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

Authors: Vatsala Sharma; Pratima Walde

Addresses: School of Electrical Electronics and Communication Engineering, Galgotias University, Greater Noida, Uttar Pradesh, 226001, India ' School of Electrical Electronics and Communication Engineering, Galgotias University, Greater Noida, Uttar Pradesh, 226001, India

Abstract: 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.

Keywords: congestion management; affectability factor; particle swarm optimisation; PSO; gravitational search algorithm; re-dispatch.

DOI: 10.1504/IJPEC.2022.125223

International Journal of Power and Energy Conversion, 2022 Vol.13 No.1, pp.1 - 23

Accepted: 26 Oct 2021
Published online: 02 Sep 2022 *

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