DocumentCode :
2110600
Title :
Simulation Model of Hydraulic Turbine Speed Control System and Its Parameters Identification Based on Resilient Adaptive Particle Swarm Optimization Algorithm
Author :
Bai Ji-zhong ; Xie Ai-guo ; Yu Xin-Hua ; Zhou Li-kun
Author_Institution :
Inst. of Water Resources & Hydro-Electr. Eng., Xian Univ. of Technol., Xian, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
A new simulation model of hydraulic turbine speed control system and mathematical models of microcomputer governor is proposed, and to investigate the first and second regulation characteristics of hydraulic turbine speed control system, after hydraulic turbine group connected to the major power systems. Simulation model established and parameters were identified intelligently by using resilient adaptive particle swarm optimization algorithm. The model parameters were finally determined with the measurement and validation and simulation. The first and second regulation process was simulated, the actual test values and simulation result values were compared, and the specific mathematical model was tested and verified. Results show that the simulation and the actual test on site are almost same, the difference of all indicators are less than 0.5%. Simulation model built can reflect the characteristics of speed control system under hydraulic turbine group connected to the major power systems. A reliable method is provided for solving similar hydraulic turbine speed control system model and model parameters measured and identification and verification. The application prospects are good.
Keywords :
angular velocity control; hydraulic turbines; mathematical analysis; parameter estimation; particle swarm optimisation; actual test values; hydraulic turbine speed control system; indicators; mathematical models; microcomputer governor; parameters identification; power systems; regulation process; resilient adaptive particle swarm optimization algorithm; simulation model; speed control system; Adaptive control; Hydraulic turbines; Mathematical model; Parameter estimation; Particle swarm optimization; Power system modeling; Power system simulation; Programmable control; Testing; Velocity control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
Type :
conf
DOI :
10.1109/APPEEC.2010.5449127
Filename :
5449127
Link To Document :
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