Title :
Parameter optimization for turbine DEH control system based on Improved Genetic Algorithm
Author :
Li, Na ; Lv, Lixia
Author_Institution :
North China Electr. Power Univ., Baoding, China
Abstract :
Improved Genetic Algorithm is used for parameter optimization of turbine DEH governing system. The algorithm can avoid the premature convergence effectively and improve the global and local search ability. The optimization results show that such method has the advantages of fast computation, high precision, and better program generality. It provides a new way for parameter optimization of steam turbine governing system.
Keywords :
convergence; genetic algorithms; hydraulic control equipment; steam turbines; digital electrical hydraulic control; global search ability; improved genetic algorithm; local search ability; parameter optimization; premature convergence; steam turbine governing system; turbine DEH control system; Control systems; Convergence; Electrical safety; Evolution (biology); Genetic algorithms; Genetic mutations; Hydraulic turbines; Optimization methods; Safety devices; Signal processing algorithms; Digital Electrical Hydraulic (DEH) control system; Genetic Algorithm; parameter optimization;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498598
