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Title: Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further

Abstract

Modeling commercial building energy usage can be a difficult and time-consuming task. The increasing prevalence of optimization algorithms provides one path for reducing the time and difficulty. Many use cases remain, however, where information regarding whole-building energy usage is valuable, but the time and expertise required to run and post-process a large number of building energy simulations is intractable. A relatively underutilized option to accurately estimate building energy consumption in real time is to pre-compute large datasets of potential building energy models, and use the set of results to quickly and efficiently provide highly accurate data. This process is called metamodeling. In this paper, two case studies are presented demonstrating the successful applications of metamodeling using the open-source OpenStudio Analysis Framework. The first case study involves the U.S. Department of Energy's Asset Score Tool, specifically the Preview Asset Score Tool, which is designed to give nontechnical users a near-instantaneous estimated range of expected results based on building system-level inputs. The second case study involves estimating the potential demand response capabilities of retail buildings in Colorado. The metamodel developed in this second application not only allows for estimation of a single building's expected performance, but also can be combined with publicmore » data to estimate the aggregate DR potential across various geographic (county and state) scales. In both case studies, the unique advantages of pre-computation allow building energy models to take the place of topdown actuarial evaluations. This paper ends by exploring the benefits of using metamodels and then examines the cost-effectiveness of this approach.« less

Authors:
; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1324383
Report Number(s):
NREL/CP-5500-67076
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2016 ACEEE Summer Study on Energy Efficiency in Buildings, 21-26 August 2016, Pacific Grove, California
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; metamodels; OpenStudio; Asset Score Tool; demand response

Citation Formats

Horsey, Henry, Fleming, Katherine, Ball, Brian, and Long, Nicholas. Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further. United States: N. p., 2016. Web.
Horsey, Henry, Fleming, Katherine, Ball, Brian, & Long, Nicholas. Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further. United States.
Horsey, Henry, Fleming, Katherine, Ball, Brian, and Long, Nicholas. 2016. "Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further". United States. doi:.
@article{osti_1324383,
title = {Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further},
author = {Horsey, Henry and Fleming, Katherine and Ball, Brian and Long, Nicholas},
abstractNote = {Modeling commercial building energy usage can be a difficult and time-consuming task. The increasing prevalence of optimization algorithms provides one path for reducing the time and difficulty. Many use cases remain, however, where information regarding whole-building energy usage is valuable, but the time and expertise required to run and post-process a large number of building energy simulations is intractable. A relatively underutilized option to accurately estimate building energy consumption in real time is to pre-compute large datasets of potential building energy models, and use the set of results to quickly and efficiently provide highly accurate data. This process is called metamodeling. In this paper, two case studies are presented demonstrating the successful applications of metamodeling using the open-source OpenStudio Analysis Framework. The first case study involves the U.S. Department of Energy's Asset Score Tool, specifically the Preview Asset Score Tool, which is designed to give nontechnical users a near-instantaneous estimated range of expected results based on building system-level inputs. The second case study involves estimating the potential demand response capabilities of retail buildings in Colorado. The metamodel developed in this second application not only allows for estimation of a single building's expected performance, but also can be combined with public data to estimate the aggregate DR potential across various geographic (county and state) scales. In both case studies, the unique advantages of pre-computation allow building energy models to take the place of topdown actuarial evaluations. This paper ends by exploring the benefits of using metamodels and then examines the cost-effectiveness of this approach.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 8
}

Conference:
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