System modeling for the large-scale diffusion of multiple electricity technologies in an urban distribution network

In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning.

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Investigation of the Impact of Large-Scale Integration of Electric Vehicles for a Swedish Distribution Network

Energies ◽

10.3390/en12244717 ◽

2019 ◽

Vol 12 (24) ◽

pp. 4717 ◽

Cited By ~ 1

Author(s):

Sylvester Johansson ◽

Jonas Persson ◽

Stavros Lazarou ◽

Andreas Theocharis

Keyword(s):

Electric Vehicles ◽

Power Distribution ◽

Large Scale ◽

Electrical Power ◽

Distribution Network ◽

Transport Sector ◽

Smart Charging ◽

Large Scale Integration ◽

Scale Integration ◽

The Impact

Social considerations for a sustainable future lead to market demands for electromobility. Hence, electrical power distribution operators are concerned about the real ongoing problem of the electrification of the transport sector. In this regard, the paper aims to investigate the large-scale integration of electric vehicles in a Swedish distribution network. To this end, the integration pattern is taken into consideration as appears in the literature for other countries and applies to the Swedish culture. Moreover, different charging power levels including smart charging techniques are examined for several percentages of electric vehicles penetration. Industrial simulation tools proven for their accuracy are used for the study. The results indicate that the grid can manage about 50% electric vehicles penetration at its current capacity. This percentage decreases when higher charging power levels apply, while the transformers appear overloaded in many cases. The investigation of alternatives to increase the grid’s capabilities reveal that smart techniques are comparable to the conventional re-dimension of the grid. At present, the increased integration of electric vehicles is manageable by implementing a combination of smart gird and upgrade investments in comparison to technically expensive alternatives based on grid digitalization and algorithms that need to be further confirmed for their reliability for power sharing and energy management.

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