Krill Herd Algorithm for Solution of Economic Dispatch with Valve-Point Loading Effect

The article presents a novel bio-inspired Krill Herd (KH) algorithm to solve economic dispatch problems. KH algorithm is based on crowding behavior of the krill individuals and achieves a near global optimum solution by using three main actives. The proposed algorithm is tested by considering three and six generating unit systems on different loads on objective function. The attained results have proved that the KH algorithm provides remarkable results as compared with the other optimization algorithms reported in the literature.

[1]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[2]  Chern-Lin Chen,et al.  Branch-and-bound scheduling for thermal generating units , 1993 .

[3]  Harish Pulluri,et al.  A solution network based on stud krill herd algorithm for optimal power flow problems , 2018, Soft Comput..

[4]  Amir Hossein Gandomi,et al.  Hybrid krill herd algorithm with differential evolution for global numerical optimization , 2014, Neural Computing and Applications.

[5]  S. Fanshel,et al.  Economic Power Generation Using Linear Programming , 1964 .

[6]  Harish Pulluri,et al.  Application of stud krill herd algorithm for solution of optimal power flow problems , 2017 .

[7]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[8]  Amir Hossein Gandomi,et al.  Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect , 2012, Appl. Soft Comput..

[9]  P. K. Chattopadhyay,et al.  Evolutionary programming techniques for economic load dispatch , 2003, IEEE Trans. Evol. Comput..

[10]  Lawrence Hasdorff,et al.  Economic Dispatch Using Quadratic Programming , 1973 .

[11]  Leandro dos Santos Coelho,et al.  An improved harmony search algorithm for power economic load dispatch , 2009 .

[12]  B. Vedik,et al.  Economic dispatch with valve point effect using symbiotic oragnisms search algorithm , 2016, 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS).

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

[14]  Osvaldo R. Saavedra,et al.  REPLY - CONCERNING THE COMMENTS ON 'EFFICIENT EVOLUTIONARY STRATEGY OPTIMISATION PROCEDURE TO SOLVE THE NONCONVEX ECONOMIC DISPATCH ROBLEM WITH GENERATOR CONSTRAINTS' , 2007 .

[15]  Osvaldo R. Saavedra,et al.  EFFICIENT EVOLUTIONARY STRATEGY OPTIMISATION PROCEDURE TO SOLVE THE NONCONVEX ECONOMIC DISPATCH PROBLEM WITH GENERATOR CONSTRAINTS , 2005 .

[16]  Junita Mohamad-Saleh,et al.  Enhanced probability-selection artificial bee colony algorithm for economic load dispatch: A comprehensive analysis , 2014 .

[17]  L. Coelho,et al.  Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect , 2006, IEEE Transactions on Power Systems.

[18]  Waree Kongprawechnon,et al.  Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints , 2008 .

[19]  A. A. El-Keib,et al.  Environmentally constrained economic dispatch using the LaGrangian relaxation method , 1994 .

[20]  Amir Hossein Alavi,et al.  Krill herd: A new bio-inspired optimization algorithm , 2012 .