Stochastic Optimal Control for Energy Internet: A Bottom-Up Energy Management Approach

In this paper, an energy management issue is considered for energy Internet where microgrids (MGs) are interconnected via energy routers (ERs). Focusing on an individual MG, we propose controllers in microturbines (MTs) and the ER, such that the following three criteria are hold simultaneously. First, a bottom-up energy management approach is realized. Second, the operation cost of utilizing battery energy storage devices is minimized. Third, the situation of overcontrol with respect to MTs is considered to be avoided. Besides, we develop a novel hybrid modeling method combining both recurrent neural networks and Ornstein-Uhlenbeck process to obtain accurate power models for both photovoltaic panels and loads. Next, we formulate our energy management issue into a stochastic optimal control problem and solve it via dynamic programming approach. Finally, examples illustrating the feasibility of the proposed methods are provided.