A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management
One of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the wors...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2021/7079296 |
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| author | Qing Duan Wanxing Sheng Haoqing Wang Caihong Zhao Chunyan Ma |
| author_facet | Qing Duan Wanxing Sheng Haoqing Wang Caihong Zhao Chunyan Ma |
| author_sort | Qing Duan |
| collection | DOAJ |
| description | One of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the worst-case scenario and is therefore somewhat conservative. In this study, focusing on the energy management of a typical islanded microgrid and considering uncertainties such as the power output of renewable energy sources and the power demand of loads, an expected-scenario-oriented two-stage robust optimization (E-TSRO) method is proposed to alleviate the conservative tendency of the C-TSRO method because the E-TSRO method chooses to optimize the system cost according to the expected scenario instead, while ensuring the feasibility of the first-stage variables for all possible scenarios, including the worst case. According to the structural characteristics of the proposed model based on the E-TSRO method, a column-and-constraint generation (C & CG) algorithm is utilized to solve the proposed model. Finally, the effectiveness of the E-TSRO model and the solution algorithm are analysed and validated through a series of experiments, thus obtaining some important conclusions, i.e., the economic efficiency of system operation can be improved at about 6.7% in comparison with the C-TSRO results. |
| format | Article |
| id | doaj-art-ae44e831caab485c9a51e74490297277 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-ae44e831caab485c9a51e744902972772025-02-03T01:25:10ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2021-01-01202110.1155/2021/70792967079296A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy ManagementQing Duan0Wanxing Sheng1Haoqing Wang2Caihong Zhao3Chunyan Ma4Power Distribution Technology Center, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Technology Center, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Technology Center, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Technology Center, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Technology Center, China Electric Power Research Institute, Beijing 100192, ChinaOne of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the worst-case scenario and is therefore somewhat conservative. In this study, focusing on the energy management of a typical islanded microgrid and considering uncertainties such as the power output of renewable energy sources and the power demand of loads, an expected-scenario-oriented two-stage robust optimization (E-TSRO) method is proposed to alleviate the conservative tendency of the C-TSRO method because the E-TSRO method chooses to optimize the system cost according to the expected scenario instead, while ensuring the feasibility of the first-stage variables for all possible scenarios, including the worst case. According to the structural characteristics of the proposed model based on the E-TSRO method, a column-and-constraint generation (C & CG) algorithm is utilized to solve the proposed model. Finally, the effectiveness of the E-TSRO model and the solution algorithm are analysed and validated through a series of experiments, thus obtaining some important conclusions, i.e., the economic efficiency of system operation can be improved at about 6.7% in comparison with the C-TSRO results.http://dx.doi.org/10.1155/2021/7079296 |
| spellingShingle | Qing Duan Wanxing Sheng Haoqing Wang Caihong Zhao Chunyan Ma A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management Discrete Dynamics in Nature and Society |
| title | A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management |
| title_full | A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management |
| title_fullStr | A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management |
| title_full_unstemmed | A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management |
| title_short | A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management |
| title_sort | two stage robust optimization method based on the expected scenario for islanded microgrid energy management |
| url | http://dx.doi.org/10.1155/2021/7079296 |
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