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Revisions to the SRCC rating process for solar water heaters : preprint

著者: J Burch; National Renewable Energy Laboratory (U.S.)
出版: Golden, CO : National Renewable Energy Laboratory, [2012]
シリーズ: Conference paper (National Renewable Energy Laboratory (U.S.)), 5500-54540.
エディション/フォーマット:   電子書籍 : Document : Conference publication : National government publication : English
データベース:WorldCat
概要:
In the United States, annual performance ratings for solar water heaters are computed with component-based simulation models driven by typical meteorological year weather and specified water draw. Changes in the process are being implemented to enhance credibility through increased transparency and accuracy. Changes to the process include using a graphical rather than text-based model-building tool, performing  続きを読む
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資料の種類: Conference publication, Document, Government publication, National government publication, インターネット資料
ドキュメントの種類: インターネットリソース, コンピューターファイル
すべての著者/寄与者: J Burch; National Renewable Energy Laboratory (U.S.)
OCLC No.: 808501106
注記: Title from title screen (viewed Aug. 28, 2012).
"June 2012."
"Presented at the 2012 World Renewable Energy Forum, Denver, Colorado, May 13-17, 2012."
物理形態: 1 online resource (8 pages) : color illustrations.
詳細: Full text available via Internet in .pdf format. Adobe Acrobat Reader required.
シリーズタイトル: Conference paper (National Renewable Energy Laboratory (U.S.)), 5500-54540.
責任者: J. Burch [and others].

概要:

In the United States, annual performance ratings for solar water heaters are computed with component-based simulation models driven by typical meteorological year weather and specified water draw. Changes in the process are being implemented to enhance credibility through increased transparency and accuracy. Changes to the process include using a graphical rather than text-based model-building tool, performing analytical tests on all components and systems, checking energy balances on every component, loop, and system at every time step, comparing the results to detect outliers and potential errors, and documenting the modeling process in detail. Examples of changes in ratings are shown, along with analytical and comparative testing results.

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