Does the One-Size-Fits-All Setting Meet the Demand? Assessment of Setting Ev–Charging-Capable Parking Spaces in Public Parking Lots Based on Agent Simulation
Despite the rapid development of electric vehicles (EVs), the limited range and accessibility of charging infrastructure are still obstacles to the development of EVs. At present, the Chinese government has made great efforts to set up charging piles and the most popular construction mode of charging piles in China is to divide a certain proportion of parking spaces in the parking lot to build charge piles. The proportion for every parking lot is same and recommended by the government, which is a one-size-fits-all construction strategy. But with the growth of EVs, some challenges arise such as how to improve the accessibility of charging facility in hot parking lots. The current work addresses this challenge by correctly forecasting the charging demand of EVs based on simulation. In particular, in this paper, based on agent simulation technology, electric vehicle agent, fuel vehicle agent and parking lot agent are established to predict the charging demand and the Wulin business district of Hangzhou City is used as an example to predict the charging demand of nine public parking lots. Simulation results show that under the current number of EVs, this one-size-fits-all setting strategy can meet the demand with high accessibility. However, with the increasing of EVs, the spatial distribution of charging demand will be more uneven and a decline of system overall benefits will appear, considering both of EVs charging and fuel vehicles parking. Given all this, a GA-based optimization is put forward and an optimized setting strategy is proposed
Year of publication: |
[2022]
|
---|---|
Authors: | Mei, Zhenyu ; Tang, Wei ; Feng, Chi ; Zhang, Lihui ; Wang, Dianhai |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Feng, Chi, (2011)
-
The Portfolio Diversification Effect of Catastrophe Bonds and the Impact of COVID-19
Feng, Chi, (2022)
-
Effects of the COVID-19 pandemic on the market value of Japanese gaming companies
Feng, Chi, (2024)
- More ...