Heat Pumps are essential to building electrification strategies, and are quickly expanding into industrial applications. The energy modeling community's performance representations of heat pump technologies primarily leverage a wide range of curve fit strategies. The number and types of curves vary between technology and application. It is difficult for practitioners to obtain accurate curve information for newer technology and the software defaults are often decades old.

Meanwhile performance boundaries are continuously expanded (both low and high temperature) and current refrigerants are scheduled to be phased down or out completely. This means that the need for new families of curves and even model objects (for all the various applications) will increase rapidly. Past efforts to streamline public sharing of performance data between vendors and the analysis community have not succeeded. Also the need for accuracy is increasing as we seek to tackle accurate sub-hourly characterizations to support demand flexibility and promote buildings as grid assets.

How do we as a community establish a robust solution to enable accurate heat pump modeling regardless of application or refrigerant? That's the question this small group will brainstorm on. We are seeking broad analytical experience: physics-based models, regression, physics-informed ML, AI... Everything's on the table.

Let's get creative and formulate ideas and potential frameworks to keep our industry moving forward in supporting robust grid decarbonization.