Engineering topics

Goldwasser, David

Publications and source records attributed to Goldwasser, David.

14 records

DOE OSTI2023

OpenStudio®-ERI (Energy Rating Index (ERI) Workflow) [SWR-18-72] 1.7.0 Released 12/14/2023

The OpenStudio®-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio®/EnergyPlus® simulation platform. The building description is provided in an HPXML file format. The project supports: - ANSI/RESNET/ICC 301© Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index - ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path - IECC ERI Compliance Alternative (Section R406) - DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/

Horowitz, Scott↗

DOE OSTI2022

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf The purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded. Supported Tools The default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux. Dependencies Install OpenStudio® 3.4.0 make sure command line can recognize the 'openstudio' command This includes EnergyPlus® 22.1 Install Ruby on your system if it isn't already setup. 2.7 is used for development but other versions may work Since OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio. Install RubyXL Ruby gem This is used to modify Microsoft Excel spreadsheets Install Parallel Ruby gem This allows the CLI to run simulations in parallel

Goldwasser, David↗

DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Representing Small Commercial Building Faults in EnergyPlus, Part II: Model Validation

Automated fault detection and diagnosis (AFDD) tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, access to high-quality training data for such algorithms is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part II (this paper) first presents a methodology of validating fault models with OpenStudio and then presents validation results, which are compared against measurements from a reference building. We discuss the results of our experiments with eight different faults in the reference building (a total of 39 different baseline and faulted scenarios), including our methodology for using fault models along with the reference building model to simulate the same faulted scenarios. Then, we present validation of the fault models by comparing results of simulations and experiments either quantitatively or qualitatively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Representing Small Commercial Building Faults in EnergyPlus, Part I: Model Development

Small commercial buildings (those with less than approximately 1000 m2 of total floor area) often do not have access to cost-effective automated fault detection and diagnosis (AFDD) tools for maintaining efficient building operations. AFDD tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, such algorithms require access to high-quality training data that is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part I (this paper) presents a library of fault models, including detailed descriptions of each fault model structure and their implementation with EnergyPlus. This paper also discusses a case study of training data set generation, representing an actual building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Advances in Calibration of Building Energy Models to Time Series Data: Preprint

Advanced building analytics and control applications such as fault detection and diagnostics and model predictive control benefit from building energy models calibrated to time series data. In this paper, we present best practices for aligning EnergyPlus (TM) model time series output with measured building performance. These include the use of subcalibration procedures to fine-tune envelope, heat transfer, and mechanical system parameters; initialization of zone temperatures to match observed conditions at the beginning of each calibration period; and calculation of calibration metrics across multiple run periods using a new OpenStudio reporting measure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Moving K-12 Zero Energy Schools to the Mainstream: Establishing Design Guidelines and Energy Targets: Preprint

K-12 school buildings are ideal candidates to lead the market shift from buildings that consume energy to buildings that produce as much renewable energy as they use, and there are now resources available to guide owners and project teams as they make that shift. Chief among them is the Advanced Energy Design Guide for K-12 School Buildings: Achieving Zero Energy (K-12 ZE AEDG). Starting with a feasibility study to prove that zero energy schools were possible, a committee of industry experts used extensive energy modeling to create a set of energy use intensity allowances for school buildings such that on-site renewable energy could meet the buildings' energy loads . These energy targets were compared with the energy use intensities of a limited number of schools that have achieved very high levels of energy performance. The allowances represent a 'zero energy ready' (rather than zero energy) school, because in many situations the ability to use on-site renewable sources is limited by utilities, policies, or economics. From these targets, the guidance for achieving a zero energy school was created and developed into the K-12 ZE AEDG, which covers the process of designing and building zero energy schools from the perspective of an owner and a project team. The K-12 ZE AEDG advocates setting an absolute energy target before design begins. The K-12 ZE AEDG also contains practical, cost-effective strategies for achieving the energy target and outreach approaches and disseminating these market-friendly strategies to design and school owner communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

ADVANCES IN CALIBRATION OF BUILDING ENERGY MODELS TO TIME SERIES DATA

Advanced building analytics and control applications, such as fault detection and diagnostics and model predictive control, benefit from building energy models calibrated to time series data. This paper recommends best practices for aligning EnergyPlus™ model time series output with measured building performance. These include the use of subcalibration procedures to fine-tune envelope, heat transfer, and mechanical system parameters; initialization of zone temperatures to match observed conditions at the beginning of each calibration period; and calculation of calibration metrics across multiple run periods using a new OpenStudio reporting measure.

Goldwasser, David↗

DOE OSTI2018

Moving K-12 Zero Energy Schools to the Mainstream: Establishing Design Guidelines and Energy Targets

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf For EnergyPlus® and OpenStudio®, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio. The initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting. The model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.

Goldwasser, David↗

DOE OSTI2016

Technical Feasibility Study for Zero Energy K-12 Schools

This technical feasibility study provides documentation and research results supporting a possible set of strategies to achieve source zero energy K-12 school buildings as defined by the U.S. Department of Energy (DOE) zero energy building (ZEB) definition (DOE 2015a). Under this definition, a ZEB is an energy-efficient building in which, on a source energy basis, the actual annual delivered energy is less than or equal to the on-site renewable exported energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Analysis of Different Methods for Computing Source Energy in the Context of Zero Energy Buildings

Building energy consumption can only be measured at the site or at the point of utility interconnection with a building. Often, to evaluate the total energy impact, this site-based energy consumption is translated into source energy, that is, the energy at the point of fuel extraction. Consistent with this approach, the U.S. Department of Energy's (DOE) definition of zero energy buildings uses source energy as the metric to account for energy losses from the extraction, transformation, and delivery of energy. Other organizations, as well, use source energy to characterize the energy impacts. Four methods of making the conversion from site energy to source energy were investigated in the context of the DOE definition of zero energy buildings. These methods were evaluated based on three guiding principles--improve energy efficiency, reduce and stabilize power demand, and use power from nonrenewable energy sources as efficiently as possible. This study examines relative trends between strategies as they are implemented on very low-energy buildings to achieve zero energy. A typical office building was modeled and variations to this model performed. The photovoltaic output that was required to create a zero energy building was calculated. Trends were examined with these variations to study the impacts of the calculation method on the building's ability to achieve zero energy status. The paper will highlight the different methods and give conclusions on the advantages and disadvantages of the methods studied.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Technical Feasibility Study for Zero Energy K-12 Schools

A simulation-based technical feasibility study was completed to show the types of technologies required to achieve ZEB status with this building type. These technologies are prioritized across the building's subsystem such that design teams can readily integrate the ideas. Energy use intensity (EUI) targets were established for U.S. climate zones such that K-12 schools can be zero-ready or can procure solar panels or other renewable energy production sources to meet the zero energy building definition. Results showed that it is possible for K-12 schools to achieve zero energy when the EUI is between 20 and 26 kBtu/ft2/yr. Temperate climates required a smaller percentage of solar panel coverage than very hot or very cold climates. The paper provides a foundation for technically achieving zero energy schools with a vision of transforming the school construction market to mainstream zero energy buildings within typical construction budgets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

OPENSTUDIO® [SWR-07-40]

OpenStudio® is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models. OPENSTUDIO® IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.

Ball, Brian↗