| Issue |
E3S Web Conf.
Volume 293, 2021
2021 3rd Global Conference on Ecological Environment and Civil Engineering (GCEECE 2021)
|
|
|---|---|---|
| Article Number | 03032 | |
| Number of page(s) | 4 | |
| Section | Sustainable Resource Development and Green Energy Saving | |
| DOI | https://doi.org/10.1051/e3sconf/202129303032 | |
| Published online | 23 July 2021 | |
Research on electric vehicle ownership prediction based on BASS model: A case study of Yunnan Province
1 Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming, China
2 Key Laboratory in Software Engineering of Yunnan Province, School of Software, Yunnan University, China
3 Information Center,Yunnan Power Grid Co., Ltd, Kunming, China
4 Kunming Enersun Technology Co., Ltd, Kunming, China
* Corresponding author: lsyfd27@sina.com
In order to forecast the number of electric vehicles in Yunnan Province, based on BASS model, this paper uses extensive analogy method to explore the acquisition of m, p and q model parameters, forecasts the purchasing power of the market, and estimates the innovation coefficient and imitation coefficient from three aspects of high potential scenario, base potential scenario and low potential scenario. The number of new energy electric vehicles in Yunnan Province in three scenarios from 2022 to 2035 is predicted. The forecast results show that under the condition of high potential development, the number of new energy vehicles in Yunnan Province will reach 409,600 in 2022; in the case of benchmark potential development, the number of new energy vehicles will reach 291,400 in 2022; in the case of low potential development, the number of new energy vehicles in Yunnan Province will reach 155,400 in 2022.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.