Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique
Due to the great impact of the penetration and locations of distributed generators (DG) on the performance of the distribution system, this paper proposes a modified moth flame optimization (MMFO) algorithm. Two modifications are proposed in MMFO to enhance the exploration and exploitation balance a...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9114999/ |
| _version_ | 1818330389803958272 |
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| author | Ehab E. Elattar Salah K. Elsayed |
| author_facet | Ehab E. Elattar Salah K. Elsayed |
| author_sort | Ehab E. Elattar |
| collection | DOAJ |
| description | Due to the great impact of the penetration and locations of distributed generators (DG) on the performance of the distribution system, this paper proposes a modified moth flame optimization (MMFO) algorithm. Two modifications are proposed in MMFO to enhance the exploration and exploitation balance and overcome the shortcomings of the original MFO. The proposed MMFO is used to find the optimal location and sizing of DG units based on renewable energy sources in the distribution system. The main objective function is to minimize the total operating cost of the distribution system by considering the minimization of the total active power loss, voltage deviation of load buses, the DG units cost, and emission. This multi-objective function is converted to a coefficient single objective function with achieving different constraints. Also, the bus location index is employed to introduce the sorting list of locations to accomplish the narrow candidate buses list. Based on the candidate buses, the proposed MMFO is used to get the optimal location and sizing of DG units. The proposed MMFO algorithm has been applied to the IEEE 69-bus test distribution system and the results are compared with other published algorithms to prove its effectiveness and superiority. |
| first_indexed | 2024-12-13T13:03:11Z |
| format | Article |
| id | doaj.art-f5e8e17f799e4adfa30011f4c0353035 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T13:03:11Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f5e8e17f799e4adfa30011f4c03530352022-12-21T23:44:55ZengIEEEIEEE Access2169-35362020-01-01810962510963810.1109/ACCESS.2020.30017589114999Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization TechniqueEhab E. Elattar0https://orcid.org/0000-0002-3966-2584Salah K. Elsayed1Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi ArabiaDepartment of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi ArabiaDue to the great impact of the penetration and locations of distributed generators (DG) on the performance of the distribution system, this paper proposes a modified moth flame optimization (MMFO) algorithm. Two modifications are proposed in MMFO to enhance the exploration and exploitation balance and overcome the shortcomings of the original MFO. The proposed MMFO is used to find the optimal location and sizing of DG units based on renewable energy sources in the distribution system. The main objective function is to minimize the total operating cost of the distribution system by considering the minimization of the total active power loss, voltage deviation of load buses, the DG units cost, and emission. This multi-objective function is converted to a coefficient single objective function with achieving different constraints. Also, the bus location index is employed to introduce the sorting list of locations to accomplish the narrow candidate buses list. Based on the candidate buses, the proposed MMFO is used to get the optimal location and sizing of DG units. The proposed MMFO algorithm has been applied to the IEEE 69-bus test distribution system and the results are compared with other published algorithms to prove its effectiveness and superiority.https://ieeexplore.ieee.org/document/9114999/Modified moth flame algorithmdistributed generatorsrenewable energy sourcesbus location indexcoefficient single objective function |
| spellingShingle | Ehab E. Elattar Salah K. Elsayed Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique IEEE Access Modified moth flame algorithm distributed generators renewable energy sources bus location index coefficient single objective function |
| title | Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique |
| title_full | Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique |
| title_fullStr | Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique |
| title_full_unstemmed | Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique |
| title_short | Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique |
| title_sort | optimal location and sizing of distributed generators based on renewable energy sources using modified moth flame optimization technique |
| topic | Modified moth flame algorithm distributed generators renewable energy sources bus location index coefficient single objective function |
| url | https://ieeexplore.ieee.org/document/9114999/ |
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