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Passive congregation based particle swam optimization (pso) with self-organizing hierarchical approach for non-convex economic dispatch

机译:基于被动会聚的粒子群优化(PSO)和自组织分层方法用于非凸经济调度

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This paper proposes a passive congregation based PSO with self-organizing hierarchical algorithm approach for solving the economic dispatch problem of power system, where some of the units have prohibited operating zones. This Algorithm is known to perform better than conventional gradient based optimization methods for non-convex optimization problems. Conventional PSO algorithm is a population based heuristic search, employing problem of premature convergence. In this work, an innovative approach based on the concept of passive congregation based PSO with self-organizing hierarchical approach is employed to overcome the problem of premature convergence in classical PSO method.
机译:提出了一种基于自聚集的PSO算法,采用自组织层次算法,解决了部分机组禁止运行区域的电力系统经济调度问题。对于非凸优化问题,该算法的性能要优于传统的基于梯度的优化方法。常规的PSO算法是一种基于种群的启发式搜索,它采用了过早收敛的问题。在这项工作中,采用了一种基于被动聚类的PSO概念和自组织分层方法的创新方法,以克服经典PSO方法中过早收敛的问题。

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