Enhancing efficiency in electrical distribution systems: A novel approach via modified genetic optimization algorithm for loss reduction in optimal network distribution

Article type: Research Article

Authors: Rajalakshmi, K.^{a; *} | Priyan, S. Vishnu^b | Inbakumar, J. Parivendhan^a | Kumar, C.^c

Affiliations: [a] Department of Robotics and Automation, Kings Engineering College, Chennai, India | [b] Department of Biomedical Engineering, Kings Engineering College, Chennai, India | [c] Department of Electronics and Communication Engineering, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

Correspondence: [*] Corresponding author. K. Rajalakshmi, Department of Robotics and Automation, Kings Engineering College, Chennai, India. E-mail: [email protected].

Abstract: The distribution system plays a pivotal role in connecting power generation sources to vital facilities like nuclear reactors. In this intricate network, losses occur while supplying electricity, demanding a reduction for enhanced performance. The quality of power reaching the nuclear plant is imperative due to the susceptibility of sensitive equipment to poor power conditions. This study presents a reconfiguration strategy to bolster dependability and curtail power losses in distribution networks. Leveraging the Modified Genetic Optimization Algorithm (MGOA), the reconfiguration conundrum is tactfully addressed to determine optimal switch operation schemes. The MGOA-based reconfiguration not only minimizes energy wastage but also refines voltage profiles, elevating operational efficiency. The effectiveness of this approach is substantiated through its successful application to radial distribution systems comprising 33, 69, and 136 buses. Embracing diverse scenarios encompassing normal and abnormal operating states, as well as varying loads, the method’s robustness is showcased. The validity of the proposed methodology is reinforced by comprehensive simulation results, underscoring its reliability and potential for real-world implementation.

Keywords: Distribution network reconfiguration, genetic algorithm firework algorithm, runner-root model, fuzzy shuffled frog-leaping algorithm, grey wolf optimizer and PSO method

DOI: 10.3233/JIFS-233917

Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3577-3591, 2024