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Optimal Sizing and Sitting of Distributed Generation in Distribution Network considering Power Generation Uncertainty

Authors :
Khasanov Mansur
Kamel Salah
Jurado Francisco
Kurbanov Abror
Jalilov Urinboy
Source :
E3S Web of Conferences, Vol 434, p 01016 (2023)
Publication Year :
2023
Publisher :
EDP Sciences, 2023.

Abstract

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.

Subjects

Subjects :
Environmental sciences
GE1-350

Details

Language :
English, French
ISSN :
22671242
Volume :
434
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.321e196bd3374308902752fdc12bd425
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202343401016