Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/537108
Title: | Unified Power Flow Controller UPFC Technique to Improve Power System Performance Using Neural Network |
Researcher: | Mathad, Vireshkumar G |
Guide(s): | Kulkarni, G H |
Keywords: | Engineering Engineering and Technology Engineering Electrical and Electronic |
University: | Visvesvaraya Technological University, Belagavi |
Completed Date: | 2022 |
Abstract: | he modern power systems are large in size, nonlinear in nature, more complex. newlineHenceforth the increase in demand results stress on power system, overloading of newlinetransmission line and oscillations in power system. Flexible Alternating Current newlineTransmission System (FACTS) technology is the recent propositions with a suitable newlinecontrol strategy to improve the transient stability of the power system. Unified Power newlineFlow Controller (UPFC) is a one of the family member of FACTS device, able to control newlinepower flow of the transmission system and provides new technology to solve stability newlineproblems. newlineThis research proposes a multi-objective work for optimum placement of UPFC newlineusing different optimization techniques. The power flow control has become significantly newlineimportant in the present power system, the UPFC plays an important role to control real newlineand reactive power selectively or simultaneously. To place UPFC at optimum location newlineGray Wolf Optimizer- Cuckoo Search (GWO-CS) algorithm is proposed and compared newlinewith Particle Swarm Optimization (PSO) and Cuckoo Search (CS) algorithms. The newlineperformance of proposed algorithm is evaluated on IEEE-30 and IEEE-62 bus test system newlineThe UPFC series and shunt control schemes have an impact on the power system newlinestability and its performance during different operating conditions. Power oscillations newlineoccur when system is dealing with any disturbance, controlling these oscillations is newlinechallenging task. In this research work Artificial Neural Network (ANN) based controller newlineis used to mitigate the power system oscillations and results are compared with newlineconventional PI controller. To show the effectiveness of proposed controller power swing newlineand fault analysis is carried on IEEE-9 bus system. The results of real and reactive power newlineoscillations, DC capacitor bus voltage and shunt converter voltage of UPFC is illustrated newline |
Pagination: | 101 |
URI: | http://hdl.handle.net/10603/537108 |
Appears in Departments: | Department of Electrical and Electronics Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 542.83 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.2 MB | Adobe PDF | View/Open | |
03_content.pdf | 3.04 MB | Adobe PDF | View/Open | |
04_abstract.pdf | 175.23 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 1.07 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 666.71 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 674.41 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.04 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.33 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 808 kB | Adobe PDF | View/Open | |
11_chapter 6.pdf | 3.47 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 588.49 kB | Adobe PDF | View/Open |
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