Abstract
Electric vehicles (EVs) have become widespread during the last decade because of the distinct advantages they offer compared to the conventional ones. However, the increased penetration of EVs in the global transportation market has led increased electricity demands, which is expected to affect the operation of energy distribution systems. In the present paper, a demonstration about the effects of uncontrolled EVs charging in a case study low voltage (LV) network is demonstrated and a fuzzy energy management strategy for the coordination of EV charging in LV networks is presented, by including the distance of the EVs from the transformers in the fuzzy management systems for the first time. The Institute of Electrical and Electronics Engineers (IEEE) European Test Feeder is used as a case study low voltage distribution grid. In particular, the developed system configuration takes into consideration the architecture of the grid, the ampacities of the lines and the voltages at the system’s buses. Moreover, electric vehicles are considered as agent-based models, which are characterized by the model of each EV, the state-of-charge of their batteries and the charging power. In particular, an investigation into the effects of uncontrolled charging is performed, in which two approaches are examined. The first approach investigates the maximum number of chargeable EVs in the case study network and how it is influenced by the grid’s household loads. The second approach examines the number of network undervoltages and lines ampacity violations in a set of simulation scenarios. The results of the first approach show that the distance of the EVs from the networks substation affects the maximum number of chargeable EVs in a significant manner. Based on the observed results of the two approaches, a fuzzy management system is designed for the coordination of EV changing, which takes into account the distance from the EV charging points to the feeder substation, the state-of-charge of the EVs’ batteries and the EVs’ charging delay time.
Highlights
The world’s transportation and electric power generation sectors are the major consumers of fossil fuels, resulting in high carbon dioxide emissions and an energy supply crisis [1]
The present paper demonstrates the effects of uncontrolled charging of electric vehicles (EVs) in low voltage distribution grids, in order to solve them by presenting a fuzzy-based centralized energy management system, which has been developed and investigated for the coordination of EV charging in such networks
The results clearly show that the enable of the distance as a parameter in the Fuzzy Logic Controller (FLC) affects the in Figures 25a–c it is shown that FLC+ allocates the charging times of EVs, better than charging behavior of the EVs in a positive way
Summary
The world’s transportation and electric power generation sectors are the major consumers of fossil fuels, resulting in high carbon dioxide emissions and an energy supply crisis [1]. The formulation of the optimization problem takes into consideration the behavior of the network and decides the charging power of each charging EV, by minimizing the EVs’ charging costs [27] Another approach, based on LP, introduces a real time energy management system for EV charging, which defines the charging priority of EVs and the dynamic regulation of the grid’s voltage [28]. The present paper demonstrates the effects of uncontrolled charging of EVs in low voltage distribution grids, in order to solve them by presenting a fuzzy-based centralized energy management system, which has been developed and investigated for the coordination of EV charging in such networks. The proposed fuzzy-based controller considers the SoC of each EV, the distance of each EV management system was developed for the coordination of EV charging, with respect to the grid’s from the substation and the charging delay time, in order to determine the priority of each EV in the constraints. Discussed, along with some directions of future research work
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