joss.24-0349

• Simulation Technology for New Energy and Transportation Systems under the Dual Carbon Goals • Previous Articles     Next Articles

Optimal Scheduling of Virtual Power Plant with Coupled Operation of CCS-P2G Considering Wind and Photovoltaic Uncertainty

Jin Xurong1, Yin Jiang2, Yang Guohua2, Li Wei1, Wang Guobin1, Wang Lele1, Yang Na2, Zhou Xuenian2   

  1. 1.Marketing Service Center of State Grid Ningxia Electric Power Co. , Ltd. , Yinchuan 750001, China
    2.School of Electrical and Electronic Engineering, Ningxia University, Yinchuan 750021, China
  • Received:2024-04-07 Revised:2024-06-06 Online:2025-05-20 Published:2025-05-23
  • Contact: Yang Guohua

Abstract:

In order to solve the problem that the uncertainty of wind power and photovoltaic power generation output easily affects the scheduling of virtual power plant, a new optimal scheduling model of virtual power plant is proposed based on information gap decision theory (IGDT) . In order to reduce the carbon emission of the system, carbon capture and storage (CCS) is installed on the combined heat and power units; in order to improve the utilization rate of renewable energy, the power to gas (P2G) device is introduced into the system, and the operation mode of CCS-P2G coupling is proposed; based on the operation of CCS-P2G coupling, the uncertainty of wind power and photovoltaic power generation output is considered based on the information gap decision theory. The model is solved by CPLEX solver, and the results show that under the coupled operation of CCS-P2G, the utilization rate of solar and wind power reaches 100%, the operating cost of the system is reduced by 12.3%, and the economy and low carbon of the system are effectively improved; under the IGDT strategy, when the uncertainty of wind power and photovoltaic power generation output does not exceed the upper limit through cost reservation, the virtual power plant operation can be effectively controlled within the scheduling cycle.

Key words: virtual power plant, uncertainty, information gap decision theory, carbon capture and storage, power to gas

CLC Number: