Sponsor
Portland State University. Department of Mechanical and Materials Engineering
First Advisor
Sung Yi
Date of Publication
Winter 3-23-2017
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Mechanical Engineering
Department
Mechanical and Materials Engineering
Language
English
Subjects
Sustainable buildings -- Design and construction -- Decision making, Building -- Design and construction -- Energy conservation -- Simulation methods
DOI
10.15760/etd.5391
Physical Description
1 online resource (xii, 88 pages)
Abstract
Accommodating the continued increase in energy demand in the face of global climate change has been a worldwide concern. With buildings in the US consuming nearly 40% of national energy, a concerted effort must be given to reduce building energy consumption. As new buildings continue to improve their efficiency through more restrictive energy codes, the other 76.9 billion square feet of current building stock falls further behind. The rate at which current buildings are being retrofit is not enough and better tools are needed to access the benefits of retrofits and the uncertainties associated with them. This study proposes a stochastic method of building energy model calibration coupled with a monthly normative building simulation addressed in ISO 13890. This approach takes advantage of the great efficiency of Latin Hypercube Sampling and the lightweight normative building simulation method, to deliver a set of calibrated solutions to assess the effectiveness of energy conservation measure, making uncertainty a part of the modeling process. A case study on a mixed-use university building is conducted to show the strength and performance of this simple method. Limitations and future concerns are also addressed.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
http://archives.pdx.edu/ds/psu/19672
Recommended Citation
Johnson, Nicolas R., "Building Energy Model Calibration for Retrofit Decision Making" (2017). Dissertations and Theses. Paper 3507.
https://doi.org/10.15760/etd.5391