Model Predictive Control of Microgrid Energy Management System with Optimal Power Flow Constraints Using Second Order Cone Programming

Energy management system (EMS) is important for the planning and operation of power system as the power generation must supply enough energy for load with the minimum operating cost. This paper presents nonlinear MPC to dispatch power generation within the limitation of the power system. The objectives are to improve EMS by considering AC optimal power flow and provide a dispatch strategy to reduce total operating cost (TOC). To realize the proposed nonlinear MPC, we consider the power plant model of Mae Hong Son in the northern part of Thailand. Load data and power generation profile are utilized as the inputs to MPC of EMS to minimize TOC for one day ahead. In this work, the optimal power flow is incorporated as the second order cone constraints. It is shown that EMS with optimal power flow can operate within the rated voltage for all buses. When comparing the results in normal mode with one-shot optimization, the proposed MPC can reduce the TOC by 1.72% in the rainy season.