Abstract
Electric vehicles (EVs) provide new options for energy balancing of power systems. One possible way to use EVs in energy balancing is to let each distribution system mitigate its forecast uncertainties through the flexibility of EVs. In consideration of the difficulties to directly govern a large number of EVs, it is more reasonable for distribution systems to dispatch electric vehicle aggregators (EVAs). Without influencing driving activities of EVs in the next day, a model is established for distribution systems to make use of EVAs, whose contributions are delaying uncertainties through their temporal flexibility and thus creating opportunities for uncertainties from different hours to offset each other. In the established model, a scheme of uncertainty transferring is proposed to relieve interruption to EVAs and distributionally robust optimization is adopted to evaluate the operation plans' average performance with temporal and spatial uncertainty correlations considered. Comprehensive case studies are carried out based on charging demands of EVAs simulated from real traffic data to verify the effectiveness of the proposed model.
| Original language | English |
|---|---|
| Article number | 8890715 |
| Pages (from-to) | 2212-2221 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 35 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - May 2020 |
Keywords
- day-ahead planning
- Distribution system
- distributionally robust optimization
- electric vehicle aggregator
- temporal flexibility
- uncertainty mitigation
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering