Real-Time Smart Charging of Electric Vehicles for Demand Charge Reduction at Non-Residential Sites
Why this work is in the frame
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Bibliographic record
Abstract
Smart electric vehicle (EV) charging deals with increasing demand charges caused by EV load on EV supply equipment (EVSE) hosts. This paper proposes a real-time smart charging algorithm that can be integrated with commercial & industrial EVSE hosts through building energy management system or with utility back office through the advanced metering infrastructure. The proposed charging scheme implements a real-time water-filling algorithm able to reduce the peak demand and to prioritize EV charging based on the data of plugged-in EVs. The algorithm also accommodates utility and local demand response and load control signals for extensive peak shaving. Real-world EV charging data from different types of venues are used to develop and evaluate the smart charging scheme for demand charge reduction at medium & large general service locations. The results show that even at constrained venues such as large retails, monthly demand charges caused by EVs can be reduced by 20%-35% for 30% EV penetration level without depreciating EVs' charging demand.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it