Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network
Available transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output u...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2024/5225784 |
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| _version_ | 1850225236476166144 |
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| author | Xiangfei Meng Lina Zhang Xin Tian Hongqing Chu Yao Wang Qingxin Shi |
| author_facet | Xiangfei Meng Lina Zhang Xin Tian Hongqing Chu Yao Wang Qingxin Shi |
| author_sort | Xiangfei Meng |
| collection | DOAJ |
| description | Available transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output uncertainty, and load demand uncertainty. Traditional works usually model the power source-load uncertainty by using robust optimization, interval optimization, or chance-constraint optimization, which cannot fully reflect the probabilistic distribution of the daily source-load uncertainty. This paper proposes an ATC assessment methodology based on the typical stochastic scenarios of renewable output and load demand of multiarea power systems. Furthermore, the conditional generative adversarial network (CGAN) algorithm is adopted to generate and select representative scenario sets based on historical raw data, which can fully reflect the usual operating condition of a system with high renewable energy penetration. The scenario set that is fed into the ATC assessment model can fully characterize the impact of source-load uncertainty on daily ATC. Finally, the proposed method is verified by a modified three-area IEEE 9-bus system and a real-world provincial power system. |
| format | Article |
| id | doaj-art-5774ce1bd28243f4bcd89b9c5fa5ab93 |
| institution | OA Journals |
| issn | 2050-7038 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Transactions on Electrical Energy Systems |
| spelling | doaj-art-5774ce1bd28243f4bcd89b9c5fa5ab932025-08-20T02:05:25ZengWileyInternational Transactions on Electrical Energy Systems2050-70382024-01-01202410.1155/2024/5225784Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial NetworkXiangfei Meng0Lina Zhang1Xin Tian2Hongqing Chu3Yao Wang4Qingxin Shi5Economic & Technology Research Institute of State Grid Shandong Electric Power CompanyEconomic & Technology Research Institute of State Grid Shandong Electric Power CompanyEconomic & Technology Research Institute of State Grid Shandong Electric Power CompanyEconomic & Technology Research Institute of State Grid Shandong Electric Power CompanyEconomic & Technology Research Institute of State Grid Shandong Electric Power CompanySchool of Electrical & Electronics EngineeringAvailable transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output uncertainty, and load demand uncertainty. Traditional works usually model the power source-load uncertainty by using robust optimization, interval optimization, or chance-constraint optimization, which cannot fully reflect the probabilistic distribution of the daily source-load uncertainty. This paper proposes an ATC assessment methodology based on the typical stochastic scenarios of renewable output and load demand of multiarea power systems. Furthermore, the conditional generative adversarial network (CGAN) algorithm is adopted to generate and select representative scenario sets based on historical raw data, which can fully reflect the usual operating condition of a system with high renewable energy penetration. The scenario set that is fed into the ATC assessment model can fully characterize the impact of source-load uncertainty on daily ATC. Finally, the proposed method is verified by a modified three-area IEEE 9-bus system and a real-world provincial power system.http://dx.doi.org/10.1155/2024/5225784 |
| spellingShingle | Xiangfei Meng Lina Zhang Xin Tian Hongqing Chu Yao Wang Qingxin Shi Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network International Transactions on Electrical Energy Systems |
| title | Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network |
| title_full | Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network |
| title_fullStr | Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network |
| title_full_unstemmed | Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network |
| title_short | Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network |
| title_sort | available transfer capability assessment of multiarea power systems with conditional generative adversarial network |
| url | http://dx.doi.org/10.1155/2024/5225784 |
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