Optimal scheduling of distributed shared energy storage based on optimal SOC interval
Proposed within the framework of the sharing economy, Shared Energy Storage (SES) aims to enhance the efficiency of Energy Storage Systems (ESS) and drive down costs. This study focuses on an innovative approach to emphasize the multifaceted utilization of individual ESS units and the centralized us...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1444791/full |
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| author | Tong Zhang Liudong Zhang Yan Chen Zhiqiang Peng |
| author_facet | Tong Zhang Liudong Zhang Yan Chen Zhiqiang Peng |
| author_sort | Tong Zhang |
| collection | DOAJ |
| description | Proposed within the framework of the sharing economy, Shared Energy Storage (SES) aims to enhance the efficiency of Energy Storage Systems (ESS) and drive down costs. This study focuses on an innovative approach to emphasize the multifaceted utilization of individual ESS units and the centralized use of dispersed ESS resources. Renewable Energy Power Plants (REPPs) collaborate to create SES pools, leveraging their ESS assets. Beyond meeting the needs of REPPs, these resources are shared for ancillary services like Secondary Frequency Regulation (SFR) to yield additional benefits. The paper delves into the scheduling techniques for SES. While conventional day-ahead robust optimization algorithms specify ESS power output for each period, they struggle to adjust schedules due to time-dependent constraints like renewable energy output and ESS state limitations. To address this, a distributed SES scheduling method based on optimal operating intervals is proposed. This method introduces an optimal interval variable for Energy Storage State of Charge (SOC) into the traditional three-layer optimization problem, effectively decoupling time-related constraints. Furthermore, a novel Nested Column and Constraint Generation (Nested C&CG) algorithm is presented to solve the mathematical model. Lastly, a revenue sharing model grounded in cooperative game theory is introduced, along with an illustrative example showcasing the efficacy of the proposed approach in managing uncertainties. |
| format | Article |
| id | doaj-art-14097fea3e2e4b5b9cef8ea600a47001 |
| institution | DOAJ |
| issn | 2296-598X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj-art-14097fea3e2e4b5b9cef8ea600a470012025-08-20T02:43:20ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2025-02-011210.3389/fenrg.2024.14447911444791Optimal scheduling of distributed shared energy storage based on optimal SOC intervalTong Zhang0Liudong Zhang1Yan Chen2Zhiqiang Peng3State Grid Jiangsu Electric Power Co., Ltd., Research Institute, Nanjing, ChinaState Grid Jiangsu Electric Power Company, Nanjing, ChinaYangzhou Power Supply Branch, Jiangsu Electric Power Co., Ltd., Yangzhou, ChinaState Grid Jiangsu Electric Power Co., Ltd., Research Institute, Nanjing, ChinaProposed within the framework of the sharing economy, Shared Energy Storage (SES) aims to enhance the efficiency of Energy Storage Systems (ESS) and drive down costs. This study focuses on an innovative approach to emphasize the multifaceted utilization of individual ESS units and the centralized use of dispersed ESS resources. Renewable Energy Power Plants (REPPs) collaborate to create SES pools, leveraging their ESS assets. Beyond meeting the needs of REPPs, these resources are shared for ancillary services like Secondary Frequency Regulation (SFR) to yield additional benefits. The paper delves into the scheduling techniques for SES. While conventional day-ahead robust optimization algorithms specify ESS power output for each period, they struggle to adjust schedules due to time-dependent constraints like renewable energy output and ESS state limitations. To address this, a distributed SES scheduling method based on optimal operating intervals is proposed. This method introduces an optimal interval variable for Energy Storage State of Charge (SOC) into the traditional three-layer optimization problem, effectively decoupling time-related constraints. Furthermore, a novel Nested Column and Constraint Generation (Nested C&CG) algorithm is presented to solve the mathematical model. Lastly, a revenue sharing model grounded in cooperative game theory is introduced, along with an illustrative example showcasing the efficacy of the proposed approach in managing uncertainties.https://www.frontiersin.org/articles/10.3389/fenrg.2024.1444791/fulldistributed shared energy storageoptimization scheduling methodthe optimal SOC intervalmultiple auxiliary servicestime coupling. (Min.5–Max. 8 |
| spellingShingle | Tong Zhang Liudong Zhang Yan Chen Zhiqiang Peng Optimal scheduling of distributed shared energy storage based on optimal SOC interval Frontiers in Energy Research distributed shared energy storage optimization scheduling method the optimal SOC interval multiple auxiliary services time coupling. (Min.5–Max. 8 |
| title | Optimal scheduling of distributed shared energy storage based on optimal SOC interval |
| title_full | Optimal scheduling of distributed shared energy storage based on optimal SOC interval |
| title_fullStr | Optimal scheduling of distributed shared energy storage based on optimal SOC interval |
| title_full_unstemmed | Optimal scheduling of distributed shared energy storage based on optimal SOC interval |
| title_short | Optimal scheduling of distributed shared energy storage based on optimal SOC interval |
| title_sort | optimal scheduling of distributed shared energy storage based on optimal soc interval |
| topic | distributed shared energy storage optimization scheduling method the optimal SOC interval multiple auxiliary services time coupling. (Min.5–Max. 8 |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1444791/full |
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