Market-Oriented Energy Management of a Hybrid Wind-Battery Energy Storage System Via Model Predictive Control With Constraint Optimizer

Abstract

This paper presents a market-oriented energy management system (EMS) for a hybrid power system composed of a wind energy conversion system and a battery energy storage system (BESS). The EMS is designed as a real-time model predictive control (MPC) system. The EMS dispatches the BESS to achieve the maximum net profit from the deregulated electricity market. Furthermore, the EMS aims at expanding the BESS lifetime by applying typical and practical constraints in the MPC problem on both the daily number of cycles (DNC) and depth of discharge (DOD). The MPC constraint optimizer is designed to tune the lifetime constraints optimally. It guarantees the optimal economic profit by finding the optimal DNC and DOD to achieve the maximum market revenue from energy arbitrage with the minimal expended-life cost. The effectiveness of this work is verified by comparison with a conventional MPC used in previous works. Simulation is conducted using real wind power and market data in Alberta, Canada.