A Three-Stage Optimal Energy Management Strategy for Cophase Power Supply Systems With Integration of Renewable Energy

Abstract

To overcome the load uncertainty of cophase power supply systems, including photovoltaic (PV), hybrid energy storage systems (HESSs), and distribution networks in electrified railways, this article proposed a three-stage optimal energy management strategy. Day-ahead optimization aims to minimize the daily cost of the system. Intraday optimization is implemented based on short-time prediction. Its objective is a hybrid of economic-based optimization and power tracking. It adjusts HESS outputs solved in the day-ahead stage. A techno-economical object is implemented in real-time optimization to reduce electricity prices and improve electricity quality. A linearized battery degradation model is proposed to conquer the difficulty of solving optimal scheduling problems with consideration of battery degradation. Real measured load profiles from a high-speed railway substation are applied to verify the proposed model. The results show that in the day-ahead stage, with the integration of PV and HESS, the daily cost of the system decreased by 6.80%. The intraday optimization and real-time optimization in the proposed model can effectively adjust the HESS output when the actual load varies compared to the reference value. The linearized battery degradation model is proved to be accurate, with an average relative error of 0.8%.