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Optimal allocation of distributed generation for power loss reduction and voltage profile improvement
Distributed generation (DG) integration in a distribution system has increased to high penetration levels. There is a need to improve technical benefits of DG integration by optimal allocation in a power system network. These benefits include electrical power losses reduction and voltage profile imp...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2016
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| _version_ | 1867613738136240130 |
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| access_status_str | Open Access |
| author | Oluwole, Osaloni Oluwafunso |
| author2 | Awodele, Kehinde |
| author_browse | Awodele, Kehinde Oluwole, Osaloni Oluwafunso |
| author_facet | Awodele, Kehinde Oluwole, Osaloni Oluwafunso |
| author_sort | Oluwole, Osaloni Oluwafunso |
| collection | Thesis |
| description | Distributed generation (DG) integration in a distribution system has increased to high penetration levels. There is a need to improve technical benefits of DG integration by optimal allocation in a power system network. These benefits include electrical power losses reduction and voltage profile improvement. Optimal DG location and sizing in a power system distribution network with the aim of reducing system power losses and improving the voltage profile still remain a major problem. Though much research has been done on optimal DG location and sizing in a power system distribution network with the aim of reducing system power losses and improving the voltage profile, most of the existing works in the literature use several techniques such as computation, artificial intelligence and an analytical approach, but they still suffer from several drawbacks. As a result, much can still be done in coming up with new algorithms to improve the already existing ones so as to address this important issue more efficiently and effectively. The majority of the proposed algorithms emphasize real power losses only in their formulations. They ignore the reactive power losses which are the key to the operation of the power systems. Hence, there is an urgent need for an approach that will incorporate reactive power and voltage profile in the optimization process, such that the effect of high power losses and poor voltage profile can be mitigated. This research used Genetic Algorithm and Improved Particle Swarm Optimization (GA-IPSO) for optimal placement and sizing of DG for power loss reduction and improvement of voltage profile. GA-IPSO is used to optimize DG location and size while considering both real and reactive power losses. The real and reactive power as well as power loss sensitivity factors were utilized in identifying the candidate buses for DG allocation. The GA-IPSO algorithm was programmed in Matlab. This algorithm reduces the search space for the search process, increases its rate of convergence and also eliminates the possibility of being trapped in local minima. Also, the new approach will help in reducing power loss and improve the voltage profile via placement and sizing. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20578 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:40:55.028Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/20578 Optimal allocation of distributed generation for power loss reduction and voltage profile improvement Oluwole, Osaloni Oluwafunso Awodele, Kehinde Folly, Komla A Electrical Engineering Distributed generation (DG) integration in a distribution system has increased to high penetration levels. There is a need to improve technical benefits of DG integration by optimal allocation in a power system network. These benefits include electrical power losses reduction and voltage profile improvement. Optimal DG location and sizing in a power system distribution network with the aim of reducing system power losses and improving the voltage profile still remain a major problem. Though much research has been done on optimal DG location and sizing in a power system distribution network with the aim of reducing system power losses and improving the voltage profile, most of the existing works in the literature use several techniques such as computation, artificial intelligence and an analytical approach, but they still suffer from several drawbacks. As a result, much can still be done in coming up with new algorithms to improve the already existing ones so as to address this important issue more efficiently and effectively. The majority of the proposed algorithms emphasize real power losses only in their formulations. They ignore the reactive power losses which are the key to the operation of the power systems. Hence, there is an urgent need for an approach that will incorporate reactive power and voltage profile in the optimization process, such that the effect of high power losses and poor voltage profile can be mitigated. This research used Genetic Algorithm and Improved Particle Swarm Optimization (GA-IPSO) for optimal placement and sizing of DG for power loss reduction and improvement of voltage profile. GA-IPSO is used to optimize DG location and size while considering both real and reactive power losses. The real and reactive power as well as power loss sensitivity factors were utilized in identifying the candidate buses for DG allocation. The GA-IPSO algorithm was programmed in Matlab. This algorithm reduces the search space for the search process, increases its rate of convergence and also eliminates the possibility of being trapped in local minima. Also, the new approach will help in reducing power loss and improve the voltage profile via placement and sizing. 2016-07-21T14:02:31Z 2016-07-21T14:02:31Z 2016 Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/20578 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Oluwole, Osaloni Oluwafunso Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| thesis_degree_str | Master's |
| title | Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| title_full | Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| title_fullStr | Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| title_full_unstemmed | Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| title_short | Optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| title_sort | optimal allocation of distributed generation for power loss reduction and voltage profile improvement |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/20578 |
| work_keys_str_mv | AT oluwoleosalonioluwafunso optimalallocationofdistributedgenerationforpowerlossreductionandvoltageprofileimprovement |