Simulating the dynamics of occupant behaviour for power management in residential buildings

Kashif, Ayesha; Ploix, Stéphane; Dugdale, Julie; Le, Xuan Hoa Binh

doi:10.1016/j.enbuild.2012.09.042

Cited by 69 publications

(29 citation statements)

References 10 publications

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“…In recent years, international research has focused on improving occupancy data collection with two main purposes: 1) providing better data for building simulation to make more accurate energy and comfort predictions [18][19][20][21][22], and 2) using real time data to control buildings and so to improve building performance [23][24][25][26][27][28]. In addition, another line of research focuses on monitoring buildings to explain better the effects of occupancy and building operation [29][30][31][32][33][34], aiming also at changing behavioural patters [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

In-use monitoring of buildings: An overview and classification of evaluation methods

Guerra-Santin

Christopher

2015

Energy and Buildings

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Section: Introductionmentioning

confidence: 99%

In-use monitoring of buildings: An overview and classification of evaluation methods

Guerra-Santin

Christopher

2015

Energy and Buildings

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“…In the most research, the presence of occupant and heat generation and energy consumption by occupant are considered without taking account the way which they behave to use energy [26]. Considering the actual behavior of occupant in simulation methods leads to more realistic simulation.…”

Section: Human Behaviormentioning

confidence: 99%

The relation between indoor environnemental quality (IEQ) and energy consumption in building based on occupant behavior - A review

2016

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Abstract. Indoor Environmental Quality (IEQ) is an important topic which impacts on occupant health, productivity and also energy consumption in buildings. The four main parameters for IEQ evaluation are: Thermal comfort, indoor air quality, visual comfort and aural comfort. The occupant behavior in buildings defines as any direct or indirect act which an occupant selects to change the displeasure environmental condition into the comfort conditions. The selected behavior by human has a significant impact on the energy consumption in buildings. This paper reviews the methods which used to simulate IEQ parameters, energy consumption and human behavior in buildings. It aims to promote the idea of more consideration about the relation between occupant behavior and energy usage in buildings. This summary of existing studies about the importance of human behavior factor in energy simulation software helps to identify new methods and strategies for simulating IEQ, Energy and behavior.

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“…Typical Monte Carlo methods are Markov Chain models [32,49,50,73,[115][116][117][118][119][120], as well as discrete [21,80] and semi-hidden [38,[121][122][123] Markov Chain models. State transition analysis is also used to develop real-time agent-and actionbased models [124][125][126][127][128][129][130].…”

Section: Explicit Modelsmentioning

confidence: 99%

An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework

Hong

D’Oca

Turner

et al. 2015

Building and Environment

258

147

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Reducing energy consumption in the buildings sector requires significant changes, but technology alone may fail to guarantee efficient energy performance. Human behavior plays a pivotal role in building design, operation, management and retrofit, and is a crucial positive factor for improving the indoor environment, while reducing energy use at low cost. Over the past 40 years, a substantial body of literature has explored the impacts of human behavior on building technologies and operation. Often, need-action-event cognitive theoretical frameworks were used to represent human-machine interactions. In Part I of this paper a review of more than 130 published behavioral studies and frameworks was conducted. A large variety of data-driven behavioral models have been developed based on field monitoring of the human-building-system interaction. Studies have emerged scattered geographically around the world that lack in standardization and consistency, thus leading to difficulties when comparing one with another. To address this problem, an ontology to represent energy-related occupant behavior in buildings is presented. Accordingly, the technical DNAs framework is developed based on four key components: i) the Drivers of behavior, ii) the Needs of the occupants, iii) the Actions carried out by the occupants, and iv) the building systems acted upon by the occupants. This DNAs framework is envisioned to support the international research community to standardize a systematic representation of energyrelated occupant behavior in buildings. Part II of this paper further develops the DNAs framework as an XML (eXtensible Markup Language) schema, obXML, for exchange of occupant information modeling and integration with building simulation tools.

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Simulating the dynamics of occupant behaviour for power management in residential buildings

Cited by 69 publications

References 10 publications

In-use monitoring of buildings: An overview and classification of evaluation methods

In-use monitoring of buildings: An overview and classification of evaluation methods

The relation between indoor environnemental quality (IEQ) and energy consumption in building based on occupant behavior - A review

An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework

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