On the Design of Intelligent Controllers for the Unified Power Flow Controller to Improve Power System Performance
碩士 === 國立聯合大學 === 電機工程學系碩士班 === 94 === This thesis presents the design of intelligent controllers based on fuzzy neural networks (FNN) and recurrent fuzzy neural networks (RFNN) for the Unified Power Flow Controller (UPFC) to provide better control features in performing various power flow control f...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/56709847546835116519 |
| Summary: | 碩士 === 國立聯合大學 === 電機工程學系碩士班 === 94 === This thesis presents the design of intelligent controllers based on fuzzy neural networks (FNN) and recurrent fuzzy neural networks (RFNN) for the Unified Power Flow Controller (UPFC) to provide better control features in performing various power flow control functions during steady-state and transient operations of power systems. Two separate FNN (or RFNN) tuned PI con¬trollers or two direct FNN (or RFNN) controllers are respectively used for controlling the shunt and series converter modules of the UPFC. The principles and various structures of the fuzzy and recurrent fuzzy neural networks are investigated in full. Comprehensive simu¬lation studies carried out on commercial grade software packages are described and results of various power flow control examples showing the concerned power system parameters and the excellent control performance of the FNN and RFNN based UPFC are presented and discussed. Typical simulation results of the proposed controllers are compared with the conventional proportional plus integral (PI) controllers to demonstrate the superiority and effectiveness of the new FNN based control algorithm.
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