An hourly hybrid multi-variate change-point inverse model using short-term monitored data for annual prediction of building energy performance, part I: Background (1404-RP)

The primary purpose of the research was to develop analysis methodologies by which the time period for field monitoring of energy use in buildings can be reduced to less than a whole year while satisfying preset accuracy levels of annual energy performance verification. Such methodologies would be of great benefit to the ongoing efforts to spur the diffusion of high-performance buildings by actual monitoring and to energy service companies and energy professionals who need a more cost-effective and acceptable alternative to year-long monitoring. The analysis has been completed in detail at two different time scales: daily and hourly. The research revealed that (1) 2 weeks of hourly monitored data can be adequate for producing accurate long-term whole building energy predictions, provided the monitoring is taken at a correct time, and (2) adding more data to the regression model (extending the length of the short-term monitoring period) can, contrary to intuition, make the predictive model much poorer. The analysis with both hourly and daily data revealed that the proper monitoring period is highly dependent on the time at which the data is taken, with the best time to collect data being during the swing seasons. To determine the amount of short-term building energy-use data that would be enough to generate acceptable annual predictions, four different daily analysis methods were tested on year-long data sets from three buildings, and five different hourly analysis methods were tested on year-long data sets from over 40 buildings. Several analysis methods were proposed and studied based on the type of data available. These categories include use of: (1) ambient temperature data only, (2) simulated/monitored data, (3) year-long utility bills and a short monitored dataset, and (4) year-long utility bills only. Three application areas for research of this nature were identified: detailed audits, green building performance verification, and verification of post-retrofit claims using pre–post monitored data. The results of the studies using the daily scales are already published (Singh et al. 2013, 2014). This paper is the first of three papers reporting on the hourly scale methodology and results, and covers the background of the research undertaken, providing a detailed literature survey that was necessary for conducting the work.