Ming Zeng
School of Economics and Management North China Electric Power University, 102206, Beijing, China
Xiaohui Zhan
School of Economics and Management North China Electric Power University, 102206, Beijing, China
Song Xue
School of Economics and Management North China Electric Power University, 102206, Beijing, China
Mingjuan Ma
School of Economics and Management North China Electric Power University, 102206, Beijing, China
Yulong Li
School of Economics and Management North China Electric Power University, 102206, Beijing, China
ABSTRACT
Large-scale development of electric vehicles plays a significance positive role in promoting the balance of power peak load and increasing employment rates, so forecasting electric vehicle inventory accurately is significant for adjusting relevant industrial policies and achieving orderly development of electric vehicles. This study proposes an improved Bass model based on Particle Swarm Optimization to forecast the inventory of electric vehicles in China by 2020 considering the advantages of Bass model with taking full account of the internal and external factors. The forecast results of the case of baseline oil price and high oil price match with the objectives of development for electric vehicles in China by 2020. It can seen that the electric vehicles will develop rapidly during Twelfth Five-Year Plan period and high oil price can promote the spread of electric vehicles to some extent.
PDF References Citation
Received: August 05, 2013;
Accepted: November 08, 2013;
Published: November 12, 2013
How to cite this article
Ming Zeng, Xiaohui Zhan, Song Xue, Mingjuan Ma and Yulong Li, 2013. Inventory Forecast of Electric Vehicles in China during the Twelfth Five-Year
Plan
Period Using Bass Model Optimized by Particle Swarm Optimization. Journal of Applied Sciences, 13: 4887-4891.
DOI: 10.3923/jas.2013.4887.4891
URL: https://scialert.net/abstract/?doi=jas.2013.4887.4891
DOI: 10.3923/jas.2013.4887.4891
URL: https://scialert.net/abstract/?doi=jas.2013.4887.4891
REFERENCES
- Andersson, S.L., A.K. Elofsson, M.D. Galus, L. Goransson, S. Karlsson, F. Johnsson and G. Andersson, 2010. Plug-in hybrid electric vehicles as regulating power providers: Case studies of Sweden and Germany. Energy Policy, 38: 2751-2762.
CrossRef - Peterson, S.B., J.F. Whitacre and J. Apt, 2010. The economics of using plug-in hybrid electric vehicle battery packs for grid storage. J. Power Sources, 195: 2377-2384.
CrossRefDirect Link - Barin, A., L.F. Pozzatti, L.N. Canha, R.Q. Machado, A.R. Abaide and G. Arend, 2010. Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning. Int. J. Electr. Power Energy Syst., 32: 1157-1164.
CrossRef - Soroudi, A., M. Ehsan and H. Zareipour, 2011. A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources. Renewable Energy, 36: 179-188.
CrossRef - Lavorato, M., M.J. Rider, A.V. Garcia and R. Romero, 2009. Distribution network planning using a constructive heuristic algorithm. Proceedings of the Power and Energy Society General Meeting, July 26-30, 2009, Calgary, AB., pp: 1-6.
CrossRef - White, C.D. and K.M. Zhang, 2011. Using vehicle-to-grid technology for frequency regulation and peak-load reduction. J. Power Sources, 196: 3972-3980.
CrossRef - Wang, R., Y. Chen, D. Feng, X. Huang and J. Wang, 2011. Development and performance characterization of an electric ground vehicle with independently actuated in-wheel motors. J. Power Sources, 96: 3962-3971.
CrossRef - Silva, C., 2011. Electric and plug-in hybrid vehicles influence on CO2 and water vapour emissions. Int. J. Hydrogen Energy, 36: 13225-13232.
CrossRef