Comparing measured and simulated building energy performance data [electronic resource]

Finding building energy performance problems is a critical step in improving energy efficiency in buildings and in reaching a building's performance goals established during design. The prevalent method of improving building energy performance is to look for relative improvements on the basis of measured performance data, sometimes with a "calibrated" energy simulation model that is made to mimic the actual consumption as closely as possible. This approach is problematic because compensation errors often mask the performance problems one wants to find, a true baseline model is not established, and there is little certainty that the identified improvements capture all major performance problems. Typically, these assessment methods focus on either the building/system level or the component level, but do not consider all levels of detail. Furthermore, existing methods do not combine spatial and thermal perspectives and do not consider the relationships between components of a building's energy system, the HVAC (heating, ventilation, and air conditioning) systems, HVAC components, zones, spaces, and the building. However, improving this interaction, i.e., using the energy system for maximum effect in a building's spaces, is precisely what building operators and users are after. The effect of these shortcomings is that identification of energy performance problems tends to be haphazard and requires great effort. To address these gaps in knowledge and corresponding shortcomings, I formalized the Energy Performance Comparison Methodology (ECPM) to identify performance problems from a comparison of measured and simulated energy performance data. It extends prior hierarchies to describe a building and its energy system more fully so that the comparison and analysis includes the spatial and thermal perspectives and all levels of detail in a building, including the relevant relationships. It formalizes measurement assumptions and simulations assumptions, approximations, and simplifications (AAS) so that measured and simulated data can be assessed while considering all known limitations. This thesis describes this EPCM and its related contributions to knowledge. It also shows that a professional, called performance assessor, can identify more problems with less effort per problem than with existing methods. The assessor uses whole building energy performance simulation (BEPS) tools, such as EnergyPlus, to generate simulated data sets for the EPCM. Measured data come from physical measurements by sensors strategically placed in buildings and control data points such as set points. By enabling a meaningful comparison of measured and simulated data, this thesis enables future research to establish expert systems that can automatically detect performance problems and correct them, allow the virtual testing of energy efficiency improvements and innovations, and provide feedback to building designers and operators for ongoing improvement of the design and building operations methods.

Advisor: Fischer Martin
Bazjanac Vladimir advisor. Thesis advisor
Haymaker John advisor. Thesis advisor