Deep transfer learning based assistant system for optimal investment decision of distribution networks
With the rapid development of clean energy and the deepening of the interaction between supply and demand, power grid investment upgrading measures involve many new elements, such as clean energy installation and distribution automation. Traditional investment decision-making models are difficult to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-04-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235248472101283X |
| _version_ | 1828404261458804736 |
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| author | Jianping Yang Yue Xiang Wei Sun Junyong Liu |
| author_facet | Jianping Yang Yue Xiang Wei Sun Junyong Liu |
| author_sort | Jianping Yang |
| collection | DOAJ |
| description | With the rapid development of clean energy and the deepening of the interaction between supply and demand, power grid investment upgrading measures involve many new elements, such as clean energy installation and distribution automation. Traditional investment decision-making models are difficult to establish and solve. In view of this, this paper analyzes the investment benefit mechanism directly from the perspective of investment input–output relationship, and designs an interactive auxiliary investment decision-making system based on correlation rule mining. The system constructs an investment benefit mapping model from power grid investment measures to benefit output by means of deep transfer learning, and provides three objective functions, which consider the optimal economy, performance improvement and comprehensive index optimization, thus assisting decision makers to formulate investment alternatives according to different investment needs. A case demonstrates the decision-making process based on an actual power grid, and verifies the practicability and effectiveness of the system. |
| first_indexed | 2024-12-10T10:33:42Z |
| format | Article |
| id | doaj.art-87c519195d4a4fa68e2926f4f4006a66 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-12-10T10:33:42Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-87c519195d4a4fa68e2926f4f4006a662022-12-22T01:52:30ZengElsevierEnergy Reports2352-48472022-04-0189196Deep transfer learning based assistant system for optimal investment decision of distribution networksJianping Yang0Yue Xiang1Wei Sun2Junyong Liu3College of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, China; Corresponding author.School of Engineering, University of Edinburgh, EH93DW Edinburgh, UKCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaWith the rapid development of clean energy and the deepening of the interaction between supply and demand, power grid investment upgrading measures involve many new elements, such as clean energy installation and distribution automation. Traditional investment decision-making models are difficult to establish and solve. In view of this, this paper analyzes the investment benefit mechanism directly from the perspective of investment input–output relationship, and designs an interactive auxiliary investment decision-making system based on correlation rule mining. The system constructs an investment benefit mapping model from power grid investment measures to benefit output by means of deep transfer learning, and provides three objective functions, which consider the optimal economy, performance improvement and comprehensive index optimization, thus assisting decision makers to formulate investment alternatives according to different investment needs. A case demonstrates the decision-making process based on an actual power grid, and verifies the practicability and effectiveness of the system.http://www.sciencedirect.com/science/article/pii/S235248472101283XInvestment decision-makingCorrelation ruleDeep transfer learning |
| spellingShingle | Jianping Yang Yue Xiang Wei Sun Junyong Liu Deep transfer learning based assistant system for optimal investment decision of distribution networks Energy Reports Investment decision-making Correlation rule Deep transfer learning |
| title | Deep transfer learning based assistant system for optimal investment decision of distribution networks |
| title_full | Deep transfer learning based assistant system for optimal investment decision of distribution networks |
| title_fullStr | Deep transfer learning based assistant system for optimal investment decision of distribution networks |
| title_full_unstemmed | Deep transfer learning based assistant system for optimal investment decision of distribution networks |
| title_short | Deep transfer learning based assistant system for optimal investment decision of distribution networks |
| title_sort | deep transfer learning based assistant system for optimal investment decision of distribution networks |
| topic | Investment decision-making Correlation rule Deep transfer learning |
| url | http://www.sciencedirect.com/science/article/pii/S235248472101283X |
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