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Performance assessment of two-timescale multi-objective volt/var optimization scheme considering EV charging stations, BESSs, and RESs in active distribution networks.

Authors :
Zamzam, Tassneem
Shaban, Khaled
Gaouda, Ahmed
Massoud, Ahmed
Source :
Electric Power Systems Research. Jun2022, Vol. 207, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• Two-timescale volt/var optimization that utilizes distributed energy resources. • Coordinating distributed energy resources along with utility-owned assets. • Engaging utility operator in the decision-making process. • Active distribution network with high distributed energy resources penetration. • Incorporate all resources and assets for enhanced network performance. The high penetrations of distributed energy resources of renewable energy sources, battery energy storage systems, and electric vehicles introduced several challenges to power networks. It can lead to high voltage variation, sudden over/under-power generation, high losses issues, and negatively impact distribution assets. Thus, there is a vital need for volt/var optimization schemes that integrate conventional volt/var devices with inverter-interfaced resources to overcome these challenges. This paper demonstrates a performance assessment of the volt/var optimization scheme utilizing different utility-owned assets and resources based on a two-timescale multi-objective algorithm. At the slow timescale, it utilizes capacitor banks and on-load tap changers to minimize system losses and maximize asset lifetime based on their conditions. The algorithm incorporates the utility operator's direct input for setting the conventional volt/var devices. The operation of these devices is optimized, in three steps, by limiting the number of switching operations based on the operator preferences. At the faster scale, it considers renewable energy sources, electric vehicle charging stations, and battery energy storage systems to be optimized to limit voltage variation and system losses further. The IEEE 33-bus distribution network is modified and used to demonstrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03787796
Volume :
207
Database :
Academic Search Index
Journal :
Electric Power Systems Research
Publication Type :
Academic Journal
Accession number :
155843584
Full Text :
https://doi.org/10.1016/j.epsr.2022.107843