| Author: | Wang, Wei |
| Title: | Electric vehicles and smart grid integration |
| Degree: | M.Sc. |
| Year: | 2013 |
| Subject: | Electric automobiles -- Power supply -- Forecasting. Electric automobiles -- Power supply -- Economic aspects. Electric power plants -- Load. Electric utilities. Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Engineering |
| Pages: | x, 62 p. : ill. ; 30 cm. |
| Language: | English |
| Abstract: | Hybrid or pure battery driven electric vehicles, as emerging technology, can alleviate the energy crisis and reduce the environmental pollution. However, due to the uncertainty of electric vehicle charging behavior, a large number of electric vehicles connected to power grid may lead to a dramatic increase in power consumption, especially, during the peak period, undermining the system operation efficiency. Hence, to solve the problem, the most suitable EV charging mode for the integration of EVs and Smart Grid must be found out. Hence, this thesis focuses on the cost-efficient integration of EVs with the Smart Grid using smart charging modes. Several researches have shown that charging strategies of electrical vehicle may cause peak demands such as morning and evening peaks, which may lead to the violations of power grid constrains. Therefore, smart charging strategy is critical to reduce the peak demand. Moreover, it can significantly improve the reliability and energy efficiency of the power system. In order to realize the EVs and Smart Grid integration, this thesis focuses on a research on the EV charging load model and a case study about the impact of EV charging mode on load characteristic taking into account the factors influencing electric vehicle charging loads and finally obtain the most suitable EV charging mode (V2G) for the integration of EVs and Smart Grid. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b26493147.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.64 MB | Adobe PDF | View/Open |
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