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首页> 外文会议>2010 International Symposium on Computer Communication Control and Automation >A preventive security-constrained optimal power flow with hybrid genetic-ant colony optimization
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A preventive security-constrained optimal power flow with hybrid genetic-ant colony optimization

机译：混合遗传-蚁群优化的安全约束预防性最优潮流

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This paper presents preventive security-constrained optimal power flow (PSCOPF) with hybrid genetic-ant colony optimization (HGACO) is presented The PSCOPF can be divided into three steps involving security analysis, severest event selection, and preventive algorithm. First, Novel security analysis will be conducted before fault occurred in the system by current-based power flow technique. Second, ranking method will be used to highlight the most severe event caused by the specific facility. And finally, a preventive algorithm will make use of the contingency information, and could be kept the operator system security and avoided congestion when fault occurred. The HGACO is integrated with genetic algorithm and ant colony optimization, and the objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence.
机译：本文提出了具有混合遗传-蚁群优化（HGACO）的预防性安全约束最优潮流（PSCOPF）。PSCOPF可以分为安全性分析，最严重事件选择和预防性算法三个步骤。首先，将通过基于电流的潮流技术在系统发生故障之前进行新颖的安全性分析。其次，将使用排名方法来突出显示由特定设施导致的最严重事件。最后，一种预防性算法将利用应变信息，并可以保证操作员系统的安全性并避免发生故障时的拥塞。 HGACO与遗传算法和蚁群优化相结合，GA的目的是通过自身优化以提高蚂蚁的搜索质量，从而产生更好的结果，因为信息素过程随机产生的蚂蚁并不一定更好。该方法不仅可以增强邻域搜索，而且可以快速搜索最优解以促进收敛。

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