Localisation of facts compensator using reptile search algorithm for enhancing power system security under multi-contingency conditions

IF 1.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sumit Ramswami Punam, Sunil Kumar
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引用次数: 0

Abstract

Due to the improvement in power demand usage, the system causes more stress. Suitable placement of FACTS is introduced to improve power flows, stability, and power system security. An advanced optimal method has been introduced to resolve optimal power flow under various conditions. Five varied FACTS devices were positioned inside the power system to improve system safety at the least cost. Selecting the suitable location and size of FACTS device enabling high security and less cost was proposed using RSA. The objective functions were mitigated based on the RSA's inspiration to improve system security. The placement of the FACTS compensator was based on objective functions like LOSI, voltage deviation, real power loss, investment cost, sensitivity index, fuel costs, and constraints. The proposed model was validated under three conditions, namely generator outage, line outage, and both outage in IEEE 118 and IEEE 30 bus-systems. In the IEEE 30 bus system, TCSC provides better security of 1.4 severity at normal conditions and 1.3 severity in contingency conditions. In the IEEE 118 bus system, UPFC has less severity of 2.4 at normal conditions, and STATCOM has the least severity of 3 at contingency conditions. The proposed model provides enhanced security in all circumstances and reduces overall costs.

Abstract Image

基于爬行搜索算法的facts补偿器局部化增强多突发条件下电力系统的安全性
由于电力需求使用率的提高,该系统造成了更大的压力。引入了合适的FACTS布局,以改善电力流、稳定性和电力系统安全性。介绍了一种求解各种条件下最优潮流的先进优化方法。五种不同的FACTS设备被放置在电力系统内,以最低的成本提高系统安全性。提出了使用RSA来选择合适的FACTS设备的位置和大小,从而实现高安全性和低成本。基于RSA改进系统安全性的灵感,目标函数得到了缓解。FACTS补偿器的布置基于LOSI、电压偏差、实际功率损耗、投资成本、灵敏度指数、燃料成本和约束等目标函数。所提出的模型在三种条件下进行了验证,即发电机停运、线路停运以及IEEE 118和IEEE 30总线系统中的两种停运。在IEEE 30总线系统中,TCSC在正常条件下提供了1.4的严重性,在意外情况下提供了1.3的严重性。在IEEE 118总线系统中,UPFC在正常条件下的严重性较低,为2.4,而STATCOM在应急条件下的最不严重,为3。所提出的模型在所有情况下都提供了增强的安全性,并降低了总体成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cognitive Computation and Systems
Cognitive Computation and Systems Computer Science-Computer Science Applications
CiteScore
2.50
自引率
0.00%
发文量
39
审稿时长
10 weeks
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