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首页> 外文会议>International conference on swarm, evolutionary, and memetic computing >Performance Study of a New Modified Differential Evolution Technique Applied for Optimal Placement and Sizing of Distributed Generation
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Performance Study of a New Modified Differential Evolution Technique Applied for Optimal Placement and Sizing of Distributed Generation

机译：一种新的改进的差分进化技术用于分布式发电最优布局和规模化的性能研究

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摘要

Determination of optimal placement and sizing of Distributed Generations (DGs) is one of the important tasks in power system operation. Several conventional as well as heuristics techniques like particle swarm optimization, differential evolution etc. have been applied to solve the problem. But one of the major drawback of these techniques are the improper selection of user defined parameters for optimal solution. Improper selection of the parameters may even lead to premature convergence. A new modified differential evolution technique based algorithm is proposed in this paper for the solution of optimal sizing and location of distributed generation to avoid premature convergence. The proposed algorithm is applied on IEEE 14 and 30 bus systems to verify its effectiveness. The results obtained by the proposed method are compared with other methods. It is found that the results obtained by the proposed algorithm are superior in terms of cost and losses.
机译：确定分布式发电装置（DG）的最佳布置和尺寸是电力系统运行中的重要任务之一。几种传统的启发式技术，例如粒子群优化，微分进化等已被应用来解决该问题。但是，这些技术的主要缺点之一是用户定义参数的选择不当，无法获得最佳解决方案。参数选择不当甚至可能导致过早收敛。提出了一种新的基于差分进化技术的改进算法，以解决分布式发电的最优规模和位置问题，避免过早收敛。该算法被应用在IEEE 14和30总线系统上，以验证其有效性。将该方法获得的结果与其他方法进行了比较。发现通过所提出的算法获得的结果在成本和损失方面是优越的。

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