Abstract
A predictive control/scheduling optimization model is proposed for managed charging of an electric vehicle (EV) fleet - under time-of-use energy and demand prices, high vehicle utilization frequency (short dwell times), multiple charge- acceptance curves (configurable charging rates), and flexible vehicle demand. This context is particularly relevant for flight schools (small electric aircraft) or other commercial facilities where an EV fleet performs multiple operating and fast-charging sessions on the same day. The proposed model performs both the operational and charging scheduling of the vehicles, which is not typically done for residential managed charging and significantly increases problem complexity. The problem is formulated as a MILP model and a case study of a small fast-charging station is presented. Results demonstrate a significant reduction in operating cost, mainly from peak shaving during high demand price periods, achieved by coordinating the operation of different vehicles, chargers and charging rates.
Original language | American English |
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Number of pages | 5 |
DOIs | |
State | Published - 2024 |
Event | 2024 IEEE Power & Energy Society General Meeting - Seattle, Washington Duration: 21 Jul 2024 → 25 Jul 2024 |
Conference
Conference | 2024 IEEE Power & Energy Society General Meeting |
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City | Seattle, Washington |
Period | 21/07/24 → 25/07/24 |
NREL Publication Number
- NREL/CP-5400-92047
Keywords
- charging stations
- electric vehicle charging
- optimal scheduling
- optimization
- smart charging