A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural Areas

Abstract

Microgrids consisting of diesel generators, storage devices, and renewable sources present an effective approach for an economic energy supply to rural areas. Advanced control methods are needed to improve the energy dispatch, enable a cost-efficient operation and guarantee an uninterrupted power supply. In particular, sudden variations in load demand or additional power supply from renewable sources are often unpredictable and underline the need for enhanced control. This paper presents an advanced control strategy for the optimal microgrid operation using a two-layer model predictive method. The first optimization layer presents an optimal control problem, based on real-time predictions of future power profiles, for the calculation of the optimal energy dispatch. To improve the robustness of the control strategy toward prediction errors, a boundary value problem is solved to adjust the diesel generator power in the second stage. The model predictive control framework is further used to adapt the weights of the forecast algorithm. Simulation studies are carried out by using real-world data to illustrate the performance and economic benefits of the proposed method. Results show the effectiveness of the control strategy in terms of computational feasibility, accuracy, increased robustness, and reduced cost.