Modelling diversity in building occupant behaviour: a novel statistical approach

Haldi, Frédéric; Calı̀, Davide; Andersen, Rune Korsholm; Wesseling, Mark Thomas; Müller, Dirk

doi:10.1080/19401493.2016.1269245

Cited by 77 publications

(50 citation statements)

References 49 publications

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“…Following the observations by O'Brien et al [67] and Haldi [68] on the building-scale, we consider three general strategies to account for inter-individual occupant diversity on the space-level or person-level: (1) the use of measured data for simulation (e.g., real occupant densities for individual buildings), (2) the use of distinct models for distinct person-types (e.g., active and passive occupants) or space-types (e.g., residential space with high appliance power density and low appliance power density), and (3) the use of a general model with metamodels that define the model parameter distributions (e.g., occupant densities for individual buildings sampled from a probability distribution). Novel statistical models that consider inter-occupant diversity on the building-scale include e.g., the models by Haldi et al [69,68] for occupant actions on windows, shading and lighting in office and residential environments.…”

Section: Strategies For Diversitymentioning

confidence: 99%

A review on occupant behavior in urban building energy models

Happle

Fonseca

Schlueter

2018

Energy and Buildings

161

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Urban building energy models aspire to become key planning tools for the holistic optimization of buildings, urban design, and energy systems in neighborhoods and districts. The energy demand of buildings is largely influenced by the behavior of the occupants. The insufficient consideration of occupant behavior is one of the causes to the "performance gap" in buildings -the difference between the simulated and the actually observed energy consumption. On the urban-scale impacts of different occupant behavior modeling approaches onto the various purposes of urban building energy models are still largely unknown. Research shows that the inappropriate choice of occupant behavior model could result in oversized district energy systems, leading to over-investment and low operational efficiency. This work therefore reviews urban building energy models in terms of their occupant behavior modeling approaches. Three categories of approaches are established and discussed: (1) deterministic space-based approaches, (2) stochastic space-based approaches, and (3) stochastic person-based approaches. They are further assessed in terms of their strategy to consider diversity in occupant behavior. Stochastic models, especially stochastic person-based models, seem to be superior to deterministic models. However, there are no stochastic models available yet that can be used for case studies of mixed-districts, comprising buildings of various occupancy types. In the reviewed urban-scale approaches, only single-use residential or office districts are modeled with stochastic techniques. However, people interact with various buildings on a daily basis. Their activities relate to their presence in different spaces at the urban-scale and to their use of appliances in those spaces. Their individual levels of comfort and behavioral patterns govern the control actions towards building systems. Therefore, a novel activity-based multi-agent approach for urban occupant behavior modeling is proposed as alternative to current approaches.Keywords: urban building energy model, energy-related occupant behavior, occupancy, occupant behavior model IntroductionUrban areas house more than half of the global population and cities are responsible for more than 70% of the global carbon dioxide emissions. At the same time, cities are crucial actors in the transition towards sustainable energy Email address: happle@arch.ethz.ch (Gabriel Happle)

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Section: Strategies For Diversitymentioning

confidence: 99%

A review on occupant behavior in urban building energy models

Happle

Fonseca

Schlueter

2018

Energy and Buildings

161

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“…Specifically, it is shown that without proper treatment of the diversity in occupants' behaviour, probabilistic occupancy-related models fail to provide representative ranges of occupant behaviour possibilities as intended [4,5]. To address this issue, different approaches for inclusion of diversity in occupant behaviour modelling efforts have been examined [4,6,7,8]. However, it has been also suggested that for specific cases, such as large open-plan offices [3], a detailed treatment of occupants' diversity may not be beneficial.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the benefits of diversity representation in window operation models for building performance simulation

Tahmasebi¹,

Mahdavi

2019

Bauphysik

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Die Vorteile der Darstellung der Vielfalt in Fensteröffnungsmodellen für die Gebäudesimulation. Um die potenziellen Vorteile der Bereitstellung von Nutzerverhaltensmodellen mit verschiedenen Nutzerinformationen zu untersuchen, wurde der Fensteröffnungsbetrieb durch Nutzer eines Großraumbüros aggregiert und auf individueller Ebene modelliert. Anschließend wurde ein Modell des Großraumbüros unter Einbeziehung der entwickelten Modelle und Ströme aufgezeichneter Daten kalibriert, um die Vorhersageleistung der Modelle und ihren Beitrag zur Verbesserung der Zuverlässigkeit von Gebäude performance‐Bewertungen zu analysieren. Den Ergebnissen zufolge übertrafen die individuellen Fensteroperationsmodelle das aggregierte Modell, indem sie den Spitzenwert und die Variation des Fensterbetriebs über alle Nutzer im freilaufenden Betrieb erfassten, was zu einer besseren Bewertung des thermischen Komforts führte. Die individuellen Modelle ergaben jedoch eine Überschätzung des Spitzenwärmebedarfs im Vergleich zum Referenzwert, der auf dem tatsächlichen Fensterbetrieb in einem einzigen Jahr basiert.

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“…Some of the mentioned studies point out how the energy use of residential buildings is not homogeneous due to occupants behaviour [10,[14][15][16][17]. In 2012, Menezes et.al.…”

Section: Introductionmentioning

confidence: 99%

climify.org: an online solution for easy control and monitoring of the indoor environment

et al. 2019

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Real energy performance of new and retrofitted buildings often consistently differs from expectations. While occupants might complain about poor indoor climate, the energy use in such buildings is often higher than expected, leading to the well-known phenomenon called “Energy Performance Gap”. In the past years, monitoring of buildings, both in terms of energy use and indoor climate conditions, was realised mostly for office buildings only, and at high financial costs. However, the exponential growth in availability of IoT devices, over the last years, opens now new scenarios for low-cost monitoring and control solutions of buildings. Yet, modern IoT devices are often only accessible online through the vendors’ software, although some devices make use of open communication protocols and can, therefore, be connected to open platforms such as openHAB. However, the use of open platforms is still connected to a big efforts for many final users. We, therefore, propose climify.org, an open platform for plug and play connection of IoT sensors and actuators, for easy monitoring and controlling of buildings and buildings’ HVAC systems. The platform climify.org offers, at time of writing, three main applications. The first application is an IoT device installation app, to be used on portable devices (e.g. mobile phones or tablets of system administrators): this app allows easily installing and locating a sensor or an actuator, within a building. The second application is an online service for data visualisation and HVAC control: while the monitoring data can be plotted, the service offers several data evaluation methods; moreover, the settings of the connected actuators can be modified and controlled. The third application can be installed on portable devices (mobile phones and tablets of buildings’ occupants) and allows occupants to provide feedback on their perception of the indoor climate through several questionnaires’ formats. Through the three applications developed within climify.org, we aim at providing the best indoor climate and the lowest energy use through a low-cost solution.

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Modelling diversity in building occupant behaviour: a novel statistical approach

Cited by 77 publications

References 49 publications

A review on occupant behavior in urban building energy models

A review on occupant behavior in urban building energy models

Revisiting the benefits of diversity representation in window operation models for building performance simulation

climify.org: an online solution for easy control and monitoring of the indoor environment

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