AUTHOR=Jaisiva S. , Prabaakaran K. , Kumar C. , Lakshmanan M. , Alwabli Abdullah , Jaffar Amar , Alharbi Ayman , Miyajan Abdulaziz 

TITLE=A novel solution for the optimal reactive power dispatch problem using an artificial neural network integrated with the firefly optimization algorithm

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2023.1310010

DOI=10.3389/fenrg.2023.1310010

ISSN=2296-598X

ABSTRACT=This article highlights applying a novel intelligence technique for solving the power system issues faced daily. Compensation for reactive power is a significant issue faced by power system operators in research. The solution can be obtained by handling a multi-objective task and multi-constraints by reducing the active power loss and minimizing the voltage deviation at the load end. The novelty of the research focuses on integrating artificial neural network techniques with the novel optimization algorithm named firefly algorithm for attaining objective function. The Levenberg Marquardt Back Propagation algorithm is most suited for proper tuning of the control variables. The objective of this research can be attained by appropriate turning of control variables being connected with the IEEE test bus systems, which helps to improve the voltage profile to a maximum extent. The existing research studies have been focused on reactive power management, which is attained by solving This is a provisional file, not the final typeset article optimal reactive power flow problems employing Nature-inspired approach techniques such as Symbiotic Organism Search Algorithm, Cuckoo Search Algorithm, Black Hole Algorithm, Krill Herd algorithm, and Whale optimization. The evolving strategy, Firefly Algorithm (FFA), minimizes the multi-constraint functions more competently and effectively than any conventional algorithm. To showcase the strength of the AI-incorporated firefly algorithm, it is examined on the standard IEEE test bus system, namely as 14, 30, 118 bus network. The obtained results quantify the effectiveness of the proposed methodology, i.e., the artificial intelligence technique in implementing the firefly algorithm is more encouraging than other conventional methods.