基于启发式遗传算法的电力系统应急选择与静态安全增强

Ahlada Sudersan, Mohamed Abdelrahman, Ghadir Radman
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引用次数: 32

摘要

本文提出了一种识别关键双线中断并通过使用启发式遗传算法(GA)优化放置FACTS设备来增强静态安全性的技术。有两个指标用于应急筛选:基于线路溢出的双线应急指数(DCI)和基于母线电压违规的电压敏感指数(VSI)。将偶然性筛选作为主要的优化问题,其目标是找到所有具有最大DCI和VSI的双线中断。安全增强被视为一个有约束的二次优化问题。目标是减少通过系统分支的传输损耗,减少或消除目前的溢流和电压违例。对于所有母线和支路,各母线处的电压幅值和通过各支路的线路流量被认为是不等式和等式约束。采用ieee14总线和ieee30总线系统对该技术进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contingency selection and static security enhancement in power systems using heuristics-based genetic algorithms
This paper proposes a technique to identify critical double-line outages and enhance static security by optimal placement of FACTS devices using heuristics-based genetic algorithm (GA). Two indices have been used for contingency screening: double-line contingency index (DCI), based on line overflows, and voltage sensitivity index (VSI), based on bus voltage violations. Contingency screening is treated as the primary optimization problem with an objective of finding all double-line outages with maximal DCI and VSI. Security enhancement is treated as a constrained secondary optimization problem. The objective is to reduce transmission losses through the branches of the system and reduce or remove the overflows and voltage violations present. The voltage magnitude at each bus and the line flow through each branch for all the buses and branches have been considered as inequality and equality constraints. The technique is demonstrated using IEEE 14 bus and IEEE 30 bus systems.
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