Economic dispatch based on optimal lambda using radial basis function network

Particle Swarm Optimization by Natural Exponent Inertia Weight for Economic load Dispatch

“…ECD with valve point loading effect and multiple fuel option (ECD-VPL-MF) [31,32]. Multiobjective formulation includes combined emission economic dispatch CEED [19,14,21], multi-area emission economic dispatch MAEED [29,30], power generation under different utilities [22].…”

“…Thus the conventional methods have failed to solve such problems as they are sensitive to initial estimates and converge into local optimal solution and computational complexity. Modern heuristic optimization techniques based on operational research and artificial intelligence concepts, such as simulated annealing [14][15], evolutionary programming [13] , genetic algorithm, tabu search [19][20], neural network, particle swarm optimization provides better solution. The PSO originally developed by Eberhart and Kennedy in 1995[25], is a population based stochastic algorithm.…”

“…For solving economic load dispatch various conventional methods like bundle method [3], non linear programming , mixed integer linear programming [4][5][6][7], dynamic programming [5], quadratic programming [6] , Lagrange relaxation method [8], network flow method [9], direct search method [10] are used to solve such problems. When compared with the conventional (classical) techniques [10][11], modern heuristic optimization techniques based on operational research and artificial intelligence concepts, such as evolutionary algorithms [12][13], simulated annealing [14,15], artificial neural networks [16][17][18], and taboo search [19,20] have been given attention by many researchers due to their ability to find an almost global optimal solution for ELD problems with operation constraints. ELD problem is non linear, non convex type with multiple local optimal point due to the inclusion of valve point loading effect, multiple fuel options with diverse equality and inequality constraints.…”

“…The primary objective of ELD is to schedule the committed generating units output so as to meet the required load demand at minimum cost satisfying all unit and system operational constraints. The optimal ELD should meet load demand, generation limit, ramp rate, prohibited operating zone, [1,2] [19,20] have been given attention by many researchers due to their ability to find an almost global optimal solution for ELD problems with operation constraints. ELD problem is non linear, non convex type with multiple local optimal point due to the inclusion of valve point loading effect, multiple fuel options with diverse equality and inequality constraints.…”

A SelfAdaptive Fuzzy Cmeans based Radial Basis Function Network to Solve Economic Load Dispatch Problems

“…This method solves the ELD with two types of iterations -first, the value of lambda is changed iteratively from its initial assumed value to the final optimal value; second, for every value of lambda chosen by trial, the power generated by the generating units have to be acquired using sub-iterations. Hence the subiterations have to be run several times leading to a time consuming job [ (Aravindhababu P. 2001)]. Over the years several efforts have been made to find optimized solutions to the ELD problem based on Artificial Intelligence such as Artificial Neural Networks, Fuzzy Logic, and Evolutionary Algorithms.…”