Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters
Diversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage...
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/1996-1073/18/11/2697 |
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| author | Junlei Liu Jiekang Wu Zhen Lei |
| author_facet | Junlei Liu Jiekang Wu Zhen Lei |
| author_sort | Junlei Liu |
| collection | DOAJ |
| description | Diversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage on the power generation side, a robust two-stage optimization operation strategy for shared energy storage is proposed, taking into account leasing demand and multiple uncertainties, from the perspective of the sharing concept. A multi-scenario application framework for shared energy storage is established to provide leasing services for wind farm clusters, as well as auxiliary services for participating in the electric energy markets and frequency regulation markets, and the participation sequence is streamlined. Based on the operating and opportunity costs of shared energy storage, a pricing mechanism for leasing services is designed to explore the driving forces of wind farm clusters participating in leasing services from the perspective of cost assessment. Considering the uncertainty of wind power output and market electric prices, as well as the market operational characteristics, an optimized operation model for shared energy storage in the day-ahead and real-time stages is constructed. In the day-ahead stage, a Stackelberg game model is introduced to depict the energy sharing between wind farm clusters and shared energy storage, forming leasing prices, leasing capacities, and energy storage pre-scheduling plans at different time periods. In the real-time stage, the real-time prediction results of wind power output and electric prices are integrated with scheduling decisions, and an improved robust optimization model is used to dynamically regulate the pre-scheduling plan for leasing capacity and shared energy storage. Based on actual data from the electricity market in Guangdong Province, effectiveness verification is conducted, and the results showed that diversified application scenarios improve the utilization rate of shared energy storage in the power generation side by 52.87%, increasing economic benefits by CNY 188,700. The proposed optimized operation strategy has high engineering application value. |
| format | Article |
| id | doaj-art-ab5554fa016a456a9ec9c1c43fa4ed3e |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Energies |
| spelling | doaj-art-ab5554fa016a456a9ec9c1c43fa4ed3e2025-08-20T02:23:03ZengMDPI AGEnergies1996-10732025-05-011811269710.3390/en18112697Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm ClustersJunlei Liu0Jiekang Wu1Zhen Lei2Guangdong Power Grid Co., Ltd., Guangzhou 510600, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaDiversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage on the power generation side, a robust two-stage optimization operation strategy for shared energy storage is proposed, taking into account leasing demand and multiple uncertainties, from the perspective of the sharing concept. A multi-scenario application framework for shared energy storage is established to provide leasing services for wind farm clusters, as well as auxiliary services for participating in the electric energy markets and frequency regulation markets, and the participation sequence is streamlined. Based on the operating and opportunity costs of shared energy storage, a pricing mechanism for leasing services is designed to explore the driving forces of wind farm clusters participating in leasing services from the perspective of cost assessment. Considering the uncertainty of wind power output and market electric prices, as well as the market operational characteristics, an optimized operation model for shared energy storage in the day-ahead and real-time stages is constructed. In the day-ahead stage, a Stackelberg game model is introduced to depict the energy sharing between wind farm clusters and shared energy storage, forming leasing prices, leasing capacities, and energy storage pre-scheduling plans at different time periods. In the real-time stage, the real-time prediction results of wind power output and electric prices are integrated with scheduling decisions, and an improved robust optimization model is used to dynamically regulate the pre-scheduling plan for leasing capacity and shared energy storage. Based on actual data from the electricity market in Guangdong Province, effectiveness verification is conducted, and the results showed that diversified application scenarios improve the utilization rate of shared energy storage in the power generation side by 52.87%, increasing economic benefits by CNY 188,700. The proposed optimized operation strategy has high engineering application value.https://www.mdpi.com/1996-1073/18/11/2697wind farm clustersshared energy storagetwo-stage optimization strategymarket-oriented leaseleasing demandStackelberg game |
| spellingShingle | Junlei Liu Jiekang Wu Zhen Lei Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters Energies wind farm clusters shared energy storage two-stage optimization strategy market-oriented lease leasing demand Stackelberg game |
| title | Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters |
| title_full | Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters |
| title_fullStr | Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters |
| title_full_unstemmed | Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters |
| title_short | Two-Stage Optimization Strategy for Market-Oriented Lease of Shared Energy Storage in Wind Farm Clusters |
| title_sort | two stage optimization strategy for market oriented lease of shared energy storage in wind farm clusters |
| topic | wind farm clusters shared energy storage two-stage optimization strategy market-oriented lease leasing demand Stackelberg game |
| url | https://www.mdpi.com/1996-1073/18/11/2697 |
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