ASHRAE Standard 205 Representation of Performance Data for HVAC&R and Other Facility Equipment addresses connection between equipment performance data and building performance simulation models. A long standing challenge for energy modelers and equipment manufacturers alike is the accurate representation of complex equipment performance in simulation models. ASHRAE 205 defines a new method to represent equipment performance as a standardized data file allow for easy creation and use of complex performance information.

The standard defines a Concise Binary Object Representation (CBOR) file confirming to a JSON schema to represent the equipment performance. Providing documentation, the actual data model, and verification and application rule sets, ASHRAE 205 is a complete solution. Along with the published standard, ASHRAE provides a series of resources to help equipment manufacturers, software developers, and energy modelers utilize the new method.

The performance of large pieces of equipment such as a chiller or packaged DX systems changes based on several variables such as temperature, load, pressure, and more. In order to fully account for this complexity a performance map of the performance variables and input variables is required. A large portion of ASHRAE 205 defines these performance maps for each type of equipment. Other sections of the standard provides method of creating, reading, and using the data files that store these performance maps.

Many energy models today use simplified, curve fit methods of representing equipment performance. These curves occasionally come directly form manufactures, however more often than not are code into simulation software and only takes in a few key points of actual performance. While acceptable for compliance purposes, this approach has gaps when used for equipment comparisons or predictive analysis.

With ASHRAE 205, the detail that each piece of equipment holds is massive, defining the performance over all conditions. In this way equipment that performance very well at part load or other conditions will show this in the results of simulations. This will help design teams select the best equipment for each project and have more confidence in the predictive results of their performance simulations.