期刊
SUSTAINABLE ENERGY GRIDS & NETWORKS
卷 23, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.segan.2020.100375
关键词
Charging Station (CS); Electric Vehicle (EV); Queuing theory; Uncertainty
With the increasing influence of renewable resources and Electric Vehicles (EVs) on the distribution grids, one of the issues that may trouble the designers and beneficiaries of the systems is the contingent nature of the output power of these elements. In the present paper, it is attempted to determine the capacity and the candidate locations for installing the renewable resource, Fast Charging Stations (FCSs), and power switches in such a way that the entire grid can be clustered as multiple active interconnected Micro-Grids (MGs). In this regard, to investigate the uncertainty of the renewable resources, load, and the FCSs in the present work, the Monte Carlo method, the UETAM model, and the queueing theory were used to produce the uncertainty scenarios. The objective functions assumed for solving this problem included the technical, economic, and environmental functions. Finally, the efficiency of the proposed method was evaluated on a sample IEEE 33-bus system and its corresponding Sioux Falls traffic network. After running the program described for the grid design, the Energy Not Supply (ENS) cost in the grid was 580.3 $ and the total cost reached the lowest value compared to other algorithms. Overall, the obtained results, after being aggregated using the risk-neutral probabilities method, indicated a significant reduction in the system's costs as well as the improvement of the technical status of the grid after applying the proposed method. (c) 2020 Elsevier Ltd. All rights reserved.
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