An Intelligent Algorithm an Approach for Distribution System Solution

P. Ravi Babu, D. Naik, Sai Charith, Seshadri Nagajyothi

2023

Abstract

The minimum loss reconfiguration trouble in radial distribution networks is one of the complex combination optimizations because it is difficult to accurately determine the open sectionalizing switches for the given network. The genetic algorithm serves best to achieve configurations with optimal actual losses in the test system. The proposed method can easily handle any complex system for an optimal reconfigured network. Through genetic algorithms, the paper primarily focuses on active losses and voltage drops. The test system calculations confirm the validity and productivity of the proposed methodology. The numerical results of the IEEE 33 bus test system are obtained through a MATLAB program

Paper Citation

in Harvard Style

Ravi Babu P., Naik D., Charith S. and Nagajyothi S. (2023). An Intelligent Algorithm an Approach for Distribution System Solution. In Proceedings of the 1st International Conference on Intelligent and Sustainable Power and Energy Systems - Volume 1: ISPES; ISBN 978-989-758-689-7, SciTePress, pages 155-160. DOI: 10.5220/0012534800003808

in Bibtex Style

@conference{ispes23,
author={P. Ravi Babu and D. Naik and Sai Charith and Seshadri Nagajyothi},
title={An Intelligent Algorithm an Approach for Distribution System Solution},
booktitle={Proceedings of the 1st International Conference on Intelligent and Sustainable Power and Energy Systems - Volume 1: ISPES},
year={2023},
pages={155-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012534800003808},
isbn={978-989-758-689-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Intelligent and Sustainable Power and Energy Systems - Volume 1: ISPES
TI - An Intelligent Algorithm an Approach for Distribution System Solution
SN - 978-989-758-689-7
AU - Ravi Babu P.
AU - Naik D.
AU - Charith S.
AU - Nagajyothi S.
PY - 2023
SP - 155
EP - 160
DO - 10.5220/0012534800003808
PB - SciTePress