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Title: | An open tool for creating battery-electric vehicle time series from empirical data, emobpy |
Authors: | Morales, Gaete |
Keywords: | pin-điện từ; emobpy; dữ liệu; thực nghiệm; công cụ mở; chuỗi thời gian |
Issue Date: | 2021 |
Publisher: | EconStor |
Abstract: | There is substantial research interest in how future feets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses.they depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricity consumption, grid availability, or grid electricity demand. as the availability of such data is highly limited, we introduce the open-source tool emobpy. Based on mobility statistics, physical properties of battery-electric vehicles, and other customizable assumptions, it derives time series data that can readily be used in a wide range of model applications. For an illustration, we create and characterize 200 vehicle profles for Germany. Depending on the hour of the day, a feet of one million vehicles has a median grid availability between 5 and 7 gigawatts, as vehicles are parking most of the time. Four exemplary grid electricity demand time series illustrate the smoothing efect of balanced charging strategies. |
URI: | http://dlib.hust.edu.vn/handle/HUST/23656 |
Link item primary: | https://www.econstor.eu/handle/10419/235851/ |
Appears in Collections: | OER - Kỹ thuật điện; Điện tử - Viễn thông |
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