Elsevier

Energy and Buildings

Volume 43, Issue 11, November 2011, Pages 3289-3294
Energy and Buildings

Short communication
Plug-load densities for energy analysis: K-12 schools

https://doi.org/10.1016/j.enbuild.2011.08.030Get rights and content

Abstract

Benchmarking plug-load densities is essential to bypass arbitrary and/or incorrect inputs used in building energy analysis. As more building simulationists play a decision-making role for the design team, they tend to lean on building energy standards and guidelines for preliminary inputs such as plug-load densities. It is necessary for building energy standards and rating systems to implement plug-load density benchmarks to reward design teams in their efforts to reduce plug-load energy use. Using case study buildings, this paper establishes benchmark plug-load densities for K-12 schools under two new categories – classrooms with computers and classrooms without computers. Eighteen K-12 schools including 9 elementary, 2 middle, and 7 high schools are assessed for actual plug-load densities. For the same case study buildings, four existing approaches – NREL, COMNET, ASHRAE 90.1-1989, and Title-24 are evaluated for plug-load densities. Results show under- and over-estimation of plug-load densities over actual densities. The development of benchmark for K-12 schools will pave way for instituting targets for trimming plug-load densities in new and retrofit building projects.

Highlights

► Establishes plug-load densities for use in energy simulation of K-12 schools under two new categories - classrooms with computers and classrooms without computers. ► Alleviates ambiguity related to applying plug-load densities for energy simulation of K-12 schools. ► Paves way for instituting targets for trimming down plug-load densities in new and retrofit K-12 school building projects.

Introduction

Energy savings in Miscellaneous Electrical Loads (MELs) has noticeably lagged behind other building energy end uses and, unquestionably, a critical research gap to achieve Net Zero Energy performance goals. K-12 school buildings are no exception. Several researches were conducted to study energy efficiency in school buildings such as optimal ventilation based on occupancy [1], [2], [3] and other energy assessments [4], [5]. Yet the major impediment to optimizing building energy use is the reduction of plug-load densities. Benchmarking plug-load densities is essential to bypass arbitrary and/or incorrect inputs used in building energy analysis. It is necessary for building energy standards and rating systems to implement plug-load density benchmarks to reward design teams in their efforts to reduce plug-load energy use. Among others, building energy analysis is conducted to show compliance for US Green Building Council's LEED™ rating system [6]. As more building simulationists play a decision-making role for the design team, they tend to lean on building energy standards and guidelines for preliminary inputs such as plug-load densities. LEED™ advocates ASHRAE Standard 90.1-2007 User Manual's [7] recommended receptacle densities originally adopted from ASHRAE Standard 90.1-1989 [8]. Based on this, recommended plug-load densities for K-12 school buildings is 5.38 W/m2. This density value has been a challenge for early design decision-making, as it does not relate to today's technology intensive receptacle requirements. These are largely under-estimated values given today's usage patterns of computers and other electronic equipment such as classroom computers, projectors, smartboards, and surround sound systems. This discrepancy may lead to unrealistic determination of energy use savings. Moreover, in K-12 schools, technological advancements in teaching methodology present an opportunity to “right-size” equipment through conscious decision-making. Specialized curriculum- driven schools such as “science schools,” use far more energy to run computing applications as compared to typical schools offering greater prospects for optimal design. Yet, plug-load density benchmarks for K-12 school buildings that incorporate technological advancements in classroom and teaching methodology is non-existent.

For benchmarking, plug-load densities may be calculated. Equipment nominal power data and diversity factors are used to calculate plug-load densities for energy analysis. Equipment nominal power and nameplate rating considerably differs during typical operation. Nominal power may be determined through monitoring average power drawn; the ratio of this average power drawn to nameplate rating is the load factor [9]. However, not all equipment peaks at the same time to the building's peak load. For example, portions of equipment may be in idle mode. The probability of actual to estimated operation is its diversity factor.

Only a few building energy standards, guidelines, and technical reports discuss either plug-load densities explicitly or a methodology to compute the same. Few noteworthy literatures are discussed below:

ASHRAE 90.1-1989 Standard [8]. This is a standard for energy-efficient design of buildings except low-rise residential buildings. This standard discusses acceptable receptacle power densities for several building types. These values are referenced in ASHRAE 90.1-2007 User Manual, table G-B and the LEED™ Reference Guide for Green Building Design and Construction [6]. The building types discussed include assembly, health/institutional, hotel/motel, light manufacturing, office, parking garage, restaurant, retail, school, and warehouse. Health/institutional and restaurant/warehouse building types represent the highest (10.76 W/m2) and lowest (1.08 W/m2) recommended plug-load densities respectively.

