Residential electrification load modeling: A critical review of electric vehicle, heat pump, and integrated modeling frameworks

Residential electrification driven by electric vehicles (EVs) and heat pumps (HPs) is fundamentally reshaping electricity demand in distribution systems. EV charging is stochastic and behavior-driven, while HP demand is continuous and governed by thermodynamic processes, creating hybrid load dynamics that may require dependence-aware representation when coincident demand, flexibility, or network constraints are relevant. The reviewed evidence includes technology-specific EV and HP studies as well as studies addressing multiple electrification technologies. Their scope and validation differ: representing EVs and HPs in a common scenario does not by itself establish that their joint behavioral, thermal, temporal, and network interactions have been explicitly modeled and validated. This distinction limits the conclusions that can be drawn about coincident demand, cold-climate operation, uncertainty propagation, and network-constrained integration. This paper presents a critical and unified review of residential electrification load modeling, covering data-driven, simulation-based, physics-based, and hybrid approaches across EV, HP, and integrated EV-HP domains. A key contribution is the identification of residential electrification as a hybrid stochastic-dynamic system, where peak demand emerges from the coupling of behavioral and thermal processes. The paper further introduces a grid-aware evaluation framework and a model suitability matrix to guide application-driven model selection. The results highlight the need for integrated, physics-informed, and grid-constrained modeling frameworks to support accurate forecasting, system planning, and real-time control in highly electrified residential networks.