Trading mechanism and pricing strategy of integrated energy systems based on credit rating and Bayesian game

Abstract

In the integrated energy market, monitoring and managing the irregularities of market members is the key to ensuring efficient and stable of the market. This paper focuses on a multi-energy market in which the energy hub (EH) as a retailer purchases electricity from the main network and sells electricity and heat to energy users. We use a credit rating model based on Fisher discriminant analysis to evaluate the credit of the EH and set up three levels of punishment to punish the irregularities in trading. Furthermore, we establish a Bayesian game to model and analyze price strategy for EH. The cross-price elasticity of demand is a private information and serve as the type of EH. Each EH estimates the others’ prices and chooses the optimal price strategy that maximizes the expected benefits. Finally, real data are adopted to evaluate the proposed model.