Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm

• Published in: Energy conversion and management Vol. 52; no. 1; pp. 374 - 381
• Main Authors: Li, Chaoshun, Zhou, Jianzhong
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 2011; Elsevier
• Subjects: Algorithms; Applied sciences; Computer simulation; Energy; energy conversion; Energy. Thermal use of fuels; Exact sciences and technology; Genetic algorithm; Gravity search algorithm; Hydraulic turbines; Hydroelectric power plants; Hydroturbine governing system; Installations for energy generation and conversion: thermal and electrical energy; Mathematical models; Modeling; Optimization; Parameter identification; Particle swarm optimization; Search algorithms; Strategy; turbines; water power; Gravity search algorithm; Parameter identification; Genetic algorithm; Modeling; Particle swarm optimization; Hydroturbine governing system
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2010.07.012

Parameter identification of hydraulic turbine governing system (HTGS) is crucial in precise modeling of hydropower plant and provides support for the analysis of stability of power system. In this paper, a newly developed optimization algorithm, called gravitational search algorithm (GSA), is introduced and applied in parameter identification of HTGS, and the GSA is improved by combination of the search strategy of particle swarm optimization. Furthermore, a new weighted objective function is proposed in the identification frame. The improved gravitational search algorithm (IGSA), together with genetic algorithm, particle swarm optimization and GSA, is employed in parameter identification experiments and the procedure is validated by comparing experimental and simulated results. Consequently, IGSA is shown to locate more precise parameter values than the compared methods with higher efficiency.