Improved gravitational search algorithm for parameter identification of water turbine regulation system

Abstract Parameter identification of water turbine regulation system (WTRS) is crucial in precise modeling hydropower generating unit (HGU) and provides support for the adaptive control and stability analysis of power system. In this paper, an improved gravitational search algorithm (IGSA) is proposed and applied to solve the identification problem for WTRS system under load and no-load running conditions. This newly algorithm which is based on standard gravitational search algorithm (GSA) accelerates convergence speed with combination of the search strategy of particle swarm optimization and elastic-ball method. Chaotic mutation which is devised to stepping out the local optimal with a certain probability is also added into the algorithm to avoid premature. Furthermore, a new kind of model associated to the engineering practices is built and analyzed in the simulation tests. An illustrative example for parameter identification of WTRS is used to verify the feasibility and effectiveness of the proposed IGSA, as compared with standard GSA and particle swarm optimization in terms of parameter identification accuracy and convergence speed. The simulation results show that IGSA performs best for all identification indicators.

[1]  Yanbin Yuan,et al.  Unit commitment problem using enhanced particle swarm optimization algorithm , 2011, Soft Comput..

[2]  Chuanwen Jiang,et al.  PID controller parameters optimization of hydro-turbine governing systems using deterministic-chaotic-mutation evolutionary programming (DCMEP) , 2006 .

[3]  Hui He,et al.  Identification of hydraulic turbine governor system parameters based on Bacterial Foraging Optimization Algorithm , 2010, 2010 Sixth International Conference on Natural Computation.

[4]  Enrique Alba,et al.  The exploration/exploitation tradeoff in dynamic cellular genetic algorithms , 2005, IEEE Transactions on Evolutionary Computation.

[5]  Ertuğrul Çam,et al.  Fuzzy logic controller in interconnected electrical power systems for load-frequency control , 2005 .

[6]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[7]  Jing Cui,et al.  Notice of RetractionThe research and application on parameter identification of hydraulic turbine regulating system based on Particle Swarm Optimization and Uniform Design , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[8]  Xiaoming Chang,et al.  A chaotic digital secure communication based on a modified gravitational search algorithm filter , 2012, Inf. Sci..

[9]  Xiaohui Yuan,et al.  Identifying of Hydraulic Turbine Generating Unit Model Based on Neural Network , 2006, Sixth International Conference on Intelligent Systems Design and Applications.

[10]  Liang Wang,et al.  A modified differential evolution approach for dynamic economic dispatch with valve-point effects , 2008 .

[11]  Nand Kishor Nonlinear predictive control to track deviated power of an identified NNARX model of a hydro plant , 2008, Expert Syst. Appl..

[12]  Lin Gao,et al.  Parameter Identification of Hydro Generation System with Fluid Transients Based on Improved Genetic Algorithm , 2009, 2009 Fifth International Conference on Natural Computation.

[13]  Xin-hua Yu,et al.  Simulation Model of Hydraulic Turbine Speed Control System and Its Parameters Identification Based on Resilient Adaptive Particle Swarm Optimization Algorithm , 2010, 2010 Asia-Pacific Power and Energy Engineering Conference.

[14]  Xiaohui Yuan,et al.  Hydrothermal scheduling using chaotic hybrid differential evolution , 2008 .

[15]  Ahmed El-Shafie,et al.  A modified gravitational search algorithm for slope stability analysis , 2012, Eng. Appl. Artif. Intell..

[16]  S. S. Thakur,et al.  Optimal static state estimation using improved particle swarm optimization and gravitational search algorithm , 2013 .

[17]  Hossein Nezamabadi-pour,et al.  BGSA: binary gravitational search algorithm , 2010, Natural Computing.

[18]  Marjan Mernik,et al.  A parameter control method of evolutionary algorithms using exploration and exploitation measures with a practical application for fitting Sovova's mass transfer model , 2013, Appl. Soft Comput..

[19]  İlyas Eker,et al.  Governors for hydro-turbine speed control in power generation: a SIMO robust design approach , 2004 .

[20]  Pangao Kou,et al.  Piecewise function based gravitational search algorithm and its application on parameter identification of AVR system , 2014, Neurocomputing.

[21]  D. M. Vinod Kumar,et al.  Strategic bidding using fuzzy adaptive gravitational search algorithm in a pool based electricity market , 2013, Appl. Soft Comput..

[22]  Xiaohui Yuan,et al.  Optimal self-scheduling of hydro producer in the electricity market , 2010 .

[23]  Long Chen,et al.  Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor , 2011 .

[24]  Rahmat-Allah Hooshmand,et al.  A NEW PID CONTROLLER DESIGN FOR AUTOMATIC GENERATION CONTROL OF HYDRO POWER SYSTEMS , 2010 .

[25]  Xiaohui Yuan,et al.  Application of enhanced discrete differential evolution approach to unit commitment problem , 2009 .

[26]  Serhat Duman,et al.  Optimal reactive power dispatch using a gravitational search algorithm , 2012 .

[27]  Nand Kishor,et al.  Dynamic simulations of hydro turbine and its state estimation based LQ control , 2006 .

[28]  Behrooz Vahidi,et al.  Bacterial foraging solution based fuzzy logic decision for optimal capacitor allocation in radial di , 2011 .

[29]  Ugur Güvenc,et al.  Combined economic and emission dispatch solution using gravitational search algorithm , 2012, Sci. Iran..

[30]  Hsing-Chih Tsai,et al.  Gravitational particle swarm , 2013, Appl. Math. Comput..

[31]  M. Ghalambaz,et al.  Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm) , 2011 .

[32]  Hossein Shayeghi,et al.  Robust design of multimachine power system stabilizers using fuzzy gravitational search algorithm , 2013 .

[33]  Nand Kishor,et al.  Simulated response of NN based identification and predictive control of hydro plant , 2007, Expert Syst. Appl..

[34]  Serhat Duman,et al.  Optimal power flow using gravitational search algorithm , 2012 .

[35]  Zhengyun Ren,et al.  Computation of stabilizing PI and PID controllers by using Kronecker summation method , 2009 .

[36]  Jianzhong Zhou,et al.  Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm , 2011 .

[37]  Jian Xiao,et al.  Hydraulic turbine governing system identification using T-S fuzzy model optimized by chaotic gravitational search algorithm , 2013, Eng. Appl. Artif. Intell..