California Energy Commission (CAC) Report on office plug-load field monitoring [10]. This report discusses recommendations for near- and long-term strategies to reduce plug-load energy consumption based on data collection and analysis of California's office plug-loads. This report lists average power data for office equipment, however, does not include diversity factor [11].

National Renewable Energy Laboratory's (NREL) technical report on methodology for modeling building energy performance across the commercial sector [12]. In this report, nominal peak power data is estimated based on a count of computers and other equipment in the space. This, then, is used to calculate plug-load densities (P)P=(CsdPDsd+PDmisc)×dCsd is scale coefficient to scale power density from PDsd, PDsd is power densities of surveyed equipment listed in table C-24 “mean nominal peak power levels of surveyed devices, PDmisc is the power density of devices that are independent of the devices included in table C-25 of the report, and d is a scheduling diversity factor included in table C-25 of the report.

Scale coefficients and assumed power density of independent devices used in this technical report are based on expert opinions and were eventually altered during calibration process that utilized 2003 Commercial Building Energy Consumption Survey (CBECS) data. The plug-load densities of office equipment used in NREL technical report are based on survey conducted in 2002.

ASHRAE Handbook – Fundamentals, Chapter 18: Nonresidential Cooling and Heating Load Calculations [13]. This handbook provides plug-load densities for offices. Plug-load densities for K-12 schools is not provided in this handbook, however, average power consumption of desktop computers, laptops, flat-panel monitors, and other office equipment data are provided. These data were originally developed by Hosni and Beck [14].

California Title 24 Standard [15]. This report is California's energy efficiency standards for residential and nonresidential buildings. The standard prescribes plug-load power densities for several building types including schools. Title 24's table N2-5 and N2-6 discusses for whole building and space level densities.

US Department of Energy's Buildings Energy Data Book [16]. This guideline discusses plug-load densities for several building types including office, retail, schools, and hospitals. Schools and hospital densities were discussed under pre-1980 and post-1980 categories. However, the plug-load density for schools remained constant from the pre-1980 to post-1980.

Commercial Energy Services Network (COMNET) Guidelines [17]. COMNET is designed to support existing standards and modeling software and to build off existing credentialing systems. COMNET has adopted NREL procedures used for plug-load density calculations except different scale coefficients and diversity factors are introduced to accommodate all building and space types. COMNET provides three methods for computing plug-load density. If detailed information is not available, Method 1 is used. In Method 2, a scale coefficient of 1.0 is used. Method 3 is similar to Method 2, except that it allows taking credit for plug-load energy reduction.

Advanced Energy Design Guide (AEDG) for K-12 Schools [18]. This guide lists plug-load densities for elementary, middle, and high schools derived from equipment peak power and the expert opinion of project committee. Diversity factors are noticeably excluded in the equipment peak power listed. Without the inclusion of average power to capture actual usage patterns of equipment, it may be difficult to ascertain the accuracy of these densities.

Additional research work related to office and K-12 school building types are listed in Table 1.

For the same building project, applying plug-load densities derived from the approaches listed above may result in different plug-load energy use. This may pose dilemma for early design decision-making especially when it is crucial to “right-size” the equipment. Issues related to under- or over-sizing is well documented [9], [20].

Using case study buildings, this paper establishes benchmark plug-load densities for K-12 schools under two new categories – classrooms with computers and classrooms without computers. Eighteen K-12 schools including 9 elementary, 2 middle, and 7 high schools are assessed for actual plug-load densities. For the same case study buildings, four existing approaches – NREL, COMNET, ASHRAE 90.1-1989, and Title-24 are evaluated for plug-load densities. Results show under- and over-estimation of plug-load densities over actual densities. The development of benchmark for K-12 schools will pave way for instituting targets for trimming down plug-load densities in new and retrofit building projects.

Section snippets

Plug-load assessment of K-12 schools

For this study, eighteen K-12 schools in California are assessed for evaluating plug-load densities. The assessment is carried out in four steps:

Step 1

Survey of K-12 schools

Document survey dataset includes 9 elementary, 2 middle, and 7 high schools, Table 2. In order to determine plug-load density relevant to today's technological advancements in teaching techniques and to accommodate to changes that may ensue in near future, the assessment consists of buildings that were either constructed in 2011

Conclusions

Benchmarking plug-load density targets is fundamental for reducing plug-load energy use in new and retrofit building projects. Such densities must be derived using most recent equipment datasets and have to accommodate for future technology expansion in classrooms. Furthermore, with greater emphasis on math–science–technology curriculum in K-12 schools, we believe that all K-12 schools will transition to include computers in classrooms in near future. Based on the study, for a typical K-12

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