Optimal Pricing of Multi Virtual Power Plants Based on Stackelberg Game and Genetic Algorithm

With the rapid development of distributed energy, virtual power plants (VPPs) need to integrate distributed energy and electricity market transactions. There is a game competition relationship between different virtual power plants.In order to maximize the profit of the control center and minimize the operation cost of the virtual power plant, this paper establishes a master-slave game model of multiple virtual power plants and control centers, and uses genetic algorithm (GA) to find the equilibrium solution. In the process of iteratively searching for the optimal solution, the objective function of the control center in each round of game is used as the fitness value of the genetic algorithm, and then carries out the selection, crossover and mutation of individuals in the feasible solution population. Finally, the optimal transaction price can be obtained quickly. The results obtained by the example demonstrate that the proposed model reduces the operating cost of the virtual power plant and inproves the revenue of the control center, which verifies the effectiveness of the method and achieves a win-win situation for both the virtual power plant and the control center.