Issue |
E3S Web Conf.
Volume 461, 2023
Rudenko International Conference “Methodological Problems in Reliability Study of Large Energy Systems“ (RSES 2023)
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Article Number | 01053 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/e3sconf/202346101053 | |
Published online | 12 December 2023 |
Distribution network planning with DG units considering the network reconfiguration and reliability
1 Tashkent State Technical University named after Islam Karimov, 100095, Uzbekistan, Tashkent, University St. 2A
2 Department of Energy, Jizzakh Polytechnic Institute, 130100 Jizzakh, Uzbekistan
3 Department of Electrical Engineering, Faculty of Engineering, Aswan University, 81542 Aswan, Egypt
4 Zhuzhou Even Control Science and Technology Development Co. Ltd, 410000 Changsha, China
* Corresponding author: hasanov6654525@mail.ru
The failure statistics of most utilities show that distribution networks (DN) make the most considerable individual contribution to the lack of supply to consumers. There are several advantages to optimizing distributed generation (DG) allocation in DNs, including loss reduction, voltage profile improvements, and reliability. A traditional objective function of optimal DG allocation is to minimize the total power loss and improve the voltage profile. Due to their ability to supply loads locally, DG units enhance the load-carrying capability of lines and, therefore, serve the same purpose as redundant lines. A DN’s reliability indices can also be improved by optimal DG allocation. As such, it is interesting to investigate how network reconfiguration (NR) may be further enhanced to improve the achievement of these critical objectives and ensure the system’s efficient operation in this context. The purpose of this paper is to present an intensive investigation of the reliability and performance improvement that NR can achieve when using DG units in modern DNs. An efficient metaheuristic rider optimizer algorithm (ROA) is applied to the complex combinatorial NR and DG allocation problem with stringent constraints. Analyses are conducted on benchmark IEEE 33-bus test DNs with explicit presentation of results.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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