Abstract
This paper presents a robust optimal control strategy for an energy storage system (ESS) of a grid-connected microgrid. The robust optimal control guarantees the highest possible economic benefit of the control schedule even under the worst case net demand prediction error conditions. Several robust optimization approaches are proposed to formulate a fast optimal control problem. The global optimum of a concise control problem can be found within a short computation time using mixed-integer linear programming. The rolling horizon controller of the energy management system periodically updates the control schedule by solving the control problem. The state of charge of an ESS is precisely calculated by the piecewise linearization technique using nonlinear efficiency maps. External working conditions such as peak control and demand response can be dynamically applied during the optimization process. The proposed strategy provides control robustness in terms of cost reduction, precise control, and external effect. Future study will focus on the development of a robust control strategy that considers both the worst and best cases of cost reduction.
Published Version
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