Abstract
The growing trend of introducing electric vehicles (EVs) into power systems to reduce the environmental emissions in the transport sector is gaining significant attention among electrical power system agents for two reasons: the potential grid services the EVs can offer in an aggregated manner and the possible undesirable effects of massive integration in grid operation that can increase the requirement for investment in new assets. In this context, the aggregator is the representative entity that needs to maximise the benefits in the management of these sizeable quantities of vehicles while fulfilling the requirements of grid services requested by the distribution system operator. In this study, we review the concept of EV aggregators and their potential services to the distribution network. Several studies related to EVs aggregation modelling have been analysed and classified into three groups: individual-based, population-based, and hybrid approaches. We present the current status of EVs aggregation modelling as well as future research trends. Furthermore, we discussed the performance comparison of EVs models from several manufacturers utilised in network integration studies, likewise the most relevant databases and surveys. Finally, we arranged and annexed the most relevant mathematical expressions of the reviewed approaches, thereby simplifying the comprehension of the methods.
| Original language | English |
|---|---|
| Article number | 106785 |
| Pages (from-to) | 106785 |
| Number of pages | 1 |
| Journal | Electric Power Systems Research |
| Volume | 189 |
| DOIs | |
| Publication status | Published - Dec 2020 |
Keywords
- Aggregator
- Electric vehicles
- Grid services
- Individual-based approach
- Population-based approach
- Vehicle surveys
Project and Funding Information
- Funding Info
- We would like to gratefully acknowledge that this study was made possible with the help of TECNALIA funding through a PhD scholarship. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work.
