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Measured Peak Equipment Loads in Laboratories

Description: This technical bulletin documents measured peak equipment load data from 39 laboratory spaces in nine buildings across five institutions. The purpose of these measurements was to obtain data on the actual peak loads in laboratories, which can be used to rightsize the design of HVAC systems in new laboratories. While any given laboratory may have unique loads and other design considerations, these results may be used as a 'sanity check' for design assumptions.
Date: September 12, 2007
Creator: Mathew, Paul A.
Partner: UNT Libraries Government Documents Department

Use of Quantitative Uncertainty Analysis to Support M&VDecisions in ESPCs

Description: Measurement and Verification (M&V) is a critical elementof an Energy Savings Performance Contract (ESPC) - without M&V, thereisno way to confirm that the projected savings in an ESPC are in factbeing realized. For any given energy conservation measure in an ESPC,there are usually several M&V choices, which will vary in terms ofmeasurement uncertainty, cost, and technical feasibility. Typically,M&V decisions are made almost solely based on engineering judgmentand experience, with little, if any, quantitative uncertainty analysis(QUA). This paper describes the results of a pilot project initiated bythe Department of Energy s Federal Energy Management Program to explorethe use of Monte-Carlo simulation to assess savings uncertainty andthereby augment the M&V decision-making process in ESPCs. The intentwas to use QUA selectively in combination with heuristic knowledge, inorder to obtain quantitative estimates of the savings uncertainty withoutthe burden of a comprehensive "bottoms-up" QUA. This approach was used toanalyze the savings uncertainty in an ESPC for a large federal agency.The QUA was seamlessly integrated into the ESPC development process andthe incremental effort was relatively small with user-friendly tools thatare commercially available. As the case study illustrates, in some casesthe QUA simply confirms intuitive or qualitative information, while inother cases, it provides insight that suggests revisiting the M&Vplan. The case study also showed that M&V decisions should beinformed by the portfolio risk diversification. By providing quantitativeuncertainty information, QUA can effectively augment the M&Vdecision-making process as well as the overall ESPC financialanalysis.
Date: May 11, 2005
Creator: Mathew, Paul A.; Koehling, Erick & Kumar, Satish
Partner: UNT Libraries Government Documents Department

Advanced Benchmarking for Complex Building Types: Laboratories as an Exemplar

Description: Complex buildings such as laboratories, data centers and cleanrooms present particular challenges for energy benchmarking because it is difficult to normalize special requirements such as health and safety in laboratories and reliability (i.e., system redundancy to maintain uptime) in data centers which significantly impact energy use. For example, air change requirements vary widely based on the type of work being performed in each laboratory space. We present methods and tools for energy benchmarking in laboratories, as an exemplar of a complex building type. First, we address whole building energy metrics and normalization parameters. We present empirical methods based on simple data filtering as well as multivariate regression analysis on the Labs21 database. The regression analysis showed lab type, lab-area ratio and occupancy hours to be significant variables. Yet the dataset did not allow analysis of factors such as plug loads and air change rates, both of which are critical to lab energy use. The simulation-based method uses an EnergyPlus model to generate a benchmark energy intensity normalized for a wider range of parameters. We suggest that both these methods have complementary strengths and limitations. Second, we present"action-oriented" benchmarking, which extends whole-building benchmarking by utilizing system-level features and metrics such as airflow W/cfm to quickly identify a list of potential efficiency actions which can then be used as the basis for a more detailed audit. While action-oriented benchmarking is not an"audit in a box" and is not intended to provide the same degree of accuracy afforded by an energy audit, we demonstrate how it can be used to focus and prioritize audit activity and track performance at the system level. We conclude with key principles that are more broadly applicable to other complex building types.
Date: August 1, 2010
Creator: Mathew, Paul A.; Clear, Robert; Kircher, Kevin; Webster, Tom; Lee, Kwang Ho & Hoyt, Tyler
Partner: UNT Libraries Government Documents Department

Labs21 environmental performance criteria Version 2.0

Description: Laboratory facilities present a unique challenge for energy efficient and sustainable design, with their inherent complexity of systems, health and safety requirements, long-term flexibility and adaptability needs, energy use intensity, and environmental impacts. The typical laboratory is about five times as energy intensive as a typical office building and costs about three times as much per unit area. The Labs21 Environmental Performance Criteria (EPC) is a rating system for use by laboratory building project stakeholders to assess the environmental performance of laboratory facilities. Currently, the U.S. Green Building Council's LEED{trademark} Rating System is the primary tool used. However, LEED{trademark} was designed for U.S. commercial office buildings and as such, lacks some attributes essential to the sustainable design of this unique and complex building type. To facilitate widespread use and to avoid ''re-inventing the wheel'' this effort builds on the existing LEED{trademark} Rating System 2.0.
Date: October 1, 2002
Creator: Mathew, Paul A.
Partner: UNT Libraries Government Documents Department

Cleanroom Energy Efficiency: Metrics and Benchmarks

Description: Cleanrooms are among the most energy-intensive types of facilities. This is primarily due to the cleanliness requirements that result in high airflow rates and system static pressures, as well as process requirements that result in high cooling loads. Various studies have shown that there is a wide range of cleanroom energy efficiencies and that facility managers may not be aware of how energy efficient their cleanroom facility can be relative to other cleanroom facilities with the same cleanliness requirements. Metrics and benchmarks are an effective way to compare one facility to another and to track the performance of a given facility over time. This article presents the key metrics and benchmarks that facility managers can use to assess, track, and manage their cleanroom energy efficiency or to set energy efficiency targets for new construction. These include system-level metrics such as air change rates, air handling W/cfm, and filter pressure drops. Operational data are presented from over 20 different cleanrooms that were benchmarked with these metrics and that are part of the cleanroom benchmark dataset maintained by Lawrence Berkeley National Laboratory (LBNL). Overall production efficiency metrics for cleanrooms in 28 semiconductor manufacturing facilities in the United States and recorded in the Fabs21 database are also presented.
Date: July 7, 2010
Creator: Initiative, International SEMATECH Manufacturing; Mathew, Paul A.; Tschudi, William; Sartor, Dale & Beasley, James
Partner: UNT Libraries Government Documents Department