<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jianjun Xia</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Qi Shen</style></author><author><style face="normal" font="default" size="100%">Wei Feng</style></author><author><style face="normal" font="default" size="100%">Le Yang</style></author><author><style face="normal" font="default" size="100%">Piljae Im</style></author><author><style face="normal" font="default" size="100%">Alison Lu</style></author><author><style face="normal" font="default" size="100%">Mahabir Bhandari</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Building Energy Use Data Between the United States and China</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">comparison</style></keyword><keyword><style  face="normal" font="default" size="100%">data analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">data model</style></keyword><keyword><style  face="normal" font="default" size="100%">Energy benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">energy monitoring system</style></keyword><keyword><style  face="normal" font="default" size="100%">energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">retrofit</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">78</style></volume><pages><style face="normal" font="default" size="100%">165-175</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Buildings in the United States and China consumed 41% and 28% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.–China Clean Energy Research Center for Building Energy Efficiency. The goal is to 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. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-6669E</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Le Yang</style></author><author><style face="normal" font="default" size="100%">David Hill</style></author><author><style face="normal" font="default" size="100%">Wei Feng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data and Analytics to Inform Energy Retrofit of High Performance Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Analytics</style></keyword><keyword><style  face="normal" font="default" size="100%">data model</style></keyword><keyword><style  face="normal" font="default" size="100%">Energy benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">High performance buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">retrofit</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><volume><style face="normal" font="default" size="100%">126</style></volume><pages><style face="normal" font="default" size="100%">90-106</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Buildings consume more than one-third of the world’s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis – energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20% of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Wei Feng</style></author><author><style face="normal" font="default" size="100%">Alison Lu</style></author><author><style face="normal" font="default" size="100%">Jianjun Xia</style></author><author><style face="normal" font="default" size="100%">Le Yang</style></author><author><style face="normal" font="default" size="100%">Qi Shen</style></author><author><style face="normal" font="default" size="100%">Piljae Im</style></author><author><style face="normal" font="default" size="100%">Mahabir Bhandari</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Energy Monitoring and Analysis</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2013</style></date></pub-dates></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;U.S. and China are the world&#039;s top two economics. Together they consumed one-third of the world&#039;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;Key research findings were summarized as follows:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Identified the need for a standard data model and platform to collect, process, analyze, and exchange building performance data due to different definitions of energy use and boundary, difficulty in exchanging data, and lack of current standards.&lt;/li&gt;&lt;li&gt;Compared energy monitoring systems to identify gaps, including iSagy, Pulse Energy, SkySpark, sMap, EPP, ION, and Metasys.&lt;/li&gt;&lt;li&gt;Contributed to develop a standard data model to represent energy use in buildings (ISO standard 12655 and a Chinese national standard)&lt;/li&gt;&lt;li&gt;Determined that buildings in the United States and China are very different in design, operation, maintenance, occupant behavior: U.S. buildings have more stringent comfort standards regarding temperature, ventilation, lighting, and hot-water use and therefore higher internal loads and operating hours, and China buildings having higher lighting energy use, seasonal HVAC operation, more operators, more use of natural ventilation, less outdoor ventilation air, and wider range of comfort temperature.&lt;/li&gt;&lt;li&gt;Completed data collection for six office buildings, one in UC Merced campus, one in Sacramento, one in Berkeley, one in George Tech campus, and two in Beijing.&lt;/li&gt;&lt;li&gt;Compiled a source book of 10 selected buildings in the United States and China with detailed descriptions of the buildings, data points, and monitoring systems, and containing energy analysis of each building and an energy benchmarking among all buildings.&lt;/li&gt;&lt;li&gt;Recognized limited availability of quality data, particularly with long periods of time-interval data, and general lack of value for good data and large datasets.&lt;/li&gt;&lt;li&gt;Compiled a building energy database, with detailed energy end use at 1-hour or 15-minute time interval, of six office buildings — four in the U.S. and two in China. The database is available to the public and is a valuable resource for building research.&lt;/li&gt;&lt;li&gt;Developed methods and used them in data analysis of building performance for the five buildings with adequate data, including energy benchmarking, profiling (daily, weekly, monthly), and diagnostics.&lt;/li&gt;&lt;li&gt;Recommended energy efficiency measures for building retrofit in both countries. U.S. buildings show more potential savings by reducing operation time, reducing plug-loads, expanding comfort temperature range, and turning off lights or equipment when not in use; while Chinese buildings can save energy by increasing lighting system efficiency, and improving envelope insulation and HVAC equipment efficiency.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;The research outputs from the project can help better understand energy performance of buildings, improve building operations to reduce energy waste and increase efficiency, identify retrofit opportunities for existing buildings, and provide guideline to improve the design of new buildings. The standardized energy monitoring and analysis platform as well as the collected real building data can also be used for other CERC projects that need building energy measurements, and be further linked to building energy benchmarking and rating/labeling systems.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-6640E</style></custom2></record></records></xml>