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Study On The Design Of UPFC Multi-objective Controller And Its Impact On Power System

Posted on:2011-08-09Degree:MasterType:Thesis
Country:ChinaCandidate:Y L ShiFull Text:PDF
GTID:2132360302498221Subject:Power system and its automation
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High power electronic devices are used in Flexible AC Transmission System (FACTS) to improve the performance of power system. As a typical representative, Unified Power Flow Controller (UPFC) can concurrently or selectively control the impedance, the phase angle and the voltage of the transmission line. It can also improve transmission line capacity and voltage quality without affecting the stability of power system.First of all, the thesis introduces the basic concepts of FACTS, focusing on the researches which contain the structure, working principle, steady and dynamic mathematical models, control strategies and applications of UPFC.Second, the traditional proportional-integral (PI) control strategy is used. The series part of the UPFC is mainly used to control the real power and reactive power of the transmission line. The shunt part of the UPFC is used to control the public DC capacitor voltage and the node voltage where the UPFC is connected. The time domain simulations of the single machine infinite system with UPFC are presented by MATLAB. The simulation results show that UPFC has quick adjustment in changing active and reactive power flow, and also can maintain the bus voltage and improve the transient stability of the system.Third, use the real power flow performance index to find the optimal location of UPFC in multi-machine system. And then select the capacity of UPFC with the objective of gaining maximum economic benefits.Finally, the design of the UPFC multi-objective controller based on Quantum Genetic Algorithm (QGA) is showed. The QGA has advantages in smaller populations and faster convergence. The time domain simulation results verify the functions of this controller.
Keywords/Search Tags:Unified Power Flow Controller (UPFC), PI Control, Placement Selections and Parameter Setting, Quantum Genetic Algorithm (QGA), Multi-objective, MATLAB Simulation
PDF Full Text Request
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