Defining Energy Uses and Spaces
In Chap. 2 we defined the building envelope, the ambient weather conditions it is exposed to, and the interior Spaces that a building is subdivided into. Of course, the activities that take place in those Spaces are significant drivers for energy consump
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Defining Energy Uses and Spaces
3.1 Energy Uses and Thermal Loads In Chap. 2 we defined the building envelope, the ambient weather conditions it is exposed to, and the interior Spaces that a building is subdivided into. Of course, the activities that take place in those Spaces are significant drivers for energy consumption as well as the reason buildings exist in the first place. In this Chapter, we will gain a better understanding of how Space occupancy and energy end uses are defined by OpenStudio. As with Constructions, the amount of data required to fully specify Space loads is significant, and we will come to appreciate how OpenStudio Libraries and data inheritance make this process both fast and consistent. Building end uses may consume energy directly as is the case with lighting, electric, and gas Equipment; however, these end uses may also add heat to the Spaces in which they are contained. This heat may impact the heating or cooling energy, which must be provided by the building’s HVAC systems. Modeling these types of interactions is an important feature of whole building energy simulation. Another significant source of thermal loading within Spaces are the occupants themselves; people contribute both sensible and latent heat through physical activity, perspiration, and respiration. Infiltration, unconditioned air that leaks into Space, is also considered a load that will be discussed in this Chapter. Lastly, while they don’t generate heat or consume energy explicitly, we will also consider the role that the thermal mass of inanimate objects within Spaces plays in storing and releasing thermal energy. It is important to note that Space loads are a strong function of occupant behavior. As such, this step in building energy modeling is arguably the most subjective and error prone part of the process. Whereas the thermal properties of an insulation material may be well known and accurately modeled, how can one model the actions of building occupant with certainty? Does an occupant show up within a Space for the same period of time each day, and how many are there? Can we predict the level of physical activity an occupant undertakes? How will © Springer International Publishing AG, part of Springer Nature 2018 L. Brackney et al., Building Energy Modeling with OpenStudio, https://doi.org/10.1007/978-3-319-77809-9_3
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3 Defining Energy Uses and Spaces
the occupant operate lights and other equipment? These are only a few factors that drive uncertainty in an analytical process that requires unambiguous numerical input of occupant behavior for 8760 h of each simulated year. Before you give up and throw this book in the rubbish bin, consider a few key points: 1. As mentioned in Chap. 1, comparative analysis is one of the most important capabilities offered by building energy modeling. As long as occupant behavior is held constant across simulations, uncertainty in occupant behavior will lead to systematic error, which in general, does not invalidate comparisons between multiple energy simulations. The
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