Baseline information development for energy smart schools -- applied research, field testing and technology integration

Xu, Tengfang ; Piette, Mary Ann

Lawrence Berkeley National Laboratory

关键词: Energy Consumption;    Testing;    Windows;    Skylights;    Electricity;   

DOI  :  10.2172/838176
RP-ID  :  LBNL--54233
RP-ID  :  AC03-76SF00098
RP-ID  :  838176

美国|英语

来源: UNT Digital Library

【 摘 要 】

The original scope of work was to obtain and analyze existing and emerging data in four states: California, Florida, New York, and Wisconsin. The goal of this data collection was to deliver a baseline database or recommendations for such a database that could possibly contain window and daylighting features and energy performance characteristics of Kindergarten through 12th grade (K-12) school buildings (or those of classrooms when available). In particular, data analyses were performed based upon the California Commercial End-Use Survey (CEUS) databases to understand school energy use, features of window glazing, and availability of daylighting in California K-12 schools. The outcomes from this baseline task can be used to assist in establishing a database of school energy performance, assessing applications of existing technologies relevant to window and daylighting design, and identifying future R&D needs. These are in line with the overall project goals as outlined in the proposal. Through the review and analysis of this data, it is clear that there are many compounding factors impacting energy use in K-12 school buildings in the U.S., and that there are various challenges in understanding the impact of K-12 classroom energy use associated with design features of window glazing and skylight. First, the energy data in the existing CEUS databases has, at most, provided the aggregated electricity and/or gas usages for the building establishments that include other school facilities on top of the classroom spaces. Although the percentage of classroom floor area in schools is often available from the databases, there is no additional information that can be used to quantitatively segregate the EUI for classroom spaces. In order to quantify the EUI for classrooms, sub-metering of energy usage by classrooms must be obtained. Second, magnitudes of energy use for electricity lighting are not attainable from the existing databases, nor are the lighting levels contributed by artificial lighting or daylight. It is impossible to reasonably estimate the lighting energy consumption for classroom areas in the sample of schools studied in this project. Third, there are many other compounding factors that may as well influence the overall classroom energy use, e.g., ventilation, insulation, system efficiency, occupancy, control, schedules, and weather. Fourth, although we have examined the school EUI grouped by various factors such as climate zones, window and daylighting design features from the California databases, no statistically significant associations can be identified from the sampled California K-12 schools in the current California CEUS. There are opportunities to expand such analyses by developing and including more powerful CEUS databases in the future. Finally, a list of parameters is recommended for future database development and for use of future investigation in K-12 classroom energy use, window and skylight design, and possible relations between them. Some of the key parameters include: (1) Energy end use data for lighting systems, classrooms, and schools; (2) Building design and operation including features for windows and daylighting; and (3) Other key parameters and information that would be available to investigate overall energy uses, building and systems design, their operation, and services provided.