A temporal and spatial distribution forecasting of private car charging load based on origin-destination matrix

作者：Zhang, Chenyu^*; Ding, Ming; Zhang, Jingjing

来源：Transactions of China Electrotechnical Society, 2017, 32(1): 78-87.

• Calculation results
• Charging loads
• Cloud modeling
• Forecasting methods
• Origin destination matrices
• Origin-destination matrix
• Spatial and temporal distribution
• Temporal and spatial distribution

To solve the problem of the uncertainty of charging sites and charging modes in forecasting electric vehicle spatial loads, a temporal and spatial distribution forecasting method based on origin-destination (OD) matrix and cloud model is proposed. First, through monitoring road traffic, the traffic attraction volume of the residential areas can be inversely deduced and the parking probability at different locations can then be dynamically predicted. Next, according to the characteristics of fast charge and slow charge, the conversion rules between users'psychology and fast charging probability can be formulated. Furthermore, the cloud model will be introduced in the rules to reflect the randomness and fuzziness of users'decision. Last, the load time curves of different charging sites will be analyzed and calculated via applying the Monte Carlo method, whose validity has been verified by data from an urban center city as an example. The calculation results show that the traffic volume changes apparently in different residential areas and different working days, and the charging load curve is significantly affected by the traffic volume change. The results also show that the fast charging load will fluctuate in a certain range randomly. Moreover, increasing the slow charge failure threshold will reduce the fast charging load peaks.

• 出版日期2017
• 单位合肥工业大学