Laboratory Evaluation of Residential Smart Panels

Widespread residential electrification in California is constrained by legacy service panels (100–125 A) that cannot support concurrent operation of high-demand loads such as heat pumps, EV chargers, and electric dryers. Conventional service upgrades are expensive, require utility coordination, and disproportionately burden lower-income households. Smart electrical panels offer a potential alternative by dynamically managing circuit-level loads to prevent main-breaker trips and defer service upgrades, but there is limited independent validation of their technical performance or market readiness. This project evaluates three commercially available smart-panel architectures—a full smart-panel replacement, a downstream smart subpanel, and retrofit smart breakers—through controlled laboratory testing at UC Davis and stakeholder engagement with contractors, utilities, and building-department officials. Laboratory testing assessed service-upgrade-avoidance (SUA) behavior using overload conditions from 5% to 100% above configured limits, circuit-level metering accuracy, and load-reenergization logic. Stakeholder engagement examined awareness, perceived barriers, and inspection challenges. All systems successfully prevented sustained overloads below main-breaker thermal-trip curves, demonstrating technical feasibility for SUA. The panel-replacement system employed overload-dependent and adaptive 1–6 min recovery intervals. The smart subpanel initiated shedding within ~4 seconds but used a fixed 1-min re-enable timer, producing frequent cycling under sustained loads. The smart-breaker system relied on user-defined “scenes” rather than automated sensing, providing limited autonomous protection and depending heavily on correct configuration. All products achieved circuit-level metering accuracy within ±5 W of laboratory reference equipment, sufficient for consumer feedback but not revenue-grade. Advanced features marketed as demand response, TOU optimization, or carbon-signal control were either minimally implemented or dependent on third-party smart-home platforms. Interviews revealed low installation experience, inconsistent inspector familiarity, unclear software-driven control behaviors, and high upfront cost as primary barriers. Results indicate that smart panels can technically defer service upgrades today, but broader adoption will require improved software transparency, installer training, and aligned permitting/inspection procedures.