Maximum loadability limit of power system using hybrid differential evolution with particle swarm optimization

Abstract Differential evolution (DE), a simple evolutionary algorithm which shows superior performance in global optimization. Since it utilizes the differential information to get the new candidate solution, sometimes it results in instability of performance. Particle swarm optimization (PSO) is widely used to solve the optimization problems as it can converge quickly. But PSO easily gets stuck in local optima. Hybridization of DE and PSO (DEPSO) eliminates the disadvantages of both. This paper presents the application of DEPSO algorithm to determine the maximum loadability limit of power system. It is tested on Matpower 30 bus and IEEE 118 bus systems. To compare the performance of this DEPSO algorithm with other evolutionary algorithms like DE and Multi Agent Hybrid PSO, statistical measures like best, mean, standard deviation of results and average computation time over 20 independent trials are considered here. The results show the better performance of DEPSO algorithm to solve the maximum loadability problem. DEPSO algorithm provides high maximum loading point in reduced time.

[1]  S. C. Choube,et al.  Loadability margin enhancement using co-ordinated aggregation based particle swarm optimization (CAPSO) , 2010 .

[2]  G. Irisarri,et al.  Maximum loadability of power systems using interior point nonlinear optimization method , 1997 .

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

[4]  Xiao-Feng Xie,et al.  DEPSO: hybrid particle swarm with differential evolution operator , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[5]  A. Shunmugalatha,et al.  Maximum Loadability Limit of a Power System Using Multiagent-based Hybrid Particle Swarm Optimization , 2008 .

[6]  Salman Mohagheghi,et al.  Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems , 2008, IEEE Transactions on Evolutionary Computation.

[7]  A. Shunmugalatha,et al.  Optimum cost of generation for maximum loadability limit of power system using hybrid particle swarm optimization , 2008 .

[8]  H. Sato.  Computation of power system loadability limits , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[9]  Venkataramana Ajjarapu,et al.  The continuation power flow: a tool for steady state voltage stability analysis , 1991 .

[10]  Ganesh K. Venayagamoorthy,et al.  Evolving Digital Circuits Using Hybrid Particle Swarm Optimization and Differential Evolution , 2006, Int. J. Neural Syst..

[11]  M. Batouche,et al.  Hybrid particle swarm with differential evolution for multimodal image registration , 2004, 2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04..

[12]  H.K.M. Youssef,et al.  Load flow solution using hybrid particle swarm optimization , 2004, International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04..

[13]  Parimal Acharjee.  Identification of maximum loadability limit and weak buses using security constraint genetic algorithm , 2012 .

[14]  Ji-Pyng Chiou,et al.  Robust searching hybrid differential evolution method for optimal reactive power planning in large-scale distribution systems , 2007 .

[15]  Z. Dong,et al.  A Modified Differential Evolution Algorithm With Fitness Sharing for Power System Planning , 2008, IEEE Transactions on Power Systems.

[16]  Hosam K. M. Youssef,et al.  Maximum loadability of power systems using hybrid particle swarm optimization , 2006 .

[17]  K.P. Wong,et al.  Application of Differential Evolution Algorithm for Transient Stability Constrained Optimal Power Flow , 2008, IEEE Transactions on Power Systems.

[18]  Han Huang,et al.  A Particle Swarm Optimization Algorithm with Differential Evolution , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[19]  Zhihua Qu,et al.  Loadability of power systems with steady-state and dynamic security constraints , 2003 .

[20]  C. K. Babulal,et al.  A Novel Approach for ATC Computation in Deregulated Environment JES , 2006 .