A Fast-Converging Virtual Power Plant Game Trading Model Based on Reference Ancillary Service Pricing

In order to improve the trading efficiency of virtual power plants (VPPs) participating in the market of multi-type auxiliary services under the gaming environment, an initial trading price setting method based on the information of VPPs’ response characteristics and real-time supply and demand changes is proposed to accelerate the convergence speed of the game. Firstly, a master–slave game trading model is established based on the reference auxiliary service pricing, which consists of a tariff coefficient and a basic tariff. Secondly, the tariff coefficient model is constructed based on response information, including response rate, quality, and reliability. Again, the basic tariff model is constructed based on the real-time supply and demand situation and the real-time grid tariff. Finally, the effectiveness of the proposed method in accelerating the convergence speed of the game is verified by analyzing 12 VPPs under the three auxiliary service scenarios of peaking, frequency regulation, and reserve.