Data-driven Occupancy Profiles for Apartment-style Student Housing

Nikdel, Leila; Schay, Alan; Hou, Daqing; Powers, Susan E.

doi:10.1016/j.enbuild.2021.111070

Cited by 10 publications

(6 citation statements)

References 38 publications

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“…During this stage the energy demand of the selected buildings were simulated using general descriptions of the building's performance and construction and synthesised data developed according to the datadriven occupancy profiles [13]. This simulation has been done using a building energy simulation software EnergyPlus [14].…”

Section: Stage 1: Simulation Of Current Energy Demand With Synthesise...mentioning

confidence: 99%

The use of synthesised data for the development of Digital Twin: Chalmers student house case study

Caceres,

Malakhatka,

Hellebro

2023

J. Phys.: Conf. Ser.

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This research focuses on the development of a digital twin for a residential building using a synthesised data approach. The methodology involves five stages, with three of them dedicated to simulating different energy scenarios: actual energy consumption, passive house level consumption, and consumption after the implementation of smart building technology. The selected building is located at the Chalmers Technical University campus in Sweden. Synthesised data is used to simulate the energy demand of the building before and after renovation, as well as after the implementation of smart building technology. A custom agent-based simulation model is developed to simulate the impact of residents’ behaviours on the building’s energy consumption, and high-resolution data was analysed and synthesised to create a new dataset that was applied to the selected buildings. Finally, the results of the simulations were analysed and compared to assess the potential energy savings and improved energy performance achieved through the implementation of different scenarios. The study provides insights into the energy-efficiency of different measures for reducing energy consumption in residential buildings. The study provides insights into the energy-efficiency of different measures for reducing energy consumption in residential buildings. This research shows the potential of using synthesised data to assess and forecast changes in building stock transformation, even when real data are not available.

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Section: Stage 1: Simulation Of Current Energy Demand With Synthesise...mentioning

confidence: 99%

The use of synthesised data for the development of Digital Twin: Chalmers student house case study

Caceres,

Malakhatka,

Hellebro

2023

J. Phys.: Conf. Ser.

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“…A personalized experience can help users better understand and take action towards energy conservation [12][13][14]. Therefore, modification of resident behaviors requires that they have tailored information that can help them understand their personal motivation to change a specific behavior [15][16][17]. We suggest that detailed granular electricity data, which are captured over short time intervals and at the circuit level, can provide a better understanding of different types of users, the magnitude and variability of their patterns of electricity consumption, and the impact of appliances on individual electricity use.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Refs. [17,18] used half-hour interval electricity data to understand the electricity use of household customers in subpopulations. Similarly, Satre-Meloy et al [19] used household electricity data to identify hourly load profiles as a function of the time of day and day of the week.…”

Section: Introductionmentioning

confidence: 99%

Energy Hogs and Misers: Magnitude and Variability of Individuals’ Household Electricity Consumption

et al. 2023

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We use circuit-level granular electricity measurements from student housing and statistical analysis to better understand individuals’ electricity consumption. Two key patterns emerged—individuals varied systematically in their magnitude of electricity use as well as in their variability of usage at the hourly and daily level. A cluster analysis of electricity consumption in individual bedrooms shows that 18% of students consume 48% of total electricity use at a median of 2.17 kWh/d/person. These few energy hogs have a disproportionate impact on electricity consumption. In contrast, the misers (22% of students) consume only 4% of the electricity (0.18 kWh/d/person). Mini-refrigerators in bedrooms contributed substantially to the total electricity use of the moderate users. In contrast, mini-refrigerators were less influential for energy hogs, suggesting that these residents may draw power in others ways, such as by using powerful computing or gaming systems for hours each day. A sub-cluster analysis revealed substantial individual variability in hourly usage profiles. Some energy hogs use electricity consistently throughout the day, while others have specific periods of high consumption. We demonstrate how our analysis is generalizable to other situations where the resident does not directly pay their utility bills and thus has limited financial incentive to conserve, and how it contributes to a deeper understanding of the different ways in which individuals use energy. This allows for targeting interventions to groups with similar patterns of consumption. For example, policies such as fines or fees that might reduce the excessive electricity use for short times or for individual hogs could result in potential savings ranging from 16–33% of bedroom electricity.

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“…In recent years, several European projects have focused on the occupants, their behaviour, comfort, and the relation of these factors to the energy efficiency of the building [8][9][10][11]. Furthermore, several authors study occupants' behaviour and the interaction between people and housing by defining occupancy profiles and energy consumption profiles [12][13][14] and the definition of metrics and methodologies that incorporate occupant behaviour into building assessment and design processes [15,16].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Social Housing Energy and Thermal Performance in Relation to Occupants’ Behaviour and COVID-19 Influence—A Case Study in the Basque Country, Spain

et al. 2022

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Evidence shows that people have a major impact on building performance. Occupants’ impact is especially important in social housing, where their occupants may present greater vulnerabilities, and their needs are not always considered. This study aims to analyse the socio-demographic influence in social rental housing concerning hygrothermal comfort and energy consumption in a case study located in Vitoria, Spain during the first 4-month period of 2020 and 2021 (during and after COVID-19 lockdown). An innovative data management system is included, where the users and administration can see in real-time the temperature and consumption in the dwellings. A 2-phase method has been applied; phase 1 is associated with outdoor climate conditions, building properties and social profile. Phase 2 determined the results in energy consumption, indoor hygrothermal comfort and occupant energy-use pattern. The results show that the comfort levels and energy consumption vary according to the analysed social profiles, as well as the heating activation periods and domestic hot water system usage. In conclusion, socio-demographic characteristics of social housing households influence the hygrothermal comfort of their dwellings, occupants’ behaviour and heating and domestic hot water energy consumption.

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Data-driven Occupancy Profiles for Apartment-style Student Housing

Cited by 10 publications

References 38 publications

The use of synthesised data for the development of Digital Twin: Chalmers student house case study

The use of synthesised data for the development of Digital Twin: Chalmers student house case study

Energy Hogs and Misers: Magnitude and Variability of Individuals’ Household Electricity Consumption

Assessment of Social Housing Energy and Thermal Performance in Relation to Occupants’ Behaviour and COVID-19 Influence—A Case Study in the Basque Country, Spain

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