Building performance simulation
A simulation model is an abstraction of the real building which allows to consider the influences on high level of detail and to analyze key performance indicators without cost-intensive measurements.
thermal and visual comfort, indoor air quality and moisture phenomena), HVAC and renewable system performance, urban level modeling, building automation, and operational optimization are important aspects of BPS.
[5] Some of them only cover certain parts of BPS (e.g. climate analysis, thermal comfort, energy calculations, plant modeling, daylight simulation etc.).
The core tools in the field of BPS are multi-domain, dynamic, whole-building simulation tools, which provide users with key indicators such as heating and cooling load, energy demand, temperature trends, humidity, thermal and visual comfort indicators, air pollutants, ecological impact and costs.
During this period, several methods had been introduced for analyzing single system components (e.g. gas boiler) using steady state calculations.
[9] The development of building simulation represents a combined effort between academia, governmental institutions, industry, and professional organizations.
[15] Four years later, Klein introduced the Engineering Equation Solver (EES)[16] and in 1997, Mattsson and Elmqvist reported on an international effort to design Modelica.
[17] BPS still presents challenges relating to problem representation, support for performance appraisal, enabling operational application, and delivering user education, training, and accreditation.
Calibration refers to the process of "tuning" or adjusting assumed simulation model inputs to match observed data from the utilities or Building Management System (BMS).
[31][32] An overview about possible causes for the widely discussed performance gap from design stage to operation is given by de Wilde (2014) and a progress report by the Zero Carbon Hub (2013).
More flexibility offer simulation engines using symbolic Differential Algebraic Equations (DAEs) with general purpose solvers that increase model reuse, transparency and accuracy.
The engine returns output data to the modeler application or another visualization tool which in turn presents the results to the user.
[41][44] Since the 1990s, building performance simulation has undergone the transition from a method used mainly for research to a design tool for mainstream industrial projects.
Building certification programs like LEED (USA), BREEAM (UK) or DGNB (Germany) showed to be a good driving force for BPS to find broader application.
This in turn has led to offers of formal energy guarantees based on simulated predictions, highlighting the general business potential of BPS.
