Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand
Abstract As the integration of renewable energy sources, such as wind power and photovoltaics, continues, the issue of system uncertainty has become more pronounced. This paper proposes a stochastic power system dispatch method based on affinely adjustable robust optimization (AARO) with a generaliz...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Energy Conversion and Economics |
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| Online Access: | https://doi.org/10.1049/enc2.70011 |
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| author | Yumin Zhang Yongchen Zhang Xizhen Xue Xingquan Ji Yunqi Wang Pingfeng Ye |
| author_facet | Yumin Zhang Yongchen Zhang Xizhen Xue Xingquan Ji Yunqi Wang Pingfeng Ye |
| author_sort | Yumin Zhang |
| collection | DOAJ |
| description | Abstract As the integration of renewable energy sources, such as wind power and photovoltaics, continues, the issue of system uncertainty has become more pronounced. This paper proposes a stochastic power system dispatch method based on affinely adjustable robust optimization (AARO) with a generalized linear polyhedron (GLP) uncertainty set that can accurately quantify the flexibility of the power system supply and demand as well as enhance the optimality of dispatch strategies. First, a GLP uncertainty set was established to characterize both the temporal stochasticity and spatial correlation of multiple renewable energy outputs. A correlation envelope was employed to reflect renewable energy outputs from historical data, and a polyhedral set was proposed to accurately describe the uncertainty for model formulation, which can effectively reduce model conservatism by minimizing empty regions. Furthermore, the range of net load variations was analysed to build a demand flexibility quantification model for the power system. Next, based on the expected operational value, a robust optimization dispatch model that considers the flexible supply and demand balance is developed within the affine strategy framework. Finally, simulations of a modified 6‐bus system and modified IEEE 57‐bus system validate the effectiveness of the proposed GLP‐AARO method for power system flexibility quantification and dispatch strategy optimization. |
| format | Article |
| id | doaj-art-c2626575f2db4124b3c66d2d137e83c0 |
| institution | OA Journals |
| issn | 2634-1581 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Conversion and Economics |
| spelling | doaj-art-c2626575f2db4124b3c66d2d137e83c02025-08-20T02:35:16ZengWileyEnergy Conversion and Economics2634-15812025-06-016317018610.1049/enc2.70011Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demandYumin Zhang0Yongchen Zhang1Xizhen Xue2Xingquan Ji3Yunqi Wang4Pingfeng Ye5College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao ChinaCollege of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao ChinaSchool of Electrical and Electronic Engineering Nanyang Technological University Singapore SingaporeCollege of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao ChinaDepartment of Electrical and Electronics Engineering RMIT Melbourne Victoria AustraliaCollege of Energy Storage Technology Shandong University of Science and Technology Qingdao ChinaAbstract As the integration of renewable energy sources, such as wind power and photovoltaics, continues, the issue of system uncertainty has become more pronounced. This paper proposes a stochastic power system dispatch method based on affinely adjustable robust optimization (AARO) with a generalized linear polyhedron (GLP) uncertainty set that can accurately quantify the flexibility of the power system supply and demand as well as enhance the optimality of dispatch strategies. First, a GLP uncertainty set was established to characterize both the temporal stochasticity and spatial correlation of multiple renewable energy outputs. A correlation envelope was employed to reflect renewable energy outputs from historical data, and a polyhedral set was proposed to accurately describe the uncertainty for model formulation, which can effectively reduce model conservatism by minimizing empty regions. Furthermore, the range of net load variations was analysed to build a demand flexibility quantification model for the power system. Next, based on the expected operational value, a robust optimization dispatch model that considers the flexible supply and demand balance is developed within the affine strategy framework. Finally, simulations of a modified 6‐bus system and modified IEEE 57‐bus system validate the effectiveness of the proposed GLP‐AARO method for power system flexibility quantification and dispatch strategy optimization.https://doi.org/10.1049/enc2.70011affinely adjustable robust optimizationflexibility quantificationgeneralized linear polyhedronrenewable energy sourcesspatiotemporal correlation |
| spellingShingle | Yumin Zhang Yongchen Zhang Xizhen Xue Xingquan Ji Yunqi Wang Pingfeng Ye Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand Energy Conversion and Economics affinely adjustable robust optimization flexibility quantification generalized linear polyhedron renewable energy sources spatiotemporal correlation |
| title | Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| title_full | Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| title_fullStr | Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| title_full_unstemmed | Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| title_short | Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| title_sort | affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand |
| topic | affinely adjustable robust optimization flexibility quantification generalized linear polyhedron renewable energy sources spatiotemporal correlation |
| url | https://doi.org/10.1049/enc2.70011 |
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