Coordination of Multiple Electric Vehicle Aggregators for Peak Shaving and Valley Filling in Distribution Feeders
| Autor: | Muhammad Kashif Rafique, Muhammad Omer Khan, Zunaib Maqsood Haider, Saad Ullah Khan, Khawaja Khalid Mehmood, Chul-Hwan Kim |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Control and Optimization
business.product_category vehicle-to-grid (V2G) Computer science 020209 energy Energy Engineering and Power Technology 02 engineering and technology active distribution networks electric vehicles peak shaving smart grid valley filling Load profile lcsh:Technology Automotive engineering Peak demand Electric vehicle 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Engineering (miscellaneous) Energy demand Renewable Energy Sustainability and the Environment lcsh:T 020208 electrical & electronic engineering Grid Power (physics) Smart grid Peaking power plant business Energy (miscellaneous) |
| Zdroj: | Energies; Volume 14; Issue 2; Pages: 352 Energies, Vol 14, Iss 352, p 352 (2021) |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en14020352 |
| Popis: | In this paper, a coordination method of multiple electric vehicle (EV) aggregators has been devised to flatten the system load profile. The proposed scheme tends to reduce the peak demand by discharging EVs and fills the valley gap through EV charging in the off-peak period. Upper level fair proportional power distribution to the EV aggregators is exercised by the system operator which provides coordination among the aggregators based on their aggregated energy demand or capacity. The lower level min max objective function is implemented at each aggregator to distribute power to the EVs. Each aggregator ensures that the EV customers’ driving requirements are not relinquished in spite of their employment to support the grid. The scheme has been tested on IEEE 13-node distribution system and an actual distribution system situated in Seoul, Republic of Korea whilst utilizing actual EV mobility data. The results show that the system load profile is smoothed by the coordination of aggregators under peak shaving and valley filling goals. Also, the EVs are fully charged before departure while maintaining a minimum energy for emergency travel. |
| Databáze: | OpenAIRE |
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