Open Access

ARTICLE

Research on Coordinated Operation Strategies for Wind Power Hybrid Energy Storage Systems Based on Model Predictive Control

Jiguang Wu¹, Qing Zhi^2,*, Jin Guan², Ruopeng Zhang², Lixia Wu², Shuhui Zhang², Caifeng Wen^3,4
1 Inner Mongolia Power (Group) Corporation Limited, Hohhot, 010051, China
2 Inner Mongolia Power (Group) Corporation Limited—Inner Mongolia Power Research Institute Branch, Hohhot, 010051, China
3 School of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot, 010051, China
4 Inner Mongolia Key Laboratory of Renewable Energy and Energy Storage Technology, Hohhot, 010051, China
* Corresponding Author: Qing Zhi. Email:

Energy Engineering https://doi.org/10.32604/ee.2025.073914

Received 28 September 2025; Accepted 21 November 2025; Published online 26 December 2025

Abstract

This paper proposes a hybrid energy storage control method that coordinates the minimum output of the wind–storage system and the SOC self-recovery capability, applied to stand-alone energy storage stations. Under the premise of meeting the wind power smoothing requirements, model predictive control (MPC) is employed to rapidly regulate the SOC and output of the energy storage system during the smoothing process, thereby enhancing its sustained and stable operation capability, and decomposing the original wind power into a direct grid-connected component and a hybrid energy storage smoothing component. Subsequently, the Northern Goshawk Algorithm-Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (NGO-ICEEMDAN) method is employed to decompose and reconstruct the hybrid energy storage power obtained from MPC rolling optimization by determining the optimal combination of white noise amplitude weight Nstd and the number of noise additions (NA), and to allocate the reconstructed power between the supercapacitor and the battery. Finally, simulation verification is conducted using actual 100 MW wind power data from a site in Inner Mongolia. The results demonstrate that the proposed strategy can coordinate the relationship among the minimum output of the hybrid energy storage system (HESS), SOC balancing, and grid-connected power fluctuations. The NGO-ICEEMDAN method enables more precise power allocation, thereby improving the rationality and efficiency of energy management in wind power hybrid energy storage systems.

---

Keywords

Standalone energy storage power station; hybrid energy storage system; model predictive control; empirical mode decomposition; multi-objective optimization

---