Issue |
E3S Web Conf.
Volume 434, 2023
4th International Conference on Energetics, Civil and Agricultural Engineering (ICECAE 2023)
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Article Number | 01016 | |
Number of page(s) | 11 | |
Section | Energetics | |
DOI | https://doi.org/10.1051/e3sconf/202343401016 | |
Published online | 12 October 2023 |
Optimal Sizing and Sitting of Distributed Generation in Distribution Network considering Power Generation Uncertainty
1 Tashkent State Technical University, 100095 Tashkent, Uzbekistan
2 Department of Electrical Engineering, Faculty of Engineering, Aswan University, 81542 Aswan, Egypt
3 Department of Electrical Engineering, University of Jaen, 23700 EPS Linares, Jaen, Spain
4 Department of Energy, Faculty of Energy and radio electronics, Jizzakh Polytechnic Institute, Jizzakh, Uzbekistan
* Corresponding author: hasanov6654525@mail.ru
This paper presents an application of the recent metaheuristic Geometric Mean Optimizer (GMO) for the allocation of renewable energy sources (RES), including wind turbine (WT) and biomass-based Distributed Generation (DG) units in the distribution network (DN). The primary objective function is to minimize the total power and energy losses. The Weibull probability distribution function (PDF) is employed to describe the uncertainty of wind speed. The high penetration of RES with intermittent availability and demand variations has introduced many challenges to DN, such as power fluctuations, voltage rise, high losses, and low voltage stability. Therefore, the use of dispatchable biomass is considered to smooth out supply fluctuations and maintain supply continuity. A standard IEEE 69-bus test system is used to verify the performance of the proposed approach. The simulation results and comparison with other techniques demonstrate the significant energy loss reduction achieved by the proposed technique.
© The Authors, published by EDP Sciences, 2023
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