Abstract
This study attempts to fit daily travel distances (DTD) data collected from the Nagoya University (NU) car-sharing system for one year to several distribution functions, including a lognormal mixture model. It is deemed here that the lognormal distribution performs best among the five tested single-distribution functions based on their p-values. Moreover, the lognormal mixture model can represent the driving pattern better overall with respect to the Akaike information criterion (AIC). Taking two types of electric vehicles (EVs) into consideration, the results show that 30 out of 48 vehicles can be substituted by the EV type with a larger battery capacity according to the observed DTD data and when a 95% confidence level is considered. In this exercise, the updated car-sharing system can have up to nine available vehicles at peak hour, which can reach the peak-shaving need and provides the possibility of contributing electricity for common use with the help of the vehicle-to-grid (V2G) system. Additionally, the updated system with a larger battery capacity can also reduce 24% of the CO2 emissions. These types of systems could be widely applied to other organizations or companies in the consideration of electricity consumption and emission reduction.
Highlights
Effort has been made for the reduction of CO2 emissions as well as energy saving
Two statistical measures are adopted in this study to evaluate the goodness of fit of each distribution and lognormal mixture model: p-value estimated by the Kolmogorov–Smirnov test (K–S test) [19] is used here to determine whether the daily travel distances (DTD) of a certain vehicle is subject to a certain distribution form with a 95% confidence level
Since the goal of this study is to find the distribution model that best fits DTD, we compare the magnitude of the Akaike information criterion (AIC) of each distribution model and vehicle instead of considering a p-value with a certain confidence level
Summary
Effort has been made for the reduction of CO2 emissions as well as energy saving. EVs described by Smith et al [1] are seen as having potential for reducing oil dependency and Greenhouse Gas (GHG) emissions in transportation use. This has been confirmed by Casals et al [2], who examined emissions changes between internal combustion engine vehicles and EVs, and suggested that some countries (e.g., France or Norway) are better suited for EV adoptions. If conventional vehicles are shifted to EVs, they can serve as an energy resource by sending electricity back into the grid under the help of a vehicle-to-grid system (V2G), and that will lower the electric system costs [4,5,6]
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