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This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper...
This paper presents a fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solving the large economic power dispatch with non-smooth cost fuel functions. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules, the adaptive PSO executed in parallel based in decomposed network procedure as a local search...
Economic power dispatch problem plays an important role in the operation of the power systems. It is a method of determine the most efficient, low cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. The primary objective of economic dispatch is to minimize the total cost of generation while maintaining the operational...
It is an important measure to carry out energy-saving power generation scheduling in China to achieve energy saving. And how to implement policies of energy-saving emission reduction and to realize coordinated and orderly scheduling has become an important topic to the network operator. Based on the basic model of economic dispatch and energy-efficient power generation scheduling rules, the multi-objective...
This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called hybrid particle swarm optimization - differential evolution (PSO-DE). The mutation operators...
This paper presents an Efficient and Reliable Particle Swarm Optimization (RPSO) method for solving the Optimal Power Flow (OPF) of large distribution system solution for Combined Economic Emission Dispatch Problem (CEEDP).The objective is to minimize the total fuel cost of the generating units having quadratic cost characteristics subjected to limits on generator True/Active /Real and Reactive Power...
This paper proposes a new evolutionary approach named as multi agent particle swarm optimization (MAPSO) algorithm for solving economic dispatch with security constraints (line flow and bus voltage). This method integrates multiagent systems (MAS) and particle swarm optimization (PSO) to form a new algorithm, multiagent particle swarm optimization algorithm. In MAPSO, an agent represents a particle...
The rational economic load dispatch can not only save the energy, but also improve efficiency of power systems, so it is important to research economic load dispatch problem. However, duo to its complex and nonlinear characteristics, it is difficult to solve the problem using traditional optimization method. PSO has been successfully applied to a wide range of applications, in solving continuous nonlinear...
This paper introduced a genetic particle evolutionary swarm optimization (GPESO) for solving the economic dispatch (ED) in power systems. GPESO is based on the genetic particle swarm optimization (GPSO). GPSO was derived from the original particle swarm optimization (OPSO), which was incorporated with the genetic reproduction mechanisms, namely crossover and mutation. To enhance the search performance...
This paper presents particle swarm optimization (PSO) technique to solve economic dispatch of valve-point loaded generating units considering emission constraint. This problem has gained recent attention due to the deregulation of power industry and environmental regulations. Minimizing operating cost can no longer be the only criterion for dispatching electric power due to increasing concern over...
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