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Autotune for Calibration

asked 2017-01-19 10:11:23 -0500

DW gravatar image

I noticed a couple of articles here and here on the DOE development of autotune for EnergyPlus. I haven't seen any updates on it in the last year. Has anyone on this forum used this, and do you know if there are any plans to continue its development? Is it possible to use this with OpenStudio someday?

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Are you looking for Autotune specifically, or a calibration tool for EnergyPlus (or OpenStudio) more generally? For EnergyPlus at least there is also APIDAE calibrator and ExCalibBEM which is based on GenOpt, and maybe a couple of other things too.

__AmirRoth__ gravatar image__AmirRoth__ ( 2017-01-19 16:27:13 -0500 )edit

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answered 2017-01-19 11:18:59 -0500

OpenStudio has developed a cloud based platform to solve calibration problems. While Autotune is not included (nor are there plans to) there are several optimization algorithms available thru the OpenStudio Analysis Spreadsheet and will soon be available in PAT. Currently the list is:

NSGA2 (Non-dominated Sorting Genetic Algorithm)

  • Multi-objective
  • Parallel F evaluations
  • Mixed Continuous or Discrete variables

SPEA2 (Strength Pareto Evolutionary Algorithm)

  • Multi-objective
  • Parallel F evaluations
  • Continuous variables only

Rgenoud (GENetic Optimized Using Derivatives)

  • Single-objective
  • Parallel F evaluations for genetic search
  • Parallel gradient calculation for continuous variables

Optim (quasi-Newton method with bounds)

  • Single-objective
  • Parallel gradient calculation
  • Continuous variables only

PSO (Particle Swarm)

  • Single-objective
  • Continuous variables only

The calibration workflow is Measure based, meaning almost any OpenStudio method is available for calibration purposes (ex, swapping out full HVAC systems, changing geometry, or simple idf parameter changes). A good Measure resource is https://bcl.nrel.gov/

The OpenStudio calibration / optimization workflow accepts timeseries and monthly utility data. Objective functions can also be put into groups for multi-objective problems. The suggested workflow is to first sample the variable space with one of the sampling algorithms available on the server (ex, LHS). Remove any non-impactful variables and choose appropriate bounds for the impactful variables. Run a calibration using a gradient based method (ex, Optim) for all continuous variables, a hybrid genetic / gradient based method (Rgenound) or choose a multi-objective algorithm such as NSGA2. Once that is completed the robustness of the solution can be checked by using one of the sensitivity methods.

Computing time is a function of base simulation time and the number of variables that are selected for calibration. All the available algorithms are parallelized meaning gradient calcs are done in parallel for Optim and Rgenoud and all population calcs for NSGA2 are run utilizing all available cores. Costs are always changing but right now you can get a 32 core box for $1.68/hr with the capability to add more boxes for larger problems.

Several papers were presented at ASHRAE:

  • Ball, 2015, Calibration example with OpenStudio.
  • Macumber, 2014, A graphical tool for cloud-based building energy simulation.
  • Long, 2014, Scaling building energy modeling horizontally in the cloud with openstudio.

There is also a calibration example in the github site for the spreadsheet which can be found here

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answered 2017-01-19 15:44:02 -0500

JoshuaRNew gravatar image

Autotune Articles

You found the oldest, and likely least-useful, set of articles. To date, there have been 4 primary-source articles which have spawned 30+ in the news:

  • Article #1 - initial software development (September 22, 2014)
  • Article #2 - release of Autotune as open source (September 2, 2015)
  • Article #3 - NREL-hosted Lab-Corps program involving 86 interviews to identify industry's specific needs, uses, and value related to calibration (September 28, 2016)
  • Article #4 - two case studies, including human vs. Autotune for calibration performance, in the Journal of Applied Energy (November 2016)

For a partial listing of Autotune news buzz, see bit.ly/autotune_publicity.


Autotune Science

While any multi-objective search algorithm can provide an answer, the DOE/BTO-funded Autotune project conducted an extensive search of over 300,000 algorithm instances to quantify performance of the best calibration algorithm in terms of:

The research, detailed in over 30 peer-reviewed publications (bit.ly/autotune_science), has been completed and Autotune is now open-source on GitHub (bit.ly/autotune_code) for use by the private sector.


Autotune Application

Regarding practical use of Autotune, there are a few resources that might help:

  • Autotune overview video [YouTube]
  • Overview slides [PDF] (note: Brian Ball presented OpenStudio's capabilities at this ASHRAE seminar)
  • Step-by-step instructions for 3 ways to run Autotune (easiest to hardest/most-flexible):

    1) Standalone demo - download the directory, replace myidf.idf, myparams.csv, myuserdata.csv, and myweather.epw with your own files, and double-click autotune.bat.

    2) Virtual machine - download a virtual machine and immediately run demo, website, or web service in a virtual environment.

    3) Server installation - step-by-step instructions for installing on a Windows or Linux machine/server.

Autotune has been used in 3 countries, integrated into 5 companies' energy modeling pipelines, and being considered for application by 4 U.S. government agencies. Autotune does use OpenStudio (slide 32) for initial model creation, but only EnergyPlus during calibration for the reasons of speed and scalability. While created to be simulation-engine agnostic for easy application with new versions or simulation engines, the primary limitation for most users is that the open-source version uses EnergyPlus 7.0. Ultimately, it is up to the user to determine whether Autotune, OpenStudio, or other private-sector calibration services work best for your needs.

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Asked: 2017-01-19 10:11:23 -0500

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Last updated: Jan 19 '17