[1]张懿璞,金雨哲,柯 吉,等.考虑电动汽车负荷的高速公路服务区离网微电网容量配置[J].长安大学学报(自然科学版),2024,44(5):126-140.[doi:10.19721/j.cnki.1671-8879.2024.05.011]
　ZHANG Yi-pu,JIN Yu-zhe,KE Ji,et al.Capacity configuration of microgrid in off-grid accessible service area considering variable load[J].Journal of Chang’an University (Natural Science Edition),2024,44(5):126-140.[doi:10.19721/j.cnki.1671-8879.2024.05.011]
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考虑电动汽车负荷的高速公路服务区离网微电网容量配置()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第44卷
期数:
2024年5期
页码:
126-140
栏目:
交通能源融合技术专题
出版日期:
2024-10-10

文章信息/Info

Title:
Capacity configuration of microgrid in off-grid accessible service area considering variable load
文章编号:
1671-8879(2024)05-0126-15
作者:
张懿璞; 金雨哲; 柯 吉; 茹 锋; 张成朔
(长安大学 能源与电气工程学院,陕西 西安 710018)
Author(s):
ZHANG Yi-pu;  JIN Yu-zhe;  KE Ji;  RU Feng;  ZHANG Cheng-shuo
(School of Energy and Electrical Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程;  交通能源融合;  电动汽车负荷;  蒙特卡洛;  高速公路;  微电网;  容量配置
Keywords:
traffic engineering;  integration of transportation and energy;  electric vehicle load;  Monte Carlo;  highway;  microgrid;  capacity configuration
分类号:
U491.11
DOI:
10.19721/j.cnki.1671-8879.2024.05.011
文献标志码:
A
摘要:
为促进交通能源融合,保障偏远地区高速公路电力的稳定供给,合理配置微电网容量至关重要。考虑路网车流量,建立高速公路电动汽车出行轨迹概率模型; 基于蒙特卡洛方法抽取初始和充电时电池容量,综合考虑气温、车主出行习惯和不同车型能耗水平等因素,预测电动车负荷时空分布; 从离网的高速公路服务区不同等级负荷需求出发,基于当地自然禀赋水平,建立以缺电概率最低为目标的规划模型; 综合考虑新能源出力、场地限制、新能源自洽率和极端天气等约束,定量分析车辆OD(起点-终点)矩阵、电池状态SOC以及包含不同车流量、气温典型日对容量配置的影响。研究结果表明:OD矩阵的平均程度对充电负荷有显著影响,当OD矩阵越平均时,电动汽车的充电负荷越小; 当OD矩阵不均衡时,充电负荷会显著增加; 初始电池状态SOC0对充电负荷有直接影响,SOC0越大,充电负荷相应减少; 反之,则增加; 工作日、双休日和节假日的充电负荷呈递增趋势,其中双休日的充电负荷比工作日高12.5%,节假日则比工作日高20%; 因冬季供暖用能比夏季供冷用能更高而风光资源匮乏,因此冬季需配置更大容量的设备以保证用电稳定; 提出的微电网容量配置方法能够有效优化电力供应,保障离网地区的电力稳定性需求,并且能够优化微电网容量配置,保障离网地区用电的稳定性需求,满足1级、2级负荷用电,3级负荷缺电率不超过0.02%,自洽率超过90%,符合供电标准与绿色化要求,为新能源在交通领域的应用提供参考。
Abstract:
To promote the integration of transportation and energy and ensure the stable power supply for highways in remote areas, the proper configuration of microgrid capacity was deemed crucial. A probability model for highway electric vehicle travel trajectories was established considering traffic flow on the road network. Initial and charging battery capacities were extracted using the Monte Carlo method, and the spatiotemporal distribution of electric vehicle loads was predicted by integrating factors such as temperature, travel habits, and different vehicle energy consumption levels. Based on the load demands of off-grid highway service areas and local natural endowments, a planning model targeting the minimum probability of power shortages was developed. Constraints like new energy output, site limitations, energy self-consistency, and extreme weather were considered to quantitatively analyze the impacts of vehicle OD(origin-destination)matrices, states of charge SOC, and typical days with varying traffic volumes and temperatures on capacity configuration. Theresults show that the average degree of the OD matrix significantly affects the charging load. A more balanced OD matrix results in a lower electric vehicle charging load, while an imbalanced OD matrix significantly increases the load. Additionally, the initial states of charge SOC0 directly impacts the charging load, a higher SOC0 reduces the charging load, while a lower SOC0 increases it. Charging loads exhibit an increasing trend on working days, weekends, and holidays, with weekend loads being 12.5% higher than on working days and holiday loads 20% higher. Due to higher heating energy consumption in winter compared to cooling in summer and scarce wind and solar resources, larger capacity equipment is needed in winter to ensure stable power supply. The microgrid capacity configuration method proposed can effectively optimize power supply and meet the stability requirements of off-grid areas, ensuring that the load for primary and secondary levels is met, with the tertiary load shortage rate not exceeding 0.02% and self-consistency exceeding 90%, thus meeting power supply standards and green requirements and providing a reference for the application of new energy in the transportation sector.8 tabs, 16 figs, 31 refs.

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备注/Memo

备注/Memo:
收稿日期:2024-07-01
基金项目:国家重点研发计划项目(2021YFB2601300); 中央高校基本科研业务费专项资金项目(300102383202)
作者简介:张懿璞(1985-),男,陕西西安人,教授,博士研究生导师,E-mail:zyipu@chd.edu.cn。
更新日期/Last Update: 2024-10-20