Doctor of Philosophy
School of Electrical, Computer and Telecommunications Engineering
Electric vehicles (EVs) are increasingly envisioned as a promising alternative for conventional transport systems because of their economic and environmental advantages and technological enhancements. However, the integration of EVs, the charging stations and other types of electric transport systems can result in a significant increase in the electric load demand in power grids. Moreover, because of the atypical aspects of the EVs and other types of electric vehicular systems, additional power quality issues can arise in the power grids. A thorough investigation is required to determine the optimal capacity of the electrical networks so that the high penetration of EVs in the distribution systems will not violate the grid codes and standards. Further, solutions need to be devised to facilitate the integration of EVs in distribution networks and suitable methods need to be developed to allow the EVs to support the power grids when connected.
In this research project, a comprehensive study of the existing and potential impacts of EVs on power systems at medium voltage (MV) and low voltage (LV) levels are carried out using computer simulations and field measurements. Models, which can replicate the characteristics of the EVs when integrated into the distribution power systems and the analysis of the interaction between the EVs and the power systems components, are also developed. Most importantly, approaches for the effective participation and the optimal integration of EVs and demand management schemes are designed so that the codes and standards for power quality of the grids can be satisfactorily met. Accordingly, new control strategies are developed to effectively and efficiently operate the distribution systems under uncertainties, varying system conditions, and the types and applications of the EVs.
Zahedmanesh, Arian, Optimal Management of Vehicle-to-Grid and Grid-to-Vehicle Services Considering Reliability and Power Quality Constraints, Doctor of Philosophy thesis, School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, 2021. https://ro.uow.edu.au/theses1/1082
This thesis is unavailable until Wednesday, January 12, 2022
Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.