Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response
The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method bas...
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| Format: | Article |
| Language: | English |
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University of Mohaghegh Ardabili
2018-12-01
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| Series: | Journal of Operation and Automation in Power Engineering |
| Subjects: | |
| Online Access: | http://joape.uma.ac.ir/article_722_3c6942baffea0b830ccf4ab673d820a9.pdf |
| _version_ | 1828186728145354752 |
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| author | M. Alilou D. Nazarpour H. Shayeghi |
| author_facet | M. Alilou D. Nazarpour H. Shayeghi |
| author_sort | M. Alilou |
| collection | DOAJ |
| description | The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based on the intelligent algorithm is proposed to optimal operate the demand side management in the presence of DG units and demand response. Firstly, the best location and capacity of different technologies of DG are selected by optimizing the technical index including the active and reactive loss and the voltage profile. Secondly, the daily performance of multi-DG and grid is optimized with and without considering the demand response. The economic and environmental indices are optimized in this step. In both steps, the non-dominated sorting firefly algorithm is utilized to multi-objective optimize the objective functions and then the fuzzy decision-making method is used to select the best result from the Pareto optimal solutions. Finally, the proposed method is implemented on the IEEE 33-bus distribution system and actual 101-bus distribution systems in Khoy-Iran. The obtained numerical results indicate the impact of the proposed method on improving the technical, economic and environmental indices of the distribution system. |
| first_indexed | 2024-04-12T07:21:34Z |
| format | Article |
| id | doaj.art-57baaea9b3514ce0937e37455fb25e2f |
| institution | Directory Open Access Journal |
| issn | 2322-4576 2423-4567 |
| language | English |
| last_indexed | 2024-04-12T07:21:34Z |
| publishDate | 2018-12-01 |
| publisher | University of Mohaghegh Ardabili |
| record_format | Article |
| series | Journal of Operation and Automation in Power Engineering |
| spelling | doaj.art-57baaea9b3514ce0937e37455fb25e2f2022-12-22T03:42:17ZengUniversity of Mohaghegh ArdabiliJournal of Operation and Automation in Power Engineering2322-45762423-45672018-12-016223024210.22098/joape.2006.4207.1328722Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand ResponseM. Alilou0D. Nazarpour1H. Shayeghi2Department of Electrical Engineering, Faculty of Engineering, University of Urmia, Urmia, IranFaculty of Electrical and Computer Engineering, University of Urmia, Urmia, IranElectrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran.The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based on the intelligent algorithm is proposed to optimal operate the demand side management in the presence of DG units and demand response. Firstly, the best location and capacity of different technologies of DG are selected by optimizing the technical index including the active and reactive loss and the voltage profile. Secondly, the daily performance of multi-DG and grid is optimized with and without considering the demand response. The economic and environmental indices are optimized in this step. In both steps, the non-dominated sorting firefly algorithm is utilized to multi-objective optimize the objective functions and then the fuzzy decision-making method is used to select the best result from the Pareto optimal solutions. Finally, the proposed method is implemented on the IEEE 33-bus distribution system and actual 101-bus distribution systems in Khoy-Iran. The obtained numerical results indicate the impact of the proposed method on improving the technical, economic and environmental indices of the distribution system.http://joape.uma.ac.ir/article_722_3c6942baffea0b830ccf4ab673d820a9.pdfDistributed generationDemand response programDemand side managementFuzzy decision-makingNon-dominated sorting firefly algorithm |
| spellingShingle | M. Alilou D. Nazarpour H. Shayeghi Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response Journal of Operation and Automation in Power Engineering Distributed generation Demand response program Demand side management Fuzzy decision-making Non-dominated sorting firefly algorithm |
| title | Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response |
| title_full | Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response |
| title_fullStr | Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response |
| title_full_unstemmed | Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response |
| title_short | Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response |
| title_sort | multi objective optimization of demand side management and multi dg in the distribution system with demand response |
| topic | Distributed generation Demand response program Demand side management Fuzzy decision-making Non-dominated sorting firefly algorithm |
| url | http://joape.uma.ac.ir/article_722_3c6942baffea0b830ccf4ab673d820a9.pdf |
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