<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Blum</style></author><author><style face="normal" font="default" size="100%">Guanjing Lin</style></author><author><style face="normal" font="default" size="100%">Michael Spears</style></author><author><style face="normal" font="default" size="100%">Janie Page</style></author><author><style face="normal" font="default" size="100%">Jessica Granderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">When Data Analytics Meet Site Operation: Benefits and Challenges</style></title><secondary-title><style face="normal" font="default" size="100%">2018 ACEEE Summer Study on Energy Efficiency in Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2018</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>46</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Evan Mills</style></author><author><style face="normal" font="default" size="100%">Jessica Granderson</style></author><author><style face="normal" font="default" size="100%">Wanyu R. Chan</style></author><author><style face="normal" font="default" size="100%">Richard C. Diamond</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Bruce Nordman</style></author><author><style face="normal" font="default" size="100%">Paul A. Mathew</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author><author><style face="normal" font="default" size="100%">Gerald Robinson</style></author><author><style face="normal" font="default" size="100%">Stephen E. Selkowitz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Green, Clean, &amp; Mean: Pushing the Energy Envelope in Tech Industry Buildings</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Lawrence Berkeley National Laboratory</style></publisher><abstract><style face="normal" font="default" size="100%">&lt;p&gt;When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business.&lt;/p&gt;&lt;p&gt;The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day.&lt;/p&gt;&lt;p&gt;There is a degree of existing documentation of efforts to design, build, and operate facilities in the technology sector. However, the material is fragmented and typically looks only at a single company, or discrete projects within a company.Yet, there is no single resource for corporate planners and decision makers that takes stock of the opportunities and documents sector-specific case studies in a structured manner. This report seeks to fill that gap, doing so through a combination of generalized technology assessments (“Key Strategies”) and case studies (“Flagship Projects”).&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-1005070E</style></custom2></record></records></xml>