Battery Energy Storage to Mitigate Wind Power Intermittencies Using Model Predictive Control

This paper presents a model predictive controller (MPC) approach for a battery energy storage system (BESS) to perform capacity firming on wind power intermittency. A state space model of the incremental type is considered to account for the process outputs and dynamics of the wind farm coupled with a BESS. The proposed control strategy has been decomposed into two control signal modes (charging/discharging) which will operate within the BESS state of charge (SOC) limits and constraints. The proposed MPC algorithm tracks a pre-defined reference power set point based on real wind power forecasting data. Simulation results demonstrate that a 40 MWh BESS can effectively minimize the tracking error of the power dispatched while optimally maximizing the BESS performance and state of health. Finally, an economic analysis is conducted to compare the economic stability regarding highly volatile electricity prices, between the proposed control scheme where the BESS follows a smoothened scheduled generation reference trajectory and the original wind power dispatched.