ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1633719
This article is part of the Research TopicPlanning and Operation of Hybrid Renewable Energy Systems, Volume IIIView all articles
Two stage coordination planning method of wind power and storage considering uncertainty of distributed source-load
Provisionally accepted
- 1Electric Power Research institute of Yunnan Electric Power Grid Co.Ltd., Kunming 650217, China
- 2Wuhan University, Wuhan, China
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With the widespread integration of distributed power sources, the power grid is facing problems such as increased losses, rising costs, voltage fluctuations, and overload, resulting in increased operational complexity. Traditional scheduling planning is no longer applicable. Therefore, reasonable planning of distributed power generation and energy storage configurations has become particularly crucial. This article proposes a two-stage wind storage coordination planning method considering source load uncertainty, based on an improved antlion algorithm and taking into account distributed energy storage charging and discharging strategies. The first stage takes wind power site selection and capacity determination as the core, with voltage offset, network loss, and system comprehensive cost as the indicator system, establishes a multi-objective function model that takes into account the stability and economic indicators of the power grid, and determines the optimal planning strategy for its integration into the system. The second stage introduces distributed energy storage devices to reduce system power fluctuations, while minimizing the sum of operation and maintenance costs, and energy storage investment, It helps achieve an apt method for planning the optimal charging and discharging strategy for the energy storage.Finally, the improved antlion algorithm, aided by adaptive Levy flight and golden sine theory as improvement factors, was used to solve the two-stage wind storage coordination planning method. The proposed scheme was found to effectively improve the system-level voltage distribution, reduce network losses, and lower the overall system costs. The improved antlion algorithm demonstrated additional advantages, such as strong search ability, fast convergence speed, and high accuracy in the calculation process. The proposed solution presented in this paper has achieved a 27.95% increase in total capacity, a reduction of 32.14 kW in active power loss, and a decrease of 221,200 yuan in total cost. These improvements demonstrate that the proposed method is more aligned with practical requirements.
Keywords: Distributed power generation, energy storage, Adaptive Levy flight, Golden sine theory, Improved the Antlion Algorithm
Received: 23 May 2025; Accepted: 26 Aug 2025.
Copyright: © 2025 Su, Zhao, Xie, Shang, Wang and Deng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jie Zhao, Wuhan University, Wuhan, China
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