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New genetic algorithms for contingencies selection in the static security analysis of electric power systems

机译:电力系统静态安全分析中突发事件选择的新遗传算法

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The importance of a reliable supply of electric power in industrial society is unquestionable. In control centers of electrical utilities, an important task is the security analysis, even for those companies that already have the modern smart grids. In this task, a contingency is the operation outage of one or more devices, while contingencies selection is the determination of the most severe contingencies on the system. Despite the current technological advances, an analysis of all possible contingencies is impracticable. In this paper, a method to efficiently perform the selection of multiple contingencies is presented. The issue is modeled as a combinatorial optimization problem and solved by genetic algorithms, developed for this application. A robust method, which considers power flow and voltage, is presented and tested over IEEE-30 test system and over a large real life system, considering double outages of branches. The results showed accuracy close to 100%, when compared with an exact method.
机译:毫无疑问,可靠的电力供应在工业社会中至关重要。在电力公司的控制中心,重要的任务是安全分析,即使对于那些已经拥有现代智能电网的公司而言。在此任务中,突发事件是一个或多个设备的运行中断,而突发事件选择是确定系统上最严重的突发事件的方法。尽管当前有技术上的进步,但对所有可能的意外情况进行分析是不可行的。在本文中,提出了一种有效地进行多种意外事件选择的方法。该问题被建模为组合优化问题,并通过针对该应用开发的遗传算法解决。提出了一种考虑潮流和电压的鲁棒方法,并在IEEE-30测试系统和大型现实生活系统中进行了测试,同时考虑了分支的两次中断。与精确方法相比,结果显示准确性接近100%。

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