A multi-energy pricing strategy for port integrated energy system based on Bayesian Stackelberg game

This paper proposes a method for multi-energy pricing strategy by constructing Bayesian Stackelberg model, in order to increase the social welfare and extend the optimal results to the case where private information about energy users (EUs) is unknown. Specifically, in Bayesian Stackelberg game model, the port acts as a leader and EUs are competitive followers. Furthermore, the decision processes of port and EUs are coupled together by the probability of consuming electricity and heat. In addition, a price regulation mechanism is designed, which is composed of fictitious play (FP) algorithm and gradient descent algorithm. Consequently, the balance of energy supply and demand can be obtained by loop iteration of these two algorithms. Numerical results have demonstrated that the multi-energy pricing strategy can achieve the balance between supply and demand and improve the social welfare.