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Combined Hybrid Differential Particle Swarm Optimization Approach for Economic Dispatch Problems

机译:求解经济调度问题的混合混合差分粒子群优化算法

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摘要

The economic dispatch problem is concerned with the optimal allocation of a load among different generatorsfor a given demand, minimizing fuel cost, emission, etc. This article presents a new, improved combined hybrid differential particle swarm optimization algorithm that combines hybrid differential evolution with particle swarm optimization for the solution of economic dispatch problems. This new algorithm combines the vibrancy and explorative nature of particle swarm optimization with the superior exploitative nature of hybrid differential evolution in such a manner that the merits of both remain intact. The results obtained are compared with a few other existing non-conventional methods, and the applicability and effectiveness of the proposed algorithm to power system optimization problems are indicated.
机译:经济调度问题涉及到在给定需求下不同发电机之间负载的最佳分配,最小化燃料成本,排放等。本文提出了一种新的,改进的混合混合差分粒子群优化算法,该算法将混合差分进化与粒子群相结合优化解决经济调度问题。这种新算法将粒子群优化的活力和探索性与混合差分进化的优越开发性相结合,从而使两者的优点保持不变。将获得的结果与其他一些现有的非常规方法进行比较,并指出了该算法在电力系统优化问题中的适用性和有效性。

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