Research results on smart heating systems based on occupancy prediction are 
often difficult to reproduce and to compare. Evaluating the performance of 
these systems through simulation or real experiments requires defining 
suitable scenarios and setting a large number of parameters. As different 
authors rely on different scenarios and parameter settings, comparing the 
reported performance results is often infeasible. In this paper, we argue that 
overcoming this problem is crucial to bring research on smart heating systems 
a step forward. We outline the main factors influencing the performance of 
such systems and we show how these factors can be integrated by proposing a 
simple yet thorough evaluation methodology for smart heating systems. Using 
parameters synthesised from real-world occupancy and weather data, we describe 
how this methodology can be used to establish performance bounds of smart 
heating systems.