Please use this identifier to cite or link to this item: https://hdl.handle.net/10953/2942
Title: Optimal Incorporation of Photovoltaic Energy and Battery Energy Storage Systems in Distribution Networks Considering Uncertainties of Demand and Generation
Authors: Abdel-Mawgoud, Hussein
Kamel, Salah
Tostado-Véliz, Marcos
Elattar, Elhab E.
Jurado-Melguizo, Francisco
Abstract: In this paper, the Archimedes optimization algorithm (AOA) is applied as a recent metaheuristic optimization algorithm to reduce energy losses and capture the size of incorporating a battery energy storage system (BESS) and photovoltaics (PV) within a distribution system. AOA is designed with revelation from Archimedes’ principle, an impressive physics law. AOA mimics the attitude of buoyant force applied upward on an object, partially or entirely dipped in liquid, which is relative to the weight of the dislodged liquid. Furthermore, the developed algorithm is evolved for sizing several PVs and BESSs considering the changing demand over time and the probability generation. The studied IEEE 69-bus distribution network system has different types of the load, such as residential, industrial, and commercial loads. The simulation results indicate the robustness of the proposed algorithm for computing the best size of multiple PVs and BESSs with a significant reduction in the power system losses. Additionally, the AOA algorithm has an efficient balancing between the exploration and exploitation phases to avoid the local solutions and go to the best global solutions, compared with other studied algorithms.
Keywords: Photovoltaic
BESS
Optimization
AOA algorithm
Uncertainty
Distribution network
Issue Date: Sep-2021
Publisher: MDPI
Citation: Abdel-Mawgoud, H.; Kamel, S.; Tostado-Véliz, M.; Elattar, E.E.; Hussein, M.M. Optimal Incorporation of Photovoltaic Energy and Battery Energy Storage Systems in Distribution Networks Considering Uncertainties of Demand and Generation. Appl. Sci. 2021, 11, 8231. https://doi.org/10.3390/app11178231
Appears in Collections:DIE-Artículos

Files in This Item:
File Description SizeFormat 
applsci-11-08231-v2.pdf14,32 MBAdobe PDFView/Open


This item is protected by original copyright