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A typical EnergyPlus annual simulation takes anywhere from two to 20 minutes depending on the size and complexity of the modeled building. With those kinds of runtimes, it is difficult to imagine analyses that take hundreds or even thousands of simulations—e.g., sensitivity analysis, design optimization, or automated model-input calibration using measured data—as parts of a typical design workflow. Unless, of course, you consider the cloud. Cloud computing allows large EnergyPlus-based analyses to be run quickly and cheaply. An analysis comprising a thousand runs can be done in under an hour for around $20, far less than the labor rate of the modeler herself!

One of the companies leveraging cloud economics is BUILDlab, an Ithaca-based startup that produces Apidae: a suite of EnergyPlus simulation services. With help from a 2012 DOE SBIR (Small Business Innovation Research) award, Apidae was developed as a turnkey toolkit that “helps modelers make the most of their EnergyPlus models.” Uploading an EnergyPlus model gives the modeler access to tools for speeding up long runs via parallelization (Accelerator), sensitivity and parametric analysis (Influence and Factors), and calibration (Calibrator). The Apidae suite also includes a Git-based revision history tracking tool (Chronicle) which allows modelers to track changes in models over time.

Apidae’s clients are using the tools to solve everyday modeling problems. “We have been using Apidae’s Accelerator to streamline our workflow by freeing up our office computers”, says Eric Studer of TNZ Energy Consulting. “For one recent project, we also used Factors to develop an expression relating optimization of above-grade R-value to annual utility costs, giving the architect a simple way to choose the most cost-effective way to achieve energy savings by adjusting envelope thermal properties.”

The newest member of the Apidae family, Calibrator, helps modelers navigate the often uncertain process of calibrating model inputs using measured data. Monthly utility bills usually don’t comprise enough data to nail down the most important aspects of the model with great certainty. Calibrator addresses this fundamental issue by returning a group of promising solutions. Users can then sort through the candidate models, check their assumptions, and focus their resources on the uncertain parts of the model that need the most attention.

“One of our favorite tag lines for Apidae has been 'turning information into knowledge,'” says BUILDlab founder David Bosworth. “All of these tools are working on essentially the same problem: managing and tracking the massive amount of data and raw information that is inherent in building energy modeling and distilling it into intuitive interfaces that allow modelers to make better decisions.”