Abstract—A Hybrid NEURO-EPSO algorithm for solving Economic Load Dispatch Problem (ELD) with non-smooth cost function is presented in this paper. The ELD problem is a highly constrained, large scale, non-linear optimization problem, considering the equality and the inequality constraints. To demonstrate the effectiveness of the proposed algorithm, it is applied to test ELD problem with non-smooth cost function while considering the Valve-Point loading effect. Here we employ an Efficient PSO technique and the Back Propagation Algorithm(NN) to solve the ELD problem, so that faster convergence and more optimized results are obtained compared to other optimization techniques.

Index Terms—Economic Load Dispatch, Effificient Particle swarm optimization, Neural networks.

First S Dhayanand is a Final year electrical engineering student of V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, Tamil Nadu, India.(Mobile: +91 98947 40059)
Second N Dhyanesh is a Final year electrical engineering student of V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, Tamil Nadu, India.(Mobile: +91 99525 12765)
Third K S Harshni is a Final year electrical engineering student of V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, Tamil Nadu, India.(Mobile: +91 99440 48470)
Fifth S Muthu Vijaya Pandian is a Lecturer in V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, Tamil Nadu, India.(Mobile: +91 98652 59633)
Fourth T Nanda Kumar is a Final year electrical engineering student of V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, Tamil Nadu, India.(Mobile: +91 97866 75470

Cite: S. Dhayanand, N Dhyanesh, K. S. Harshni, S. Muthu Vijaya Pandian, T. Nandakumar, and K. Thanushkodi, "A Hybrid Neuro-Efficient Particle Swarm Optimization (EPSO) Algorithm for Economic Load Dispatch Considering Transmission Losses with Non-Smooth  and  Smooth  Cost  Function,"  International  Journal  of  Computer  and
Electrical Engineering vol. 1, no. 2, pp. 204-212, 2009.