Author
Listed:
- Yunfei Xu
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Yiqiong He
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Hongyang Liu
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Heran Kang
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Jie Chen
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Wei Yue
(Economic and Technological Research Institute, State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot 010020, China)
- Wencong Xiao
(School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)
- Zhenning Pan
(School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)
Abstract
Integrated energy systems (IESs) serve as pivotal platforms for realizing the reform of energy structures. The rational planning of their equipment can significantly enhance operational economic efficiency, environmental friendliness, and system stability. Moreover, the inherent randomness and intermittency of renewable energy generation, coupled with the peak and valley characteristics of load demand, lead to fluctuations in the output of multi-energy coupling devices within the IES, posing a serious threat to its operational stability. To address these challenges, this paper focuses on the economic and stable operation of the IES, aiming to minimize the configuration costs of hybrid energy storage systems, system voltage deviations, and net load fluctuations. A multi-objective optimization planning model for an electric–hydrogen hybrid energy storage system is established. This model, applied to the IEEE-33 standard test system, utilizes the Multi-Objective Artificial Hummingbird Algorithm (MOAHA) to optimize the capacity and location of the electric–hydrogen hybrid energy storage system. The Multi-Objective Artificial Hummingbird Algorithm (MOAHA) is adopted due to its faster convergence and superior ability to maintain solution diversity compared to classical algorithms such as NSGA-II and MOEA/D, making it well-suited for solving complex non-convex planning problems. The simulation results demonstrate that the proposed optimization planning method effectively improves the voltage distribution and net load level of the IES distribution network, while the complementary characteristics of the electric–hydrogen hybrid energy storage system enhance the operational flexibility of the IES.
Suggested Citation
Yunfei Xu & Yiqiong He & Hongyang Liu & Heran Kang & Jie Chen & Wei Yue & Wencong Xiao & Zhenning Pan, 2025.
"Optimization Configuration of Electric–Hydrogen Hybrid Energy Storage System Considering Power Grid Voltage Stability,"
Energies, MDPI, vol. 18(13), pages 1-22, July.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:13:p:3506-:d:1693548
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