Artificial Immune based Economic Load Dispatch with valve-point effect

Economic load dispatch (ELD) is one of the optimization problems in power systems. Economic Load Dispatch determines the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, while satisfying the load demand simultaneously. In this paper Artificial Immune System (AIS) optimization approach has been applied to solve the constrained Economic Load Dispatch with valve-point effect. The developed AIS based optimization technique used total cost of generation as the objective function and represented it as the affinity measure. For illustrative purposes, the proposed AIS based technique has been applied to various test cases (consisting of 3, 13 and 40 generating units) to validate its effectiveness. The developed AIS based optimization technique (both binary coded and decimal coded) has been thoroughly investigated by varying the population size. The results of the proposed AIS based optimization technique are compared with that of genetic algorithm (GA) based approach. The simulation results reveal that the developed technique is easy to implement and capable of finding feasible near global optimal solution. The results substantiate the robustness, fast convergence and efficiency of the proposed methodology.

[1]  Hiroyuki Mori,et al.  A genetic algorithm based approach to economic load dispatching , 1993, [1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems.

[2]  Z. M. Yasin,et al.  Artificial-immune-based for solving economic dispatch in power system , 2004, PECon 2004. Proceedings. National Power and Energy Conference, 2004..

[3]  K. Mun,et al.  An application of evolutionary computations to economic load dispatch with piecewise quadratic cost functions , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[4]  M. Rahli,et al.  Economic Dispatch using a Genetic Algorithm: Application to Western Algeria's Electrical Power Network , 2005, J. Inf. Sci. Eng..

[5]  S. C. Srivastava,et al.  A genetic algorithm based economic load dispatch solution for Eastern region of EGAT system having combined cycle and cogeneration plants , 1998, Proceedings of EMPD '98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137).

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

[7]  D. Dasgupta,et al.  Immunity-based systems: a survey , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[8]  June Ho Park,et al.  Economic load dispatch using evolutionary algorithms , 1996, Proceedings of International Conference on Intelligent System Application to Power Systems.

[9]  Yim-Shu Lee,et al.  Improved genetic algorithm for economic load dispatch with valve-point loadings , 2003, IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468).

[10]  Mimoun Younes,et al.  ECONOMIC POWER DISPATCH USING THE COMBINATION OF TWO GENETIC ALGORITHMS , 2006 .

[11]  R. Chakrabarti,et al.  Improved Fast Evolutionary Program for Economic Load Dispatch with Non-smooth Cost Curves , 2004 .

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

[13]  Manoj Kumar Tiwari,et al.  A clonal algorithm to solve economic load dispatch , 2007 .

[14]  C.-L. Chiang,et al.  Genetic-based algorithm for power economic load dispatch , 2007 .

[15]  F. Azuaje.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[16]  M. Younes,et al.  ECONOMIC POWER DISPATCH USING EVOLUTIONARY ALGORITHM , 2006 .

[17]  Samir Sayah,et al.  Using Evolutionary Computation to Solve the Economic Load Dispatch Problem , 2008 .