Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO
Distributed generators (DGs) offer significant advantages to electric power systems, including improved system losses, stability, and reduced losses. However, realizing these benefits necessitates optimal DG site selection and sizing. This study proposes a traditional multiobjective particle swarm o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | Journal of Energy |
| Online Access: | http://dx.doi.org/10.1155/2023/6678491 |
| _version_ | 1797661480710045696 |
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| author | Tom Wanjekeche Andreas A. Ndapuka Lupembe Nicksen Mukena |
| author_facet | Tom Wanjekeche Andreas A. Ndapuka Lupembe Nicksen Mukena |
| author_sort | Tom Wanjekeche |
| collection | DOAJ |
| description | Distributed generators (DGs) offer significant advantages to electric power systems, including improved system losses, stability, and reduced losses. However, realizing these benefits necessitates optimal DG site selection and sizing. This study proposes a traditional multiobjective particle swarm optimization (PSO) approach to determine the optimal location and size of renewable energy-based DGs (wind and solar) on the Namibian distribution system. The aim is to enhance voltage profiles and minimize power losses and total DG cost. Probabilistic models are employed to account for the random nature of wind speeds and solar irradiances. This is used in an algorithm which eventually optimizes the siting and sizing of DGs using the nearest main substation as reference. The proposed method is tested on the Vhungu-Vhungu 11 kV distribution network in Namibia. Four cases were considered: base case with no DG, solar power, wind power, and a hybrid of both wind and solar. Optimal values for each case are determined and analyzed: 0.69.93 kW at 26 km for solar PV-based DG and 100 kW at 42 km for wind-based DG. These findings will serve as a valuable blueprint for future DG connections on the Namibian distribution network, providing guidance for optimizing system performance. |
| first_indexed | 2024-03-11T18:46:06Z |
| format | Article |
| id | doaj.art-dfe6717b0d9e47a7bc292608ebb15887 |
| institution | Directory Open Access Journal |
| issn | 2314-615X |
| language | English |
| last_indexed | 2024-03-11T18:46:06Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | Journal of Energy |
| spelling | doaj.art-dfe6717b0d9e47a7bc292608ebb158872023-10-12T00:00:23ZengHindawi LimitedJournal of Energy2314-615X2023-01-01202310.1155/2023/6678491Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSOTom Wanjekeche0Andreas A. Ndapuka1Lupembe Nicksen Mukena2Department of Electrical and Computer EngineeringDepartment of Electrical and Computer EngineeringDepartment of Electrical and Computer EngineeringDistributed generators (DGs) offer significant advantages to electric power systems, including improved system losses, stability, and reduced losses. However, realizing these benefits necessitates optimal DG site selection and sizing. This study proposes a traditional multiobjective particle swarm optimization (PSO) approach to determine the optimal location and size of renewable energy-based DGs (wind and solar) on the Namibian distribution system. The aim is to enhance voltage profiles and minimize power losses and total DG cost. Probabilistic models are employed to account for the random nature of wind speeds and solar irradiances. This is used in an algorithm which eventually optimizes the siting and sizing of DGs using the nearest main substation as reference. The proposed method is tested on the Vhungu-Vhungu 11 kV distribution network in Namibia. Four cases were considered: base case with no DG, solar power, wind power, and a hybrid of both wind and solar. Optimal values for each case are determined and analyzed: 0.69.93 kW at 26 km for solar PV-based DG and 100 kW at 42 km for wind-based DG. These findings will serve as a valuable blueprint for future DG connections on the Namibian distribution network, providing guidance for optimizing system performance.http://dx.doi.org/10.1155/2023/6678491 |
| spellingShingle | Tom Wanjekeche Andreas A. Ndapuka Lupembe Nicksen Mukena Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO Journal of Energy |
| title | Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO |
| title_full | Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO |
| title_fullStr | Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO |
| title_full_unstemmed | Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO |
| title_short | Strategic Sizing and Placement of Distributed Generation in Radial Distributed Networks Using Multiobjective PSO |
| title_sort | strategic sizing and placement of distributed generation in radial distributed networks using multiobjective pso |
| url | http://dx.doi.org/10.1155/2023/6678491 |
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