A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks
This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-05-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/10/5/618 |
| _version_ | 1828357775952969728 |
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| author | Ke-yan Liu Wanxing Sheng Yongmei Liu Xiaoli Meng |
| author_facet | Ke-yan Liu Wanxing Sheng Yongmei Liu Xiaoli Meng |
| author_sort | Ke-yan Liu |
| collection | DOAJ |
| description | This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO). Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA). In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible. |
| first_indexed | 2024-04-14T03:20:35Z |
| format | Article |
| id | doaj.art-222637557aef4c39b4ec4b5a82d06aab |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T03:20:35Z |
| publishDate | 2017-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-222637557aef4c39b4ec4b5a82d06aab2022-12-22T02:15:19ZengMDPI AGEnergies1996-10732017-05-0110561810.3390/en10050618en10050618A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution NetworksKe-yan Liu0Wanxing Sheng1Yongmei Liu2Xiaoli Meng3Power Distribution Department, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Department, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Department, China Electric Power Research Institute, Beijing 100192, ChinaPower Distribution Department, China Electric Power Research Institute, Beijing 100192, ChinaThis work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO). Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA). In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible.http://www.mdpi.com/1996-1073/10/5/618distribution network reconfigurationinterval analysisreliabilitydata uncertainty |
| spellingShingle | Ke-yan Liu Wanxing Sheng Yongmei Liu Xiaoli Meng A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks Energies distribution network reconfiguration interval analysis reliability data uncertainty |
| title | A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks |
| title_full | A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks |
| title_fullStr | A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks |
| title_full_unstemmed | A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks |
| title_short | A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks |
| title_sort | network reconfiguration method considering data uncertainties in smart distribution networks |
| topic | distribution network reconfiguration interval analysis reliability data uncertainty |
| url | http://www.mdpi.com/1996-1073/10/5/618 |
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