Finally, a few links, details and instructions for those of you who want to get rolling with the tools.  The nodes are available in Dynamo’s package manager, using a recent daily build of Dynamo.  We expect an official release with this functionality by the end of October, but in the meantime you can use a daily build to use the tools. 

To install the package, search for the name in the Dynamo package manager – Dynamo > Packages > Search for a package > ‘Energy Analysis for Dynamo – and install the package.  Once the package is installed, you’ll likely want to check out our sample files in the package’s ‘extra’ folder, and watch our first round of tutorial videos (1,2). 

We should also note that some analytical information (constructions, schedules, etc.) can only be analyzed using Dynamo on top of Vasari. The source code is available on Github under an Apache v2 license – it is open for anyone to use and modify.

via Energy Analysis for Dynamo – Open Beta Release! | CORE studio

The github page is here

Go here:

Click this link to go direct to course registration page:

Free courses:

To register to take the Autodesk Building Performance Analysis (BPA) Certificate on your own, you can use the following key:

From Revit, you need to:

  • Run Energy Simulation
  • then click Results and Compare

From here, click on:

Clicking this little icon in Green Building Studio:

Will show you something like this:

Essentially, this is giving you some ideas on how you may improve the efficiency and performance of your building.

Read more:
Potential Energy Savings Chart – WikiHelp

New Potential Energy Savings Widget Helps You Focus on What Matters! – Building Performance Analysis

This post looks at the post-processing side of the energy modeling workflow. Often, a spreadsheet tool like Excel is a first choice for many analysis tasks. This is great for simple cases, but if the number of files or the amount of data is large or complex, Excel will cost you time and lead to errors. This is where you should turn to Python! 

Read more at:
Python for Energy Modelers – Part 3 – Simple Post-processing | openRevit