Abstract
This paper proposes an adaptive real-time energy scheduling method (RT-EMS) for a microgrid, using a Lyapunov optimization-based real-time approach. Inaccuracy in day-ahead predictions can result in non-optimal solutions to the energy scheduling problem. Although the real-time optimization method eliminates the need to deal with the prediction uncertainties, it ignores the valuable statistical information used in day-ahead stochastic approaches and provides suboptimal solutions to the problem. The proposed adaptive approach combines the advantages of both the stochastic day-ahead and the RT-EMS and reduces the real-time operational cost of the microgrid. The proposed method moves the RT-EMS solution towards the optimal solution, by adding a penalty term to the objective function. Numerical results are provided to demonstrate the improved performance of the proposed adaptive method.
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