DocumentCode :
2295541
Title :
Identification of hydraulic turbine governor system parameters based on Bacterial Foraging Optimization Algorithm
Author :
Kou, Pangao ; Zhou, Jianzhong ; Li, Chaoshun ; He, Yaoyao ; He, Hui
Author_Institution :
Coll. of Hydroelectric Digitization Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
7
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
3339
Lastpage :
3343
Abstract :
Hydraulic turbine generating unit plays an important role in power system. An accurate hydraulic turbine governor system model is essential to analyze its stability and dynamic performance. In order to identify the parameters of the hydraulic turbine governor system model, a new approach of Bacterial Foraging Optimization Algorithm (BFOA) is introduced in this study. To improve the precision of the identification process, a modified objective function is proposed based on the measurement of gate opening, mechanical torque and generator speed from a simulated model. The improved objective function (IOF) and the conventional objective function (COF) are used in the identification and two sets of parameters are derived and compared. The results show that BFOA is effective in identification of hydraulic turbine governor system and parameters derived from the modified objective function have a higher accuracy.
Keywords :
hydraulic turbines; hydroelectric generators; optimisation; power engineering computing; power system stability; BFOA; bacterial foraging optimization algorithm; gate opening; generator speed; hydraulic turbine generating unit; hydraulic turbine governor system; mechanical torque; objective function; power system; Hydraulic turbines; Microorganisms; Object oriented modeling; Object recognition; Parameter estimation; Torque; Bacterial Foraging Optimization Algorithm; Identification; governor system; hydraulic turbine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583639
Filename :
5583639
Link To Document :
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