Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations
The strong uncertainty introduced by a high proportion of renewable energy sources integrated into the energy system complicates the internal optimization of system operation and may lead to the spillover of uncertainty risks, affecting the stable operation of the higher-level power grid. To address...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2025-02-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202408007 |
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| _version_ | 1850070418458673152 |
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| author | Jin LI Kemeng LIU Danli XU Weiju GAO Lei HUANG Haoxing WU Haochen HUA |
| author_facet | Jin LI Kemeng LIU Danli XU Weiju GAO Lei HUANG Haoxing WU Haochen HUA |
| author_sort | Jin LI |
| collection | DOAJ |
| description | The strong uncertainty introduced by a high proportion of renewable energy sources integrated into the energy system complicates the internal optimization of system operation and may lead to the spillover of uncertainty risks, affecting the stable operation of the higher-level power grid. To address this issue, a two-layer coordinated optimization strategy for the external response of a multi-energy complementary micro-energy grid system based on a shared energy storage station is proposed. Firstly, operational models for energy equipment within the micro-energy grid system are constructed, and operational modes and profit mechanisms for the shared energy storage station are proposed. Secondly, a two-layer coordinated optimization model considering two different stakeholders is established, with the micro-energy grid system operator as the upper layer and the shared energy storage station operator as the lower layer. Subsequently, the Hong's (2m+1) point estimation method is used to quantify the uncertainty of wind and solar power, and the two-layer nonlinear optimization model is transformed into a single-layer mixed-integer optimization model using the KKT conditions and Big-M method. Finally, simulation results demonstrate that the proposed strategy can effectively prevent the spillover of uncertainty risks associated with wind and solar power, reducing the operational costs of the micro-energy grid operator by 6.3%. |
| format | Article |
| id | doaj-art-56f9fcf181884af2a0147b97599daf9c |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2025-02-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-56f9fcf181884af2a0147b97599daf9c2025-08-20T02:47:33ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492025-02-01582435610.11930/j.issn.1004-9649.202408007zgdl-58-01-lijinDouble-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage StationsJin LI0Kemeng LIU1Danli XU2Weiju GAO3Lei HUANG4Haoxing WU5Haochen HUA6China Southern Power Grid Power Dispatching and Control Center, Guangzhou 510530, ChinaChina Southern Power Grid Power Dispatching and Control Center, Guangzhou 510530, ChinaChina Southern Power Grid Power Dispatching and Control Center, Guangzhou 510530, ChinaNARI Control System Co., Ltd., Nanjing 211103, ChinaNARI Control System Co., Ltd., Nanjing 211103, ChinaSchool of Electrical and Power Engineering, Hohai University, Nanjing 211100, ChinaSchool of Electrical and Power Engineering, Hohai University, Nanjing 211100, ChinaThe strong uncertainty introduced by a high proportion of renewable energy sources integrated into the energy system complicates the internal optimization of system operation and may lead to the spillover of uncertainty risks, affecting the stable operation of the higher-level power grid. To address this issue, a two-layer coordinated optimization strategy for the external response of a multi-energy complementary micro-energy grid system based on a shared energy storage station is proposed. Firstly, operational models for energy equipment within the micro-energy grid system are constructed, and operational modes and profit mechanisms for the shared energy storage station are proposed. Secondly, a two-layer coordinated optimization model considering two different stakeholders is established, with the micro-energy grid system operator as the upper layer and the shared energy storage station operator as the lower layer. Subsequently, the Hong's (2m+1) point estimation method is used to quantify the uncertainty of wind and solar power, and the two-layer nonlinear optimization model is transformed into a single-layer mixed-integer optimization model using the KKT conditions and Big-M method. Finally, simulation results demonstrate that the proposed strategy can effectively prevent the spillover of uncertainty risks associated with wind and solar power, reducing the operational costs of the micro-energy grid operator by 6.3%.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202408007multi-energy micro-gridrisk overflowshared energy storage stationhong's (2m+1) point estimation method |
| spellingShingle | Jin LI Kemeng LIU Danli XU Weiju GAO Lei HUANG Haoxing WU Haochen HUA Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations Zhongguo dianli multi-energy micro-grid risk overflow shared energy storage station hong's (2m+1) point estimation method |
| title | Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations |
| title_full | Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations |
| title_fullStr | Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations |
| title_full_unstemmed | Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations |
| title_short | Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations |
| title_sort | double layer optimization of external derivative response for multi energy microgrid with shared energy storage stations |
| topic | multi-energy micro-grid risk overflow shared energy storage station hong's (2m+1) point estimation method |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202408007 |
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