Skip to content Skip to navigation

Formalizing Assumptions to Document Limitations of Building Performance Measurement Systems

TitleFormalizing Assumptions to Document Limitations of Building Performance Measurement Systems
Publication TypeWorking Paper
Year of Publication2010
AuthorsMaile, T, Fischer, M, Bazjanac, V
Date Published08/2010
Publication Languageeng
KeywordsAssumptions, Building Energy Performance, Center for Integrated Facility Engineering, CIFE, Measurement, Stanford University
AbstractBuilding energy performance is often unknown or inadequately measured. When performance is measured, it is critical to understand the validity of the measured data before identifying performance problems. Limitations of measurement systems make adequate assessment of validity difficult. These limitations originate in the set of available data and in the functional parts of the measurement system. Previous research has used project-specific assumptions in an ad-hoc manner to describe these limitations, but the research has not compiled a list of critical measurement assumptions and a process to link the measurement assumptions to performance problems. To aid in the assessment of measured data, we present a list of critical measurement assumptions drawn from the existing literature and four case studies. These measurement assumptions describe the validity of measured data. Specifically, we explain the influence of sensing, data transmission, and data archiving. We develop a process to identify performance problems resulting from differences between measured and simulated data using the identified measurement assumptions. This paper validates existing measurement data sets based on known performance problems in a case study and shows that the developed list of critical measurement assumptions enables the identification of differences caused by measurement assumptions and exclude them from analysis of potential performance problems.
PDF Link
Citation Key672