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Security constrained optimal power flow considering detailed generator model by a new robust differential evolution algorithm

机译:通过新的鲁棒差分进化算法,在考虑详细发电机模型的情况下,安全约束的最优潮流

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摘要

This paper presents a new multiobjective model, including two objective functions of generation cost and voltage stability margin, for optimal power flow (OPF) problem. Moreover, the proposed OPF formulation contains a detailed generator model including active/reactive power generation limits, valve loading effects, multiple fuel options and prohibited operating zones of units. Furthermore, security constraints, including bus voltage limits and branch flow limits in both steady state and post-contingency state of credible contingencies, are also taken into account in the proposed formulation. To solve this OPF problem a novel robust differential evolution algorithm (RDEA) owning a new recombination operator is presented. The proposed RDEA has a minimum number of adjustable parameters. Besides, a new constraint handling method is also presented, which enhances the efficiency of the RDEA to search the solution space. To show the efficiency and advantages of the proposed solution method, it is applied to several test systems having complex solution spaces and compared with several of the most recently published approaches.
机译:本文提出了一种新的多目标模型,该模型包括发电成本和电压稳定裕度这两个目标函数,用于最优潮流(OPF)问题。此外,拟议的OPF公式包含详细的发电机模型,包括有功/无功发电限值,阀门负荷效应,多种燃料选择和机组的禁止运行区域。此外,在提议的公式中还考虑了安全性约束,包括可信状态的稳定状态和事后状态中的母线电压限制和分支流量限制。为了解决这个OPF问题,提出了一种具有新的重组算子的新型鲁棒差分进化算法(RDEA)。拟议的RDEA具有最少数量的可调参数。此外,还提出了一种新的约束处理方法,可以提高RDEA搜索解空间的效率。为了显示所提出的解决方案方法的效率和优势,将其应用于具有复杂解决方案空间的几种测试系统,并与几种最新发布的方法进行了比较。

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