The impacts of occupant behavior on building energy consumption: A review

Chen, Shuo; Zhang, Kevin; Xia, Xiaobo; Chen, Yixing; Setunge, Sujeeva; Shi, Long

doi:10.1016/j.seta.2021.101212

Cited by 65 publications

(39 citation statements)

References 126 publications

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“…Due to the important role of the method of use for temporary water abstraction, the authors of the studies [48] write clearly not about its calculation, but "prediction", emphasizing the stochastic nature of this consumption, depending on the way the system is used by users. The authors of the review [54] also emphasize a significant impact on energy consumption in buildings, which, although it concerns heating, ventilation and lighting systems, seems to indicate a similar unpredictability of their use, as in the case of DHW systems. The authors of the model for optimizing energy consumption in a building [55], based on user behavior survey, also refer to "prediction" rather than "calculating" the actual values of energy consumption in a building.…”

Section: Hot Water Consumption-standard Methodsmentioning

confidence: 99%

Peak Power of Heat Source for Domestic Hot Water Preparation (DHW) for Residential Estate in Poland as a Representative Case Study for the Climate of Central Europe

Amanowicz

2021

Energies

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Due to the energy transformation in buildings, the proportions of energy consumption for heating, ventilation and domestic hot water preparation (DHW) have changed. The latter component can now play a significant role, not only in the context of the annual heat demand, but also in the context of selecting the peak power of the heat source. In this paper, the comparison of chosen methods for its calculation is presented. The results show that for contemporary residential buildings, the peak power for DHW preparation can achieve the same or higher value as the peak power for heating and ventilation. For this reason, nowadays the correct selection of the peak power of a heat source for DHW purposes becomes more important, especially if it uses renewable energy sources, because it affects its size and so the investment cost and economic efficiency. It is also indicated that in modern buildings, mainly accumulative systems with hot water storage tanks should be taken into account because they are less sensitive to design errors (wrongly selected peak value in the context of the uncertainty of hot water consumption) and because they result in acceptable value of peak power for DHW in comparison to heating and ventilation.

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Section: Hot Water Consumption-standard Methodsmentioning

confidence: 99%

Peak Power of Heat Source for Domestic Hot Water Preparation (DHW) for Residential Estate in Poland as a Representative Case Study for the Climate of Central Europe

Amanowicz

2021

Energies

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“…Ramadan & P. Sisiopiku, 2020;McFadden et al, 1977;Xie & Waller, 2010) , urban water management (Williamson, 2012), disaster evacuation (Jumadi et al, 2018), crime (Malleson et al, 2010) and urban social dynamics (Malleson & Birkin, 2013). To date, there is relatively less application in building simulation research, particularly in the sub-discipline of occupant presence and behaviors (Andrews et al, 2016;Chen et al, 2021).…”

Section: Population Synthesis Methodologymentioning

confidence: 99%

Generating synthetic occupants for use in building performance simulation

Putra

Andrews

Hong

2021

Journal of Building Performance Simulation

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Occupant behavior simulation frameworks can employ synthetic populations to characterize occupancy and behavioral patterns in buildings based on real demographic data at a certain geographical location. Multiple methods are available to generate a synthetic population, with pros-and cons-for different applications and contexts. For buildings, very few synthetic occupant populations have been generated. This paper uses a Bayesian Networks (BN) structural learning approach to synthesize populations of occupants in a multi-family housing. Two additional cases of office occupants and senior housing residents are considered as a cross-case comparison. We draw upon the extended version of Drivers-Needs-Actions-Systems (DNAS) framework to guide the selection of variables and data imputation. The resulting synthetic occupant data is evaluated by comparing the joint distributions between the actual and synthetic data sets, % difference, and Standardized-Root-Mean-Squared-Error (SRMSE). Our results show that the BN approach is powerful in learning the structure of data sets. The synthetic data sets successfully match the joint distributions of the underlying combined data sets. Experiments on the multi-family housing particularly show the best performance compared to the cases of office and senior housing. Future work includes testing and demonstration of how the synthetic data sets feed to occupant behavior module through co-simulation with building performance simulation tools, such as EnergyPlus.

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“…Occupant interactions, among other influencing factors, can significantly impact building energy efficiency related to the heating, ventilation and air conditioning system, the lighting system and the hot water supply, among other elements [37]. In addition, other occupants' information, such as setpoints, income levels, homeownership and gender, have been identified to potentially influence the energy use in buildings, and some studies have investigated the related energy impacts.…”

Section: Occupant Behaviormentioning

confidence: 99%

Impacts on Indoor Thermal Comfort and Heating Energy Use in Hellenic Dwellings from Occupant Behavioral Reactions

Dascalaki¹,

Balaras²

2021

Applied Sciences

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In an effort to reduce the operational cost of their dwellings, occupants may even have to sacrifice their indoor thermal comfort conditions. Following the economic recession in Greece over recent years, homeowners have been forced to adapt their practices by shortening heating hours, lowering the indoor thermostat settings, isolating spaces that are not heated or even turning off their central heating system and using alternative local heating systems. This paper presents the results from over 100 occupant surveys using questionnaires and walk-through energy audits in Hellenic households that documented how occupants operated the heating systems in their dwellings and the resulting indoor thermal comfort conditions and actual energy use. The results indicate that the perceived winter thermal comfort conditions were satisfactory in only half of the dwellings, since the actual operating space heating periods averaged only 5 h (compared with the assumed 18 h in standard conditions), while less than half heated their entire dwellings and only a fifth maintained an indoor setpoint temperature of 20 °C, corresponding to standard comfort conditions. Mainstream energy conservation measures include system maintenance, switching to more efficient systems, reducing heat losses and installing controls. This information is then used to derive empirical adaptation factors for bridging the gap between the calculated and actual energy use, making more realistic estimates of the expected energy savings following building renovations, setting prudent targets for energy efficiency and developing effective plans toward a decarbonized building stock.

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The impacts of occupant behavior on building energy consumption: A review

Cited by 65 publications

References 126 publications

Peak Power of Heat Source for Domestic Hot Water Preparation (DHW) for Residential Estate in Poland as a Representative Case Study for the Climate of Central Europe

Peak Power of Heat Source for Domestic Hot Water Preparation (DHW) for Residential Estate in Poland as a Representative Case Study for the Climate of Central Europe

Generating synthetic occupants for use in building performance simulation

Impacts on Indoor Thermal Comfort and Heating Energy Use in Hellenic Dwellings from Occupant Behavioral Reactions

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