Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming
With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environmen...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/11/2790 |
| _version_ | 1797566430888067072 |
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| author | Xiangyu Kong Siqiong Zhang Bowei Sun Qun Yang Shupeng Li Shijian Zhu |
| author_facet | Xiangyu Kong Siqiong Zhang Bowei Sun Qun Yang Shupeng Li Shijian Zhu |
| author_sort | Xiangyu Kong |
| collection | DOAJ |
| description | With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified. |
| first_indexed | 2024-03-10T19:26:42Z |
| format | Article |
| id | doaj.art-61672a33028d4e4584c0e29fc9776b54 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T19:26:42Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-61672a33028d4e4584c0e29fc9776b542023-11-20T02:28:37ZengMDPI AGEnergies1996-10732020-06-011311279010.3390/en13112790Research on Home Energy Management Method for Demand Response Based on Chance-Constrained ProgrammingXiangyu Kong0Siqiong Zhang1Bowei Sun2Qun Yang3Shupeng Li4Shijian Zhu5Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaState Grid Liaoning Electric Power Company, Dalian 110006, ChinaTianjin Electric Power Research Institute, State Grid Tianjin Electric Power Company, Tianjin 300384, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaWith the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified.https://www.mdpi.com/1996-1073/13/11/2790demand responseenergy managementcontrol strategychance-constrained programmingparticle swarm optimization |
| spellingShingle | Xiangyu Kong Siqiong Zhang Bowei Sun Qun Yang Shupeng Li Shijian Zhu Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming Energies demand response energy management control strategy chance-constrained programming particle swarm optimization |
| title | Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming |
| title_full | Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming |
| title_fullStr | Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming |
| title_full_unstemmed | Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming |
| title_short | Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming |
| title_sort | research on home energy management method for demand response based on chance constrained programming |
| topic | demand response energy management control strategy chance-constrained programming particle swarm optimization |
| url | https://www.mdpi.com/1996-1073/13/11/2790 |
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