Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Optimal Location of Facts Devices in IEEE 14 Bus System Using Ga and Deiwo

Version 1 : Received: 26 May 2023 / Approved: 30 May 2023 / Online: 30 May 2023 (04:32:45 CEST)

How to cite: CHETHAN, M.; K, R. Optimal Location of Facts Devices in IEEE 14 Bus System Using Ga and Deiwo. Preprints 2023, 2023052040. https://doi.org/10.20944/preprints202305.2040.v1 CHETHAN, M.; K, R. Optimal Location of Facts Devices in IEEE 14 Bus System Using Ga and Deiwo. Preprints 2023, 2023052040. https://doi.org/10.20944/preprints202305.2040.v1

Abstract

FACTS devices provide significance to enhance the functioning of both static and dynamic power systems. The type, size, and location of FACTS devices determine how well they achieve the goals of enhancing voltage stability, loadability, and loss minimization simultaneously. The aim of the function in this study includes voltage stability, line loadings, and loss minimization, which are expected to obtain the most benefits from their installation and other weights allocated to them. It has been determined how installing TCSC, and SVC will improve loadability under situations of continuously increasing load. In this study, a novel optimization technique known as differential evolution invasive weed optimization (DEIWO) is utilized to locate the optimal location for FACTS devices within the IEEE 14 bus system by considering valve point effects. DEIWO was a recently developed, dominant, and simple metaheuristic algorithm for genuine parameter optimization. DEIWO was inspired by the natural process of weed colonization and dissemination, and it is highly effective at addressing broad multi-dimensional, linear and nonlinear optimization problems. The proposed method was implemented in the IEEE 14 bus testing system. Different methods from the research papers have been used to compare and analyze the results. The results demonstrate the DEIWO algorithm's capability and show how it may be used in practice to locate FACTS devices in deregulated electricity networks in the most advantageous place. A comparison of the proposed process to existing algorithms found in the literature and implemented using traditional techniques reveals that it performs better in terms of precision and convergence

Keywords

Genetic algorithm; voltage sensitivity indices; loss sensitivity indices; voltage profiles; reactive power; active power; Differential evolution invasive weed optimization

Subject

Engineering, Electrical and Electronic Engineering

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