A novel optimisation technique based on swarm intelligence for congestion management in transmission lines

被引:2
|
作者
Sharma V. [1 ]
Walde P. [1 ]
机构
[1] School of Electrical Electronics and Communication Engineering, Galgotias University, Uttar Pradesh, Greater Noida
关键词
affectability factor; congestion management; gravitational search algorithm; particle swarm optimisation; PSO; re-dispatch;
D O I
10.1504/ijpec.2022.125223
中图分类号
学科分类号
摘要
In this manuscript, a novel and unique optimisation technique is incorporated with combination of an improved particle swarm optimisation technique and an improved gravitational search algorithm (IPSO-IGSA) to get over with the congestion problem in transmission lines. The problem of transmission line congestion is alleviated by using the affectability factor concept for optimal rescheduling of the generators' active power. The generators having high affectability factor value would be picked-up for rescheduling their active power. The main perspective is to minimise the total re-dispatching power, which ultimately reflects in the all over rescheduling cost that may not be, discouraged the market participants also. The combined IPSO-IGSA has been implemented on both IEEE-30-bus framework as well as IEEE-118-bus framework. The graphs and statistical results obtained clearly show that the proposed technique is capable of solving the congestion problem more efficiently with faster convergence capability and also reduced congestion cost. © 2022 Inderscience Enterprises Ltd.
引用
收藏
页码:1 / 23
页数:22
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