Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/298423
Title: Market power analysis including wind power integration
Researcher: Jain b marshel
Guide(s): Babulal CK
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
Market power
wind power
University: Anna University
Completed Date: 2019
Abstract: Market Power is a major concern in the development of restructured Power Systems. It is an adverse sign of competitive electricity market. Exercise of market power could raise the electricity price above competitive level, thereby increasing the financial burden of the consumers and reduce the market efficiency. The problem of visualization and mitigation of Market Power has gained more attention by the researchers to encourage competition and eliminate monopoly in the system. There are many indices to visualize Market Power in the Power System. However, only few indices consider the transmission congestion and generation/load variation in visualizing market power. The industrial power system is dynamic loaded and may involve transmission congestion. Hence it is necessary to have a methodology to visualize market power which considers load/generation variation and transmission constraints. This thesis presents a new method to measure market power using PSO based modified must run share indices and uses PST optimized by PSO to mitigate the severity of market power. The effectiveness of the proposed works has been tested in IEEE-14 bus system and modified IEEE-30 bus test system for without and with contingency cases. Renewable energy sources, especially wind energy plays significant role in meeting the increasing demand in the world. The integration of wind energy may have significant impact on market power of other generating firms in the restructured power systems. Hence it is necessary to study the impact of wind farm integration on market power. This thesis analyses the impact of wind farm integration on market power in a restructured environment. The wind farm is modelled based on artificial neural network trained using real time data. The effectiveness of the proposed works has been tested in IEEE-14 bus system and modified IEEE-30 bus test system. newline
Pagination: xx, 128p.
URI: http://hdl.handle.net/10603/298423
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File24.86 kBAdobe PDFView/Open
02_certificates.pdf250.12 kBAdobe PDFView/Open
03_abstracts.pdf8.22 kBAdobe PDFView/Open
04_acknowledgements.pdf61.5 kBAdobe PDFView/Open
05_contents.pdf162.85 kBAdobe PDFView/Open
06_listofabbreviations.pdf61.09 kBAdobe PDFView/Open
07_chapter1.pdf132.46 kBAdobe PDFView/Open
08_chapter2.pdf383.59 kBAdobe PDFView/Open
09_chapter3.pdf516.59 kBAdobe PDFView/Open
10_chapter4.pdf732.91 kBAdobe PDFView/Open
11_chapter5.pdf484.7 kBAdobe PDFView/Open
12_conclusion.pdf27.35 kBAdobe PDFView/Open
13_appendix.pdf296.05 kBAdobe PDFView/Open
14_references.pdf128.89 kBAdobe PDFView/Open
15_listofpublications.pdf65.93 kBAdobe PDFView/Open
80_recommendation.pdf155.82 kBAdobe PDFView/Open


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