PreprintArticleVersion 1This version is not peer-reviewed
State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control
Version 1
: Received: 15 October 2024 / Approved: 16 October 2024 / Online: 16 October 2024 (11:42:12 CEST)
How to cite:
Hou, R.; Liu, J.; Zhao, J.; Liu, J.; Chen, W. State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control. Preprints2024, 2024101260. https://doi.org/10.20944/preprints202410.1260.v1
Hou, R.; Liu, J.; Zhao, J.; Liu, J.; Chen, W. State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control. Preprints 2024, 2024101260. https://doi.org/10.20944/preprints202410.1260.v1
Hou, R.; Liu, J.; Zhao, J.; Liu, J.; Chen, W. State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control. Preprints2024, 2024101260. https://doi.org/10.20944/preprints202410.1260.v1
APA Style
Hou, R., Liu, J., Zhao, J., Liu, J., & Chen, W. (2024). State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control. Preprints. https://doi.org/10.20944/preprints202410.1260.v1
Chicago/Turabian Style
Hou, R., Jinhui Liu and Wenxiang Chen. 2024 "State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control" Preprints. https://doi.org/10.20944/preprints202410.1260.v1
Abstract
To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by Hybrid Energy Storage Systems (HESS), this paper proposes a State of Charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.
Keywords
SOC balancing control; secretary bird optimization algorithm; successive variational mode decomposition; variational mode decomposition; power allocation; multi-fuzzy control
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
