Lawrence Berkeley National Laboratory

Rapid growth of electric demand combined with increased penetration of intermittent power sources increases the value of flexible electric heating, but the techno-economic role of central hot-water storage under realistic tariffs remains unclear. This paper introduces HeatShift-HP, an open-source Python/Modelica co-simulation workflow. The framework couples a generic air-to-water heat pump and a stratified storage tank Functional Mock-up Unit with a supervisory rule-based controller and time series of weather, heating load, and end-user electricity prices. The framework targets plant-side flexibility and varies specific tank volume, nominal supply and return temperatures, heat-pump sizing, controller settings, and tariff variants, including a price-responsive boosting strategy constrained by a cost-neutral coefficient of performance approximation. The workflow is applied to a single-family reference building in Berlin and Chicago using 2025 weather and hourly retail prices with and without dynamic grid-fee components. A theoretical pre-analysis shows that typical hot-water buffers provide only limited stand-alone autonomy compared with building thermal mass. Annual simulations show that nominal system temperature is the dominant driver of both seasonal performance and paid heat costs. Lowering the nominal supply temperature from 40 ∘C to 35 ∘C reduces the median paid specific heat cost by about 3.7 % in Berlin and 4.4 % in Chicago for the standard controller, with similarly strong reductions under price-based control. By contrast, additional storage mainly improves operational flexibility by reducing cycling and increasing low-price heat generation. The pooled effect of price-based control remains below 1 % in both cities, but matched Berlin dynamic-grid cases show savings of up to 4.0 %. Dynamic grid fees in Berlin reduce median paid heat costs by about 7.0 %  to  7.6 % relative to the fixed-grid tariff. The results show that low-temperature system design minimises absolute heat costs, whereas the incremental value of price-based control depends primarily on sufficient storage, moderate control actions, and retail tariffs with sufficiently strong temporal price variation.