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Robertson, Joseph

Publications and source records attributed to Robertson, Joseph.

25 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

OpenStudio® Fault Models Gem [SWR-15-23]

Overview of the OpenStudio® Fault Models Gem: Creating a comprehensive library of OpenStudio® fault models. Features: - Physics-based fault impact simulation within the capability of EnergyPlus®/OpenStudio® - Fault intensity implementation simulating how severe faults are (e.g., how much portion is fouled in the condenser heat exchanger) and estimating the impact of a fault in different fault intensities. - Fault evolution implementation simulating evolving/increasing fault intensity through certain period of time. Future goals: - what are common/typical faults in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)? - how often (e.g., incidence and prevalence) faults occur in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)?

Frank, Stephen↗
DOE OSTI2016

OpenStudio® Resources [SWR-07-40]

This repository includes a suite of simulation tests that can be used to validate new OpenStudio® model objects as well as ensure that objects continue to work after they are added. Each new OpenStudio Model object should ideally have two simulation tests associated with it: - a Ruby one which verifies the Ruby API and, - an OSM one that verifies the OSM file can be loaded with future versions of OpenStudio. Both tests should result in a simulation-ready OpenStudio Model that can be simulated using EnergyPlus®. Both of these tests are located in the /model/simulationtests directory, the easiest way to add a new test is to find a related existing test and modify it. When new tests are added they must be added to the model_tests.rb file.

Benne, Kyle↗
DOE OSTI2014

OpenStudio - Fault Modeling

This software record documents the OpenStudio fault model development portion of the Fault Detection and Diagnostics LDRD project.The software provides a suite of OpenStudio measures (scripts) for modeling typical HVAC system faults in commercial buildings and also included supporting materials: example projects and OpenStudio measures for reporting fault costs and energy impacts.

Frank, Stephen↗
DOE OSTI2013

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Assessment of the U.S. Department of Energy's Home Energy Scoring Tool

The National Renewable Energy Laboratory (NREL) conducted a series of assessments of the U.S. Department of Energy's (DOE) proposed Home Energy Scoring Tool (HEST). This report is an assessment of the 4/27/2012 release of HEST. Predictions of electric and natural gas consumption were compared with weather-normalized utility billing data for a mixture of newer and older homes located in Oregon, Wisconsin, Minnesota, North Carolina and Texas.

03 NATURAL GAS↗