Solution space of optimal heat pump schedules

TL;DR

This paper investigates the set of optimal heat pump schedules in residential heating, revealing that the space of optimal solutions is large and complex, which underscores the importance of mathematical optimization in practical applications.

Contribution

It demonstrates that the optimal scheduling space for heat pumps is extensive and challenging to model statistically, supporting the use of mathematical optimization methods.

Findings

Large space of optimal schedules found in practice

Optimal schedules are difficult to reproduce with statistical models

Mathematical optimization is valuable for real-life heating applications

Abstract

We study the space of optimal schedules for a heat pump with thermal energy storage used in heating a residential building. We model the heating system as a Mixed Integer Linear Program with the objective to minimise the cost of heating. We generate a large number of realistic daily heat demands and calculate the optimal schedule for the heat pump. In addition to cost savings stemming from optimal running, we find that the space of optimal schedules is large in practice, even for the simplest model of the heating system we use, and that the optimal schedules are difficult to reproduce with statistical models. These findings strengthen the case for the use of mathematical optimisation in real-life applications.