Distributed Energy Trading for Multiple Microgrids Considering Wind Power Uncertainty

This paper proposes a stochastic programming based distributed method to solve optimal trading strategies among multiple microgrids (MGs) under uncertainty from wind power generations. Firstly, scenario generation and reduction technologies are adopted to predict and select the most representative scenarios of wind power automatically. Then, uncertainty from wind generations is integrated into the operating model of individual MGs and addressed by the stochastic programming method. Furthermore, in order to ensure the independence and privacy of energy trading processes, a distributed solution method is developed based on an alternating direction multiplier method. Finally, numerical tests with three MGs are implemented to show the effectiveness of the proposed distributed trading method.