Control strategies for dynamic insulation materials applied to commercial buildings

Abstract

This paper evaluates the potential heating and cooling energy use and cost savings associated with improved controls of dynamic insulation materials (DIMs) when used in multilayered wall assemblies for commercial office buildings. Using a genetic algorithm (GA) based optimization technique, optimum R-value settings are identified for the DIMs throughout the year. These optimal R-value settings are selected to maximize energy cost savings when compared to traditional static insulated wall systems. It is found that optimal control settings for DIMs depend on several factors including building design and operation strategies as well as climatic conditions. Moreover, the optimal settings were found to depend on the orientation of exterior walls and well as the climatic conditions. Specifically, the analysis results indicate that north-facing walls are more active and frequently have to change their R-value in order to minimize the office building energy use and cost. When optimally controlled, DIMs could save up to 17% of annual heating and cooling energy costs for US office buildings.