Online Optimal Operation of Microgrid Using Approximate Dynamic Programming Under Uncertain Environment

This paper focuses on economical operation of a grid-connected microgrid in real-time. An online optimization model is developed to achieve the microgrid operation in the process of dynamic optimal control, and through information feedback and online optimization to reduce the impact of uncertainty in a MG. The online optimization model has the characteristics of nonlinear and discontinuous, so an approximate dynamic programming (ADP) algorithm is used to solve this online model. Finally, the proposed online optimization model is tested in the European benchmark microgrid system. The simulation results show that the online optimization model overcomes the impacts of random fluctuations of renewable energy and loads and reduces the operating cost of the microgrid.

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