Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/475603
Title: Mitigation of congestion in deregulated power system using facts controller
Researcher: Ramposelvi, R
Guide(s): Geetha, G and Chandrasekar, A
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
Congestion management
Optimal location of tcsc
Facts controller
University: Anna University
Completed Date: 2022
Abstract: Congestion is a main constraint in deregulated power system which newlineoccurs due to insufficient power transmission to fulfill the market demand newlineleading to voltage instability, power loss, short circuit, line overload and may newlinealso cause total system failure. So, in order to enhance the system stability, newlinepower flow capability and quality, congestion management methods are to be newlineemployed. Lately, usage of FACTS controllers in the congested line has newlineproven to improve the performance of deregulated power system. Among the newlinevarious FACTS controllers, TCSC shows a promising role in reducing the newlinecongestion by enhancing the power flow in transmission and distribution lines, newlineminimizing the power losses and improvising the voltage profile. However, newlinethe challenging part of using FACTS controllers is to find an optimal location newlinewhich in case failed may lead to huge capital cost. Therefore, as a maiden newlineattempt, this limitation is tried to be rectified by using optimization algorithms newlinefor finding the best location to mitigate the congestion cost effectively. The newlineunderlying motivation of this thesis is to manage the congestion in newlinederegulated power system using three different phases that are depicted newlinehereinafter.The initial phase of work was started with choosing an optimal newlinelocation for the TCSC controller using the seeker and particle swarm newlineoptimization algorithm for an IEEE-30 bus and 33 bus radial systems newlinerespectively. The comparative results proved the effectiveness of seeker over newlineparticle swarm optimization algorithm in mitigating the congestion by optimal newlineplacing of TCSC.Owing to the advantage of precise convergence capability of genetic newlinealgorithm, the second phase research was carried out placing the TCSC based newlineon the better performance index provided by the GA optimization algorithm. newlineThe performance index is based on both the real and reactive power, in newlinedetermining the optimal TCSC location. This was tested and proved using newlineIEEE-6, IEEE-14 and IEEE-30 bus systems. newline newline
Pagination: xvii,152p.
URI: http://hdl.handle.net/10603/475603
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File41.83 kBAdobe PDFView/Open
02_prelim pages.pdf1.54 MBAdobe PDFView/Open
03_content.pdf13.94 kBAdobe PDFView/Open
04_abstract.pdf9.42 kBAdobe PDFView/Open
05_chapter 1.pdf246.75 kBAdobe PDFView/Open
06_chapter 2.pdf80.67 kBAdobe PDFView/Open
07_chapter 3.pdf694.46 kBAdobe PDFView/Open
08_chapter 4.pdf617.87 kBAdobe PDFView/Open
09_chapter 5.pdf613.08 kBAdobe PDFView/Open
10_annexures.pdf86.62 kBAdobe PDFView/Open
80_recommendation.pdf64.22 kBAdobe PDFView/Open
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