Modeling, analysis and coordination of electric vehicles integrating into the electric power grid

• Main Authors: Wu, Diyun, 伍迪芸
• Other Authors: Chau, KT
• Language: English
• Published: The University of Hong Kong (Pokfulam, Hong Kong) 2014
• Subjects: Electric vehicles; Smart power grids
• Online Access: http://hdl.handle.net/10722/197122

In recent years, since the concept of smart grid rises and the existing power grids are continuously modernized, more and more electric vehicles (EVs) are integrated into the power grid. In the power grid, EVs are expected to provide various energy services, such as spinning reserves, regulation services, optimization services, stability improvement, reactive compensation and grid security. This thesis is to model, analyze and implement these energy services of EVs. 　　Firstly, a multilayer framework of a power system with vehicle-to-grid (V2G) and vehicle-to-vehicle (V2V) operation is proposed. Its fundamental components including batteries, renewable energy sources are modeled for system analysis. Moreover, a general model for multiply purposes is presented. 　　Secondly, based on the modeling of EVs and the power systems, the analysis on frequency regulation and transient stability of the V2G system can be carried out effectively. The objectives of the frequency regulation are to keep the system frequency constant, and eliminate the deviations fast and effectively. While, the transient stability is to observe the performances of the power systems integrated with EVs and superconducting magnetic energy storage (SMES) during emergency cases. The results illustrate that EVs are valuable for improve the frequency and transient stability of the power systems. 　　Finally, the coordination and optimization of the power systems with EVs are studied. Unit commitment involving EVs is analyzed, which uses EVs to replace some expensive generating units to achieve minimum operating cost and emissions. In addition, the optimal sizing of EV aggregations in the distribution power system is conducted to minimize the total power loss. And the individual EV in the aggregations is dispatched to achieve minimum charging cost by satisfying the optimal sized demand and the real-time pricing. The results verified that EVs can be used to achieve optimized goals, such as minimum costs, emissions and losses. === published_or_final_version === Electrical and Electronic Engineering === Doctoral === Doctor of Philosophy