Comfort zone - A COSMIC approach to modelling thermal comfort in building simulations
Methods are available to determine whether people will be comfortable with the indoor temperatures of buildings. Building simulations for example, have long used Predicted Mean Vote (PMV) index, as a way to estimate this comfort (known as thermal comfort). This index can help determine whether heating and cooling should be switched on. What PMV is not able to fully account for is the way people adapt to their surroundings, particularly in buildings without continuous air conditioning.
A new COSMIC study, co-written with LIFE BUILD OSS, "A methodological framework and computational tool for adaptive predicted mean vote setpoints in EnergyPlus building simulations" explores a potential improvement to PMV, bringing in the approach of Adaptive Predicted Mean Vote (aPMV) into EnergyPlus, a widely used building energy simulation programme. Unlike the traditional PMV approach, the adaptive model recognises that people can adjust to changing indoor conditions and stay comfortable across a range of temperatures.
The researchers Daniel Sánchez-García, David Bienvenido-Huertas, Alberto Cerezo-Narváez, MCarmen Delgado Guerrero, and José Sánchez Ramos, developed a methodology and Python-based computational tool that allows building simulations to use adaptive comfort conditions for the setting of heating and cooling temperatures. The tool can be customised with 13 parameters and adjusted depending on simulation needs. This enables a more realistic assessment of thermal comfort and energy performance calculations for buildings.
The study demonstrates how incorporating these adaptive assumptions about occupant comfort can help designers make more informed decisions at earlier stages of building projects. The researchers note an area of refinement to be adjusting the adaptive coefficient used by the model for different climates to gain even more accurate results.
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