Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
Author
dc.contributor.author
Khasanov, Mansur
Author
dc.contributor.author
Kamel, Salah
Author
dc.contributor.author
Rahmann Zúñiga, Claudia Andrea
Author
dc.contributor.author
Hasanien, Hany M.
Author
dc.contributor.author
Al-Durra, Ahmed
Admission date
dc.date.accessioned
2022-01-07T14:28:07Z
Available date
dc.date.available
2022-01-07T14:28:07Z
Publication date
dc.date.issued
2021
Cita de ítem
dc.identifier.citation
IET Gener. Transm. Distrib. 2021;15:3400–3422
es_ES
Identifier
dc.identifier.other
10.1049/gtd2.12230
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/183472
Abstract
dc.description.abstract
This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass-based Distributed Generation (DG) units in distribution systems (DS). The main objective function is to minimize the total power and energy losses. Power loss-sensitivity factor (PLSF) is used with the ROA to determine the suitable candidate buses and accelerate the solution process. The Weibull and Beta probability distribution functions (PDF) are employed to characterize the variability of wind speed and solar radiation, respectively. The high penetration of intermittent renewable resource together with demand variations has introduced many challenges to distribution systems such as power fluctuations, voltage rise, high losses, and low voltage stability, therefore battery energy storage (BES) and dispatchable Biomass are considered to smooth out the fluctuations and improve supply continuity. The standard 33 and 69-bus test systems are used to verify the effectiveness of the proposed technique compared with other well-known optimization techniques. The results show that the developed approach accelerates to the near-optimal solution seamlessly, and in steady convergence characteristics compared with other techniques.
es_ES
Patrocinador
dc.description.sponsorship
National Research and Development Agency of Chile (ANID) ANID/Fondap/15110019
es_ES
Lenguage
dc.language.iso
en
es_ES
Publisher
dc.publisher
Wiley
es_ES
Type of license
dc.rights
Attribution-NonCommercial-NoDerivs 3.0 United States