Optimal allocation of distributed generation for power loss reduction and voltage profile improvement

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dc.contributor.advisorAwodele, Kehindeen_ZA
dc.contributor.advisorFolly, Komla Aen_ZA
dc.contributor.authorOluwole, Osaloni Oluwafunsoen_ZA
dc.date.accessioned2016-07-21T14:02:31Z
dc.date.available2016-07-21T14:02:31Z
dc.date.issued2016en_ZA
dc.description.abstractDistributed 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.en_ZA
dc.identifier.apacitationOluwole, O. O. (2016). <i>Optimal allocation of distributed generation for power loss reduction and voltage profile improvement</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/20578en_ZA
dc.identifier.chicagocitationOluwole, Osaloni Oluwafunso. <i>"Optimal allocation of distributed generation for power loss reduction and voltage profile improvement."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2016. http://hdl.handle.net/11427/20578en_ZA
dc.identifier.citationOluwole, O. 2016. Optimal allocation of distributed generation for power loss reduction and voltage profile improvement. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Oluwole, Osaloni Oluwafunso AB - 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. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Optimal allocation of distributed generation for power loss reduction and voltage profile improvement TI - Optimal allocation of distributed generation for power loss reduction and voltage profile improvement UR - http://hdl.handle.net/11427/20578 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20578
dc.identifier.vancouvercitationOluwole OO. Optimal allocation of distributed generation for power loss reduction and voltage profile improvement. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20578en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleOptimal allocation of distributed generation for power loss reduction and voltage profile improvementen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc (Eng)en_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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