Documents in the NTIS Technical Reports collection are the results of federally funded research. They are directly submitted to or collected by NTIS from Federal agencies for permanent accessibility to industry, academia and the public.  Before purchasing from NTIS, you may want to check for free access from (1) the issuing organization's website; (2) the U.S. Government Printing Office's Federal Digital System website http://www.gpo.gov/fdsys; (3) the federal government Internet portal USA.gov; or (4) a web search conducted using a commercial search engine such as http://www.google.com.
Accession Number DE2013-1087478
Title Simulation and Bit Data Challenges in Tuning Building Energy Models.
Publication Date 2013
Media Count 7p
Personal Author J. Sanyal
Abstract EnergyPlus is the flagship building energy simulation software used to model whole building energy consumption for residential and commercial establishments. A typical input to the program often has hundreds, sometimes thousands of parameters which are typically tweaked by a buildings expert to get it right. This process can sometimes take months. Autotune is an ongoing research effort employing machine learning techniques to automate the tuning of the input parameters for an EnergyPlus input description of a building. Even with automation, the computational challenge faced to run the tuning simulation ensemble is daunting and requires the use of supercomputers to make it tractable in time. In this proposal, we describe the scope of the problem, the technical challenges faced and overcome, the machine learning techniques developed and employed, and the software infrastructure developed/in development when taking the EnergyPlus engine, which was primarily designed to run on desktops, and scaling it to run on shared memory supercomputers (Nautilus) and distributed memory supercomputers (Frost and Titan). The parametric simulations produce data in the order of tens to a couple of hundred terabytes. We describe the approaches employed to streamline and reduce bottlenecks in the workflow for this data, which is subsequently being made available for the tuning effort as well as made available publicly for open-science.
Keywords Automation
Buildings
Computer software
Computer systems programs
Energy consumption
Energy models
Memory devices
Simulation
Supercomputers
Tuning

 
Source Agency Technical Information Center Oak Ridge Tennessee
NTIS Subject Category 97B - Energy Use, Supply, & Demand
89B - Architectural Design & Environmental Engineering
62 - Computers, Control & Information Theory
Corporate Author Oak Ridge National Lab., TN.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1403
Contract Number DE-AC05-00OR22725

Science and Technology Highlights

See a sampling of the latest scientific, technical and engineering information from NTIS in the NTIS Technical Reports Newsletter

Acrobat Reader Mobile    Acrobat Reader