When transformer capacity constrains charging, specify the allocation objective. Alyami ranks deadline and required energy to maximise completed requests [1]; that is one objective, not a universal definition of fairness. Equal power, protected service and curtailment history can select different outcomes.
Separate feasibility from the allocation objective
First define electrical/thermal limits, resource availability and service requirements. Jain’s transformer-aware EV study illustrates the local equipment boundary [2]. Choose an allocation objective only within the feasible set; changing a service requirement must remain visible.
Preserve the location and phase of each resource. Equal division of a total allowance can violate the limiting phase even when the arithmetic sum is correct. Likewise, a user with a near departure deadline may need a higher interval power to receive the same completed service as someone connected overnight.
| Rule considered | What is equalized or protected | Possible tradeoff |
|---|---|---|
| Equal instantaneous power | kW allocated during an interval | Different energy completion when availability differs |
| Deadline-aware service | Progress toward the stated completion requirement | A later-deadline user may wait longer |
| Basic-service reserve | A specified minimum service before discretionary use | Less capacity remains for optional requests |
| Curtailment-history adjustment | Burden over several events | Requires a defined history and treatment of new participants |
Use a small example with explicit requests
Consider an illustrative pair of chargers with the same power capability. One has a short remaining connection window and the other a longer window. An equal-power rule may leave the first request incomplete while the second still has unused future opportunity. A deadline-aware rule can change that outcome if the remaining transformer allowance and later intervals permit it.
The comparison should retain requested energy, availability and phase constraints. Report completed energy, unmet energy and waiting time under each rule. A favorable result obtained by reducing one customer’s request is a different service agreement, not an improvement in allocation.
Make exceptions and infeasibility reviewable
Define how overrides, failed devices, nonparticipating customers and previously curtailed users enter the rule. A minimum reserve should identify the service it protects and who approves it. Do not present one chosen fairness metric as a regulatory requirement unless the applicable rule has actually been established.
A disputed allocation should be reproducible from the requests, the selected objective and the binding transformer constraint. Preserve any request that could not be fulfilled and why. If the same shortfall persists across feasible schedules, an unexplained fairness score cannot resolve the capacity or service conflict.
References
- S. Alyami, Ensuring Sustainable Grid Stability through Effective EV Charging Management: A Time and Energy-Based Approach, Sustainability 16, 6149, 2024, section 3. DOI: 10.3390/su16146149.
- A. Jain and M. Karimi-Ghartemani, Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers, Energies 15, 9023, 2022. DOI: 10.3390/en15239023.