Influence of Dynamic Pricing on Bottom-Up Household Technology Selection with Heat Pump Water Heater

This paper examines the effects of dynamic retail and feed-in tariffs on technology selection and operation scheduling for a household demand-side energy system that incorporates technologies, including a heat pump water heater (HPWH). We develop a mixed-integer linear programming (MILP) model that integrates (i) a dynamic HPWH sub-model and (ii) a market-linked tariff sub-model. The model is applied to a five-day winter period for a household in Fukui, Japan. Compared with the conventional flat-rate tariff case, the dynamic-tariff case—while still minimizing the total cost—retains a hybrid water-heating mix of a gas-fired water heater and the HPWH and does not trigger the adoption of additional renewable devices such as a rooftop photovoltaic (PV) array or a solar-thermal collector; the only quantitative change is that the optimal capacities of the HPWH and the smart distribution panel increase by 12.8% and 7.4%, respectively. Operational schedules shift toward low-price hours, reducing gas-related costs and gas-related CO2 emissions by 8.6% and 10.9%, whereas electricity-derived CO2 emissions rise by 3.1%, leaving total CO2 emissions almost unchanged. Sensitivity analysis confirms that tariff volatility variations (±50%) have minimal impact on costs and emissions (below 1%). These findings suggest that during short winter periods, price signals primarily enhance operational flexibility rather than alter equipment adoption, and that additional hardware investment remains crucial for achieving higher operating efficiency.