Abstract
The charging load of electric vehicles (EVs) is characterized by uncertainty and flexibility, which burdens the distribution network, especially when there is a high penetration of distributed generation (DG) in smart grids. Large-scale EV mobility integration not only affects smart grid operation reliability but also the reliability of EV charging services. This paper aims at estimating the comprehensive impacts caused by spatial-temporal EV charging from the perspective of both electricity system reliability and EV charging service reliability. First, a comprehensive reliability index system, including two novel indexes quantifying EV charging service reliability, is proposed. Then, considering traffic constraints and users’ charging willingness, a spatial-temporal charging load model is introduced. In the coupled transportation and grid framework, the reliability impacts from plenty of operation factors are analyzed. Moreover, the electricity system reliability and EV charging service reliability correlated with DG integration are discussed. A coupled transportation grid system is adopted to demonstrate the effectiveness and practicability of the proposed method. The numerical results analyze reliability impacts from EV penetration level, trip chain, EV battery capacity, DG installation location, and capacity. The proposed studies reveal that when the EV capacity ratio to DG capacity is 3:1, the system reliability reaches the maximum level.
Highlights
The problems of carbon emissions and energy shortage have been increasingly serious nowadays, which has captured people’s attention on sustainable and clean energy
Impacts of electric vehicles (EVs) integration on the coupled system considering EV spatialtemporal mobile charging should be investigated to make a tradeoff between electricity system reliability and charging service reliability and to obtain a strategy for EV and distributed generation (DG) coordination operation
The rest of this paper is organized as follows: in Mobile Electric vehicle Charging Load Modeling, spatial-temporal mobile EV charging load modeling is introduced; the reliability evaluation method for both system and EV charging service-based sequential Monte Carlo is proposed in Reliability Assessment; Framework provides a detailed description of the research framework employed in this paper; Numerical simulations about coupled system reliability with EV mobility and DG integration are performed in Case Study; and Conclusion draws some conclusions
Summary
The problems of carbon emissions and energy shortage have been increasingly serious nowadays, which has captured people’s attention on sustainable and clean energy. Reliability impacts of DG and EV operation in coordination on smart grids should be analyzed Considering insufficiency in these studies, the reliability impacts of large-scale mobile EV integration on electricity system-based sequential Monte Carlo method are discussed in this paper. 2) A spatial-temporal mobile EV charging load model based on the vehicle-transportation-grid trajectory is proposed considering EV traffic characteristics and users’ charging willingness. The rest of this paper is organized as follows: in Mobile Electric vehicle Charging Load Modeling, spatial-temporal mobile EV charging load modeling is introduced; the reliability evaluation method for both system and EV charging service-based sequential Monte Carlo is proposed in Reliability Assessment; Framework provides a detailed description of the research framework employed in this paper; Numerical simulations about coupled system reliability with EV mobility and DG integration are performed in Case Study; and Conclusion draws some conclusions.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
