Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model

被引:52
作者
Lin, Haiyang [1 ]
Fu, Kun [1 ]
Wang, Yu [1 ]
Sun, Qie [1 ]
Li, Hailong [2 ]
Hu, Yukun [3 ]
Sun, Bo [4 ]
Wennersten, Ronald [1 ]
机构
[1] Shandong Univ, Inst Thermal Sci & Technol, Jingshi Rd 17923, Jinan 250061, Shandong, Peoples R China
[2] Malardalen Univ, Sch Business Soc & Technol, Vasteras, Sweden
[3] UCL, Dept Civil Environm & Geomat Engn, London, England
[4] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicle; Agent-based trip chain model; Vehicle to grid; Fast charging; Charging flexibility; OPTIMAL ENERGY MANAGEMENT; FLEXIBILITY; IMPACT; INTEGRATION; STRATEGIES; PATTERNS; PHEVS;
D O I
10.1016/j.energy.2019.116122
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper developed an agent-based trip chain model (ABTCM) to study the distribution of electric vehicles (EVs) charging demand and its dynamic characteristics, including flexibility and uncertainty, at different types of location. Key parameters affecting charging demand include charging strategies, i.e. uncontrolled charging (UC) and off-peak charging (OPC), and EV supply equipment, including three levels of charging equipment. The results indicate that the distributions of charging demand are similar as the travel patterns, featured by traffic flow at each location. A discrete peak effect was found in revealing the relation between traffic flow and charging demand, and it results in the smallest equivalent daily charging demand and peak load at public locations. EV charging and vehicle-to-grid (V2G) flexibility were examined by instantaneous adjustable power and accumulative adjustable amount of electricity. The EVs at home locations have the largest charging and V2G flexibility under the UC strategy, except for a period of regular working time. The V2G flexibility at work and public locations is generally larger than charging flexibility. Due to the fast charging application, the uncertainties of charging demand at public locations are the highest in all locations. In addition, the OPC strategy mitigates the uncertainty of charging demand. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
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