Credit rating based real-time energy trading in microgrids

In this paper, we investigate the problem of credit rating management in energy trading among microgrids subject to transmission losses and wheeling cost. The main concern is how to constrain the default behaviors of retailers to enable all the consumers and retailers to be actively involved in the energy trading. By endowing retailers as leaders and consumers as followers, we establish a multi-leader multi-follower dynamic game model and propose a scorecard model based on logistic regression to evaluate retailers’ credit ratings. The concept of trust degree is then introduced for all the retailers as a punitive measure to relate their credit ratings with the reduction in the profit. With such a strategy, we can theoretically show that a unique equilibrium exists for the dynamic game model. Moreover, a best response algorithm is proposed to make the consumers and retailers achieve the equilibrium iteratively. Numerical simulations are provided to demonstrate the effectiveness and efficiency of the proposed method. It is found that default behaviors of selfish retailers can be greatly constrained with only a slight degradation of the interests of other participants, thereby promoting the establishment of a trustworthy trading market. We also discuss the influence level of transmission losses on trading behaviors of retailers and consumers.