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Title: Building Energy Monitoring and Analysis

Abstract

U.S. and China are the world’s top two economics. Together they consumed one-third of the world’s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services. Buildings in the US and China consumed about 40% and 25% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change. This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current buildingmore » energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.« less

Authors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Environmental Energy Technologies Division
OSTI Identifier:
1134237
Report Number(s):
LBNL-6640E
DOE Contract Number:
DE-AC02-05CH11231
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION

Citation Formats

Hong, Tianzhen, Feng, Wei, Lu, Alison, Xia, Jianjun, Yang, Le, Shen, Qi, Im, Piljae, and Bhandari, Mahabir. Building Energy Monitoring and Analysis. United States: N. p., 2013. Web. doi:10.2172/1134237.
Hong, Tianzhen, Feng, Wei, Lu, Alison, Xia, Jianjun, Yang, Le, Shen, Qi, Im, Piljae, & Bhandari, Mahabir. Building Energy Monitoring and Analysis. United States. doi:10.2172/1134237.
Hong, Tianzhen, Feng, Wei, Lu, Alison, Xia, Jianjun, Yang, Le, Shen, Qi, Im, Piljae, and Bhandari, Mahabir. Sat . "Building Energy Monitoring and Analysis". United States. doi:10.2172/1134237. https://www.osti.gov/servlets/purl/1134237.
@article{osti_1134237,
title = {Building Energy Monitoring and Analysis},
author = {Hong, Tianzhen and Feng, Wei and Lu, Alison and Xia, Jianjun and Yang, Le and Shen, Qi and Im, Piljae and Bhandari, Mahabir},
abstractNote = {U.S. and China are the world’s top two economics. Together they consumed one-third of the world’s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services. Buildings in the US and China consumed about 40% and 25% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change. This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.},
doi = {10.2172/1134237},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jun 01 00:00:00 EDT 2013},
month = {Sat Jun 01 00:00:00 EDT 2013}
}

Technical Report:

