The impact of occupant modeling on energy outcomes of building energy simulation
Kim, Ji Hyun
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The reported performance gap between predicted and real building energy consumption has drawn keen attention from the building simulation community and related stakeholders. Alongside other research efforts to identify, quantify, and close this gap, the most recent attempt is the development of occupant behavior models that generate more “realistic” occupant inputs in the building energy simulation used for prediction. These new occupant models are typically realized by stochastic methods. To date, the newly developed models focus on mimicking real life variability. In spite of that, they have not led to more accurate consumption predictions than previous methods. Rather than adding yet another occupant behavior modeling approach, this thesis emphasizes the need to understand the impact of occupant models on building energy outcomes in real life applications. To accomplish this, we investigate two distinctive approaches to occupant modeling: top-down and bottom-up. We build the argument in the thesis that the top-down approach is suitable in highly variable situations where relatively little information about actual occupant variables can be known. This is usually the case in residential applications. By introducing a so-called “Life Style Factor,” we conclude that the use of this factor is promising to capture the variability of occupant-related parameters in residential buildings. For commercial buildings, a fundamental analysis is conducted to identify the impact of occupant-related inputs on the performance gap while explicitly considering the level of modelers’ knowledge about occupants’ presence and actions at the time of prediction. The results of a sensitivity analysis reveal that even in the case where the modelers’ ignorance of actual occupancy is significant and hence occupant parameters become important contributors to the performance gap, the resulting disparity could be fairly well quantified without introducing complex occupant behavior models. It is also found that the randomness of occupant behavior with respect to actions has no significant role in the performance gap at least in typical building simulation practice. This finding is significant as it advises us to rethink our pursuit of accuracy by developing new occupant behavior models, such as the ones that explicitly model the human reasoning, perception and action related to the opening of windows.