This paper summarizes the results of a series of analyses to evaluate the suitability of switchable window systems as grid-interactive efficient building (GEB) technology. The switchable window systems (SWS) are capable of changing both their optical and thermal properties to adjust specifically solar heat gain coefficient and U-value to desired levels. In this paper, a specific SWS prototype will be discussed supported with experimental testing analysis under controlled laboratory conditions. Through dynamic building energy modeling approach and Genetic-Algorithm (GA) based optimization technique, the best control strategies for SWS are developed to enhance the electrical load flexibility and demand response capability of US office buildings located in select cities representative of common US climates. In particular, optimized controls are evaluated to assess the potential of using the SWS technology to enhance not only the energy efficiency of office buildings but also their demand response in order to meet the grid requirements while maintaining acceptable indoor thermal comfort levels. Through the analysis results, the potential of using SWS combined with other load shifting strategies such as precooling protocols as well as machine learning techniques as grid-interactive efficient building (GEB) strategies is thoroughly investigated and quantified for a select sets of electricity rates and US climates.


Optimal Controls of Switchable Window Systems for Grid-Interactive Efficient Buildings

Division / Sponsor:
Advanced Energy Systems Division (AESD) & Solar Energy Division (SED)

Paper Proceedings: https://asmedigitalcollection.asme.org/ES/ES2020/volume/83631

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