Imperialist competitive algorithm based optimal power flow

In this paper, a new approach based on Imperialist Competitive Algorithm (ICA) optimization is proposed for solving the optimal power flow (OPF) problem. ICA is one of the evolutionary optimization algorithms which are based on colonialism as a social-political phenomenon. The objective of the OPF problem is to minimize the system total generation cost with regard to some inequality and equality constraints such as the units' active and reactive power output limits, generation/demand balance, power flow limit of lines, voltage on busses, and transformer taps. To validate the proposed algorithm, it is applied to the IEEE 30-buses system and results are compared with those of genetic algorithm and particle swarm optimization and the effectiveness of the proposed algorithm is justified.

[1]  Caro Lucas,et al.  Vehicle Fuzzy Controller Design Using Imperialist Competitive Algorithm , 2008 .

[2]  Hiroshi Sasaki,et al.  A decoupled solution of hydro-thermal optimal power flow problem by means of interior point method and network programming , 1998 .

[3]  Zahra Nasiri-Gheidari,et al.  Application of an imperialist competitive algorithm to the design of a linear induction motor , 2010 .

[4]  O. Alsac,et al.  Optimal Load Flow with Steady-State Security , 1974 .

[5]  Vassilios Petridis,et al.  Optimal power flow by enhanced genetic algorithm , 2002 .

[6]  Philip G. Hill,et al.  Power generation , 1927, Journal of the A.I.E.E..

[7]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

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

[9]  Claudio A. Roa-Sepulveda,et al.  A solution to the optimal power flow using simulated annealing , 2003 .

[10]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. II. Newton, linear programming and interior point methods , 1999 .

[11]  Mahmoud A. Abo-Sinna,et al.  A solution to the optimal power flow using genetic algorithm , 2004, Appl. Math. Comput..

[12]  Caro Lucas,et al.  Designing MIMO PIID controller using colonial competitive algorithm: Applied to distillation column process , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[13]  R. Yokoyama,et al.  Improved genetic algorithms for optimal power flow under both normal and contingent operation states , 1997 .

[14]  Hua Wei,et al.  An interior point nonlinear programming for optimal power flow problems with a novel data structure , 1997 .

[15]  K. S. Swarup,et al.  Solving multi-objective optimal power flow using differential evolution , 2008 .

[16]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[17]  K. Fahd,et al.  Optimal Power Flow Using Tabu Search Algorithm , 2002 .

[18]  Abbas Rabiee,et al.  Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch , 2012 .

[19]  S. R. Spea,et al.  Optimal power flow using differential evolution algorithm , 2010 .

[20]  William F. Tinney,et al.  Optimal Power Flow Solutions , 1968 .

[21]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[22]  M. A. Abido,et al.  Optimal power flow using particle swarm optimization , 2002 .

[23]  B. Yegnanarayana,et al.  Genetic-algorithm-based optimal power flow for security enhancement , 2005 .

[24]  Caro Lucas,et al.  Colonial competitive algorithm: A novel approach for PID controller design in MIMO distillation column process , 2008, Int. J. Intell. Comput. Cybern..