Optimized Frequency Regulation Strategy for Wind Farms with Integrated Energy Storage Using Improved Model Predictive Control

This study aims to enhance frequency regulation in wind farms integrated into large-scale wind power. We propose a strategy that combines energy storage with wind power regulation to overcome limitations of wind turbines, such as short inertia control duration and slower pitch response, thereby improving frequency stability in the power system. We employ an improved Model Predictive Control (MPC) method to construct an optimization objective function aimed at minimizing frequency deviation, incorporating a virtual control. This model allows for real-time adjustments of weights based on frequency changes, optimizing the power outputs from both wind turbines and energy storage systems. We compare three frequency regulation strategies — wind-only, storage-only, and wind-storage joint regulation — and offer insights into the optimal capacity allocation for the energy storage system. The results indicate that the total power and storage capacity required for the wind-storage joint frequency regulation scheme are only 67% and 11.1% of those needed for the storage-only scheme, respectively. This demonstrates a significant reduction in configuration costs for the energy storage system, thereby enhancing the economic and practical feasibility of energy storage technology in wind power frequency regulation.