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This paper proposes a version of fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solve large nonconvex economic dispatch problems. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules to adjust dynamically the three parameters associated to PSO mechanism search. The adaptive PSO executed in...
This paper presents an application of Bees Algorithm (BA) for solving various types of Economic Dispatch (ED) problem. Complete ED problem formulation prohibited, operating zones, ramp-rate limits, and non-smooth or non-convex cost functions arising from the use of multiple fuels should be taken into consideration. To show its efficiency, the Bee algorithm is applied to solve various types ED problems...
This paper presents a new efficient approach to economic dispatch (ED) problems with smooth and non smooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this paper a modified random...
In this paper, an improved genetic algorithm is proposed to solve the economic dispatch (ED) problem with valve point loading effects. The proposed algorithm reduces the dimension of the search space in a certain way such that it is less time consuming. The evolutionary algorithm is proved to be efficient in solving the economic dispatch problem. Furthermore, it provides a suitable framework for future...
This paper proposed the use of a new constraint-preserving method (NCPM) to solve the nonconvex economic dispatch (NED) with linear constraint problems. NCPM always generates feasible solutions every time that reduces the search space (exclude the infeasible domain) to enhance the probability of obtaining the global optimum. Based on the benchmark of the same objective function, NCPM was compared...
Aiming at enhancing the diversity of the traditional particle swarm optimization (PSO) algorithm, this paper proposes a method of combining the conventional PSO algorithm with Gaussian mutation (GM) operator to enhance the global search capability and investigate the performance of the proposed hybrid PSO-GM algorithm, while solving the economic dispatch (ED) problem considering non-smooth cost functions...
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