Cost Minimization Online Energy Management for Microgrids with Power and Thermal Storages

In this paper, we consider a typical microgrid scenario that consists of centralized power grid, renewable energy generation, and combined heat and power (CHP) local (co-)generation, as well as power and heat energy storage devices. We aim to minimize the microgrid's operating cost by formulating it as a stochastic non-convex optimization programming, which is challenging to solve optimally. We design an online algorithm by developing a modified Lyapunov optimization approach based on the random system inputs (e.g., the acquired electricity from power grid, the charging/discharging of the energy storage devices, obtained power from the local generator, and the renewable energy generation etc.), which does not require any statistic information of the system. Considering that the nonconvexity of the problem is caused by the dependence of power in battery pack and heat energy in thermal tank, we further explore the relation between them and convert the problem into a convex stochastic optimization programming. We show that the proposed algorithm is efficient with very low computational complexity and is proved to achieve near optimal performance. Moreover, extensive empirical evaluations using real-world traces are provided to study the effectiveness of the proposed algorithm.