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  • The report titled ''BEMA - Building Energy Monitoring Analysis: A Short-Term Measurement of Building Thermal Performance'' represents the work during the period October 1987 through October 1988. Also enclosed is a list of meetings, seminars and workshops conducted during the same period and the final financial report. View graphs for the ASHRAE conference in Ottawa are also enclosed. The purpose of this project is to transfer the short-term monitoring technology to the private sector. To that end, NAHB/NRC has developed a program which is being funded by New York Energy Research and Development Authority to commercialize the technology developed undermore » the DOE contract. Enclosed is a brief discussion of the project and our collaboration with SERI on the project.« less
  • This report summarizes a longer report entitled PSTAR - Primary and Secondary Terms Analysis and Renormalization. A Unified Approach to Building Energy Simulations and Short-Term Monitoring. These reports highlight short-term testing for predicting long-term performance of residential buildings. In the PSTAR method, renormalized parameters are introduced for the primary terms such that the renormalized energy balance equation is best satisfied in the least squares sense; hence, the name PSTAR. Testing and monitoring the energy performance of buildings has several important applications, among them: extrapolation to long-term performance, refinement of design tools through feedback from comparing design versus actual parameters, building-as-a-calorimetermore » for heating, ventilating, and air conditioning (HVAC) diagnostics, and predictive load control. By combining realistic building models, simple test procedures, and analysis involving linear equations, PSTAR provides a powerful tool for analyzing building energy as well as testing and monitoring. It forms the basis for the Short-Term Energy Monitoring (STEM) project at SERI. 3 figs., 1 tab.« less
  • This report presents a unified method of hourly simulation of a building and analysis of performance data. The method is called Primary and Secondary Terms Analysis and Renormalization (PSTAR). In the PSTAR method, renormalized parameters are introduced for the primary terms such that the renormalized energy balance equation is best satisfied in the least squares sense, hence, the name PSTAR. PSTAR allows extraction of building characteristics from short-term tests on a small number of data channels. These can be used for long-term performance prediction (''ratings''), diagnostics, and control of heating, ventilating, and air conditioning systems (HVAC), comparison of design versusmore » actual performance, etc. By combining realistic building models, simple test procedures, and analysis involving linear equations, PSTAR provides a powerful tool for analyzing building energy as well as testing and monitoring. It forms the basis for the Short-Term Energy Monitoring (STEM) project at SERI.« less
  • Three independent tasks had been performed (Stetzenbach 2008, Stetzenbach 2008b, Stetzenbach 2009) to measure a variety of parameters in normative buildings across the United States. For each of these tasks 10 buildings were selected as normative indoor environments. Task 1 focused on office buildings, Task 13 focused on public schools, and Task 0606 focused on high performance buildings. To perform this task it was necessary to restructure the database for the Indoor Environmental Quality (IEQ) data and the Sound measurement as several issues were identified and resolved prior to and during the transfer of these data sets into SPSS. Duringmore » overview discussions with the statistician utilized in this task it was determined that because the selection of indoor zones (1-6) was independently selected within each task; zones were not related by location across tasks. Therefore, no comparison would be valid across zones for the 30 buildings so the by location (zone) data were limited to three analysis sets of the buildings within each task. In addition, differences in collection procedures for lighting were used in Task 0606 as compared to Tasks 01 & 13 to improve sample collection. Therefore, these data sets could not be merged and compared so effects by-day data were run separately for Task 0606 and only Task 01 & 13 data were merged. Results of the statistical analysis of the IEQ parameters show statistically significant differences were found among days and zones for all tasks, although no differences were found by-day for Draft Rate data from Task 0606 (p>0.05). Thursday measurements of IEQ parameters were significantly different from Tuesday, and most Wednesday measures for all variables of Tasks 1 & 13. Data for all three days appeared to vary for Operative Temperature, whereas only Tuesday and Thursday differed for Draft Rate 1m. Although no Draft Rate measures within Task 0606 were found to significantly differ by-day, Temperature measurements for Tuesday and Thursday showed variation. Moreover, Wednesday measurements of Relative Humidity within Task 0606 varied significantly from either Tuesday or Thursday. The majority of differences in IEQ measurements by-zone were highly significant (p<0.001), with the exception of Relative Humidity in some buildings. When all task data were combined (30 buildings) neither the airborne culturable fungi nor the airborne non-culturable spore data differed in the concentrations found at any indoor location in terms of day of collection. However, the concentrations of surface-associated fungi varied among the day of collection. Specifically, there was a lower concentration of mold on Tuesday than on Wednesday, for all tasks combined. As expected, variation was found in the concentrations of both airborne culturable fungi and airborne non-culturable fungal spores between indoor zones (1-6) and the outdoor zone (zone 0). No variation was found among the indoor zones of office buildings for Task 1 in the concentrations of airborne culturable fungi. However, airborne non-culturable spores did vary among zones in one building in Task 1 and variation was noted between zones in surface-associated fungi. Due to the lack of multiple lighting measurements for Tasks 13 and 0606, by-day comparisons were only performed for Task 1. No statistical differences were observed in lighting with respect to the day of collection. There was a wide range of variability by-zone among seven of the office buildings. Although few differences were found for the brightest illumination of the worksurface (IllumWkSfcBrtst) and the darkest illumination of the worksurface (IllumWkSfcDrkst) in Task 1, there was considerable variation for these variables in Task 13 and Task 0606 (p < 0.001). Other variables that differed by-zone in Task 13 include CombCCT and AmbCCT1 for S03, S07, and S08. Additionally, AmbChromX1, CombChromY, and CombChromX varied by-zone for school buildings S02, S04, and S05, respectively. Although all tasks demonstrated significant differences in sound measurements by zone, some of the buildings within each task did not appear to differ in sound quality. Hence, post-hoc tests were not appropriate and individual zones were not compared for these buildings. It is interesting to note that sound measurements in some buildings were widely varied with most zone comparisons and other buildings varied between only a few zones.« less
  • This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyzemore » good building energy data to provide valuable and actionable information for key stakeholders.« less