| 引用本文: | 陈立兴,韩晓新,季振亚,王琪.高速公路充电网络充电设施运行状态时空预测建模[J].电力自动化设备,2021,41(8): |
| CHEN Lixing,HAN Xiaoxin,JI Zhenya,WANG Qi.Spatio-temporal forecasting modeling for running status of charging facilities in highway charging network[J].Electric Power Automation Equipment,2021,41(8): |
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| 摘要: |
| 准确的充电网络充电设施运行状态时空预测建模是高速公路预约充电优化的基础。考虑电动汽车行驶速度与传统汽车相接近，基于传统汽车的实际行驶速度数据，提出了一种高速公路充电网络充电设施运行状态时空预测建模方法。一方面，采用灰色关联分析法、协整-自回归移动平均法和小波神经网络方法对电动汽车的行驶速度进行滚动预测；另一方面，基于预测值和观察值，利用蒙特卡洛方法、弗洛伊德方法和排队算法对高速公路充电网络充电设施运行状态进行时空预测。算例研究结果表明，采用所提方法得到的高速公路充电网络充电设施运行状态时空预测结果比较准确，可满足电动汽车预约充电优化需求。 |
| 关键词: 高速公路充电网络 电动汽车 充电设施运行状态 时空预测 排队算法 建模 |
| DOI：10.16081/j.epae.202104026 |
| 分类号:U469.72 |
| 基金项目:江苏省自然科学基金资助项目(211320B51903)；江苏省高等学校自然科学研究项目(111320B11902)；常州市科技计划项目(CJ20190073, CJ20200044)；江苏理工学院人才引进项目(KYY17018) |
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| Spatio-temporal forecasting modeling for running status of charging facilities in highway charging network |
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CHEN Lixing1, HAN Xiaoxin1, JI Zhenya2, WANG Qi1
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1.School of Electrical & Information Engineering, Jiangsu University of Technology, Changzhou 213001, China;2.School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
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| Abstract: |
| Accurate spatio-temporal forecasting modeling for RSCF(Running Status of Charging Facilities) in highway charging network is the basis of reservation charging optimization. Considering that the driving speed of EV(Electric Vehicle) is close to that of traditional vehicle, based on the actual driving speed data of traditional vehicle, a spatio-temporal forecasting modeling method for RSCF in highway charging network is proposed. On the one hand, the rolling forecasting for EV driving speed is carried out by using the grey relational analysis method, cointegration-autoregressive moving average method and wavelet neural network method. On the other hand, based on the forecasting and observed values, the spatio-temporal forecasting for RSCF in highway charging network is realized by using Monte Carlo method, Freudian method and queuing algorithm. The results of case study show that the spatio-temporal forecasting results for RSCF in highway charging network obtained by the proposed method are more accurate, which can meet the optimization requirements of reservation charging of EV. |
| Key words: highway charging network electric vehicles running status of charging facilities spatio-temporal forecasting queuing algorithm modeling |
