Protecting residential electrical panels and service through model predictive control: A field study
<|reference_start|>Protecting residential electrical panels and service through model predictive control: A field study: Residential electrification - replacing fossil-fueled appliances and vehicles with electric machines - can significantly reduce greenhouse gas emissions and air pollution. However, installing electric appliances or vehicle charging in a residential building can sharply increase its current draws. In older housing, high current draws can jeopardize electrical infrastructure, such as circuit breaker panels or electrical service (the wires that connect a building to the distribution grid). Upgrading electrical infrastructure can entail long delays and high costs, so poses a significant barrier to electrification. This paper develops and field-tests a control system that avoids the need for electrical upgrades by keeping an electrified home's total current draw within the safe limits of its panel and service. In the proposed control architecture, a high-level controller plans device set-points over a rolling prediction horizon. A low-level controller monitors real-time conditions and ramps down devices if necessary. The control system was tested in an occupied, electrified single-family house with code-minimum insulation, an air-to-air heat pump and backup resistance heat, a resistance water heater, and a plug-in hybrid electric vehicle with Level I charging. The field tests spanned 31 winter days with outdoor temperatures as low as -20 C. The control system maintained the whole-home current within the safe limits of electrical panels and service rated at 100 A, a common rating for older houses in North America, by adjusting only the temperature set-points of the heat pump and water heater. Simulations suggest that the same 100 A limit could accommodate a second electric vehicle with Level II charging. The proposed control system could allow older homes to safely electrify without upgrading electrical panels or service, saving a typical household on the order of $2,000 to $10,000.<|reference_end|>
@article{pergantis2024protecting,
    title={Protecting residential electrical panels and service through model
  predictive control: A field study},
    author={Elias N. Pergantis, Levi D. Reyes Premer, Alex H. Lee, Priyadarshan,
  Haotian Liu, Eckhard A. Groll, Davide Ziviani, Kevin J. Kircher},
    journal={arXiv preprint arXiv:2409.04884},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.04884},
    primaryClass={eess.SY cs.SY}
}