Electric vehicle charging in smart grid:A spatial-temporal simulation method
| Autor: | Xiangyu Wei, Chenghong Gu, Zhuozhen Jiang, Yue Xiang, Fei Teng, Yang Wang |
|---|---|
| Přispěvatelé: | Innovate UK |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Trip chain
business.product_category Distribution networks Computer science 020209 energy Spatial-temporal modeling Trajectory 02 engineering and technology Electric vehicle 0915 Interdisciplinary Engineering Automotive engineering Industrial and Manufacturing Engineering Distribution system Electric power system 020401 chemical engineering 0202 electrical engineering electronic engineering information engineering SDG 7 - Affordable and Clean Energy 0204 chemical engineering Electrical and Electronic Engineering Civil and Structural Engineering Battery energy Energy Mechanical Engineering 0914 Resources Engineering and Extractive Metallurgy Energy consumption Building and Construction Pollution Distribution network General Energy Smart grid Charging load Transportation system business 0913 Mechanical Engineering |
| Zdroj: | Xiang, Y, Jiang, Z, Gu, C, Teng, F, Wei, X & Wang, Y 2019, ' Electric vehicle charging in smart grid : A spatial-temporal simulation method ', Energy, vol. 189, 116221, pp. 1-12 . https://doi.org/10.1016/j.energy.2019.116221 |
| DOI: | 10.1016/j.energy.2019.116221 |
| Popis: | Electric vehicles (EVs) play an important role in the future energy system. The large-scale adoption of moving EV load significantly accelerates the integration of transportation and distribution systems. The method to simulate the mobility and charging of a single or aggregated EVs is the key to analyze EVs’ flexibility on the operation of distribution network. Considering the integrated impacts from both the transportation and power systems, and the uncertainty of user’s driving behavior and charging intention, this paper proposes a spatial-temporal simulation method based on the vehicle-transportation-grid trajectory. The trajectory can not only describe the destination location and time like the trip chain, but also give the key information including the driving path in a whole travel process. The driving, parking, and charging are analyzed by the proposed spatial-temporal simulation method. It models the driving behavior based on statistical results and transportation systems, EV energy consumption pattern based on battery energy, and the charging demand based on the user’s subjective intention at the coupled systems. Finally, a 30-node transportation system is developed and integrated with a 33-bus distribution network to illustrate the proposed method. Two typical days, “workday” and “holiday”, are simulated and compared under different EV penetration levels (0%, 20%, 50% and 100%), different trip chain ratio (the ratio of 3-trip chains is 50%, 70%, 90%) to demonstrate the effectiveness of the spatial-temporal simulation method. |
| Databáze: | OpenAIRE |
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