An Adaptive Model Predictive Control Based Control Strategy of BESS to Improve AGC Performance of Thermal Power Plant

Battery energy storage system (BESS) coordinated with thermal power plant (TPP) is a practical way to improve the frequency response of the system with high renewable integration. The high cost and lifespan degradation limit the capacity and capability of BESS in participating in automatic generation control (AGC). This paper proposes an adaptive model predictive control (MPC) strategy of BESS to improve AGC performance of TPP. A detailed model of the TPP is built to describe its dynamic behavior in AGC response to obtain the accurate system model for the proposed controller. An adaptive MPC control strategy incorporated the lifespan degradation of BESS is adopted to reduce the total cost of a one-time response and preserve the frequency regulation capability for future disturbance. Different weighting factors are chosen in the frequency regulation phase and state of charge (SoC) recovery phase under specified constraints respectively. The frequency regulation performance of the system is improved by the proposed strategy. The proposed control strategy is verified by a two-area system with wind farm. The results show that the proposed control strategy improves the frequency response of the system and reduce the lifespan degradation of the BESS significantly.