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Enhancing the performance of flexible AC transmission systems (FACTS) by computational intelligence

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Othman, Ahmed Mohamed
dc.date.accessioned 2012-08-30T06:30:49Z
dc.date.available 2012-08-30T06:30:49Z
dc.date.issued 2011
dc.identifier.isbn 978-952-60-4175-9 (printed)
dc.identifier.isbn 978-952-60-4176-6 (PDF)
dc.identifier.issn 1799-4934
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4973
dc.description.abstract The thesis studies and analyzes UPFC technology concerns the management of active and reactive power in the power networks to improve the performance aiming to reach the best operation criteria. The contributions of the thesis start with formatting, deriving, coding and programming the network equations required to link UPFC steady-state and dynamic models to the power systems. The thesis derives GA applications on UPFC to achieve real criteria on a real world sub-transmission network. An enhanced GA technique is proposed by enhancing and updating the working phases of the GA including the objective function formulation and computing the fitness using the diversity in the population and selection probability. The simulations and results show the advantages of using the proposed technique. Integrating the results by linking the case studies of the steady-state and the dynamic analysis is achieved. In the dynamic analysis section, a new idea for integrating the GA with ANFIS to be applied on the control action procedure is presented. The main subject of the thesis deals with enhancing the steady-state and dynamics performance of the power grids by Flexible AC Transmission System (FACTS) based on computational intelligence. Control of the electric power system can be achieved by designing the FACTS controller, where the new trends as Artificial Intelligence can be applied to this subject to enhance the characteristics of controller performance. The proposed technique will be applied to solve real problems in a Finnish power grid. The thesis seeks to deal, solve, and enhance performances until the year 2020, where the data used is until the conditions of year 2020. The FACTS device, which will be used in the thesis, is the most promising one, which known as the Unified Power Flow Controller (UPFC). The thesis achieves the optimization of the type, the location and the size of the power and control elements for UPFC to optimize the system performance. The thesis derives the criteria to install the UPFC in an optimal location with optimal parameters and then designs an AI based damping controller for enhancing power system dynamic performance. In this thesis, for every operating point GA is used to search for controllers' parameters, parameters found at certain operating point are different from those found at others. ANFISs are required in this case to recognize the appropriate parameters for each operating point. en
dc.format.extent 164 s. : kuv. ; 25 cm.
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University en
dc.relation.ispartofseries Aalto University publication series. Doctoral dissertations, 55/2011 en
dc.subject.other Electrical engineering
dc.title Enhancing the performance of flexible AC transmission systems (FACTS) by computational intelligence en
dc.type G4 Monografiaväitöskirja fi
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.contributor.department Sähkötekniikan laitos fi
dc.contributor.department Department of Electrical Engineering en
dc.subject.keyword United Power Flow Controller (UPFC) en
dc.subject.keyword genetic algorithm (GA) en
dc.subject.keyword optimal location en
dc.subject.keyword optimal settings en
dc.identifier.urn URN:ISBN:978-952-60-4176-6
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (monografia) fi
dc.type.ontasot Doctoral dissertation (monograph) en
dc.contributor.supervisor Lehtonen, Matti, Prof.
dc.contributor.supervisor El-Arini, Mahdi, Prof., Zagazig University
local.aalto.digifolder Aalto_68369
local.aalto.digiauth ask


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