Compared with a single virtual power plant

multi-virtual power plants optimization has significant advantages in energy interaction. By connecting multiple virtual power plants

a broader energy network can be formed to achieve more efficient energy allocation and utilization

and improve the flexibility and reliability of energy interaction. Therefore

a chance constrained optimal scheduling model for multi-virtual power plants considering cooperation satisfaction is proposed. Firstly

P2P transactions between virtual power plants are considered

and a cooperative game model for multi-virtual power plants is constructed with the goal of minimizing total operating costs. Then

chance constrained optimal programming method is used to address the impact of photovoltaic output uncertainty on the optimization results of virtual power plants

avoiding the risk of load loss caused by uncertainty in photovoltaic output. Then

a generalized Nash bargaining method based on cooperation satisfaction is proposed to achieve a reasonable allocation of cooperation surplus. Finally

an example is used to verify that this method can provide a multi-virtual power plant cooperative trading strategy that takes into account both economy and reliability

and improves the enthusiasm for cooperation among virtual power plants.