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A new approach to the solution of Economic Dispatch using Particle SwarmOptimization is presented. It is the progression of allocating productionamongst the dedicated units such that the restriction forced are fulfilled andthe power needs are reduced. More just, the soft computing method has receivedsupplementary concentration and was used in a quantity of successful andsensible applications. Here, an attempt has been made to find out the minimumcost by using Particle Swarm Optimization Algorithm using the data of threegenerating units. In this work, data has been taken such as the losscoefficients with the max-min power limit and cost function. PSO and SimulatedAnnealing are functional to put out the least amount for dissimilar energyrequirements. When the outputs are compared with the conventional method, PSOseems to give an improved result with enhanced convergence feature. All themethods are executed in MATLAB environment. The effectiveness and feasibilityof the proposed method were demonstrated by three generating units case study.Output gives hopeful results, signifying that the projected method ofcalculation is competent of economically formative advanced eminence solutionsaddressing economic dispatch problems.

A New Approach to the Solution of Economic Dispatch Using Particle Swarm Optimization with Simulated Annealing