AUTOMATION OF COMMON BUILDING ENERGY SIMULATION WORKFLOWS USING PYTHON

A valuable skillset for building industry professionals is proficiency in high-level, scripting languages that can automate and perform many common repetitive or technically intensive tasks. This application-focused paper emphasizes the use of the Python programming language in various workflows common to the building performance modeling and simulation process. Python is an open, powerful, and easy-to-learn scripting language with an emphasis on programmer productivity. While the highlighted applications themselves are notably ordinary amongst building simulation practitioners, the novelty of this discussion is in the speed and usefulness of new Python libraries and data analysis techniques. Four short examples are illustrated: simulation input file templating, data exchange and interoperability, performance curve regression, and time-series output data postprocessing. An overview is presented of the growing current and planned Python libraries, extensions, and projects that are especially applicable and, in some cases, explicitly designed for the building industry.

[1]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[2]  Arno Schlueter,et al.  Building information model based energy/exergy performance assessment in early design stages , 2009 .

[3]  Paul Raftery,et al.  VISUALIZING PATTERNS IN BUILDING PERFORMANCE DATA , 2011 .

[4]  Ruzhu Wang,et al.  Simulation and experimental validation of the variable-refrigerant-volume (VRV) air-conditioning system in EnergyPlus , 2008 .

[5]  T. Agami Reddy,et al.  Applied Data Analysis and Modeling for Energy Engineers and Scientists , 2011 .

[6]  McKinney Wes,et al.  Python for Data Analysis , 2012 .

[7]  Eitan M. Gurari,et al.  Introduction to the theory of computation , 1989 .

[8]  Travis E. Oliphant,et al.  Python for Scientific Computing , 2007, Computing in Science & Engineering.

[9]  Brian E. Granger,et al.  IPython: A System for Interactive Scientific Computing , 2007, Computing in Science & Engineering.

[10]  Vincent Lemort,et al.  Liquid flooded compression and expansion in scroll machines – Part II: Experimental testing and model validation , 2012 .

[11]  Stéphane Bertagnolio,et al.  Development of an Evidence-Based Calibration Methodology Dedicated to Energy Audit of Office Buildings. Part 1: Methodology and Modeling. , 2010 .

[12]  Vincent Lemort,et al.  Liquid-flooded compression and expansion in scroll machines - Part I: Model development , 2012 .

[13]  Marcus Jones,et al.  PUSHING THE LIMITS OF SIMULATION COMPLEXITY - A BUILDING ENERGY PERFORMANCE SIMULATION OF AN EXHIBITION CENTER IN THE U.A.E. , 2010 .