Impacts of diversity in commercial building occupancy profiles on district energy demand and supply

Happle, Gabriel; Fonseca, Jimeno A.; Schlueter, Arno

doi:10.1016/j.apenergy.2020.115594

Cited by 43 publications

(9 citation statements)

References 42 publications

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“…This led occupants to modify their habits and behaviors in residential buildings, as they must adjust to being more often at home. Changes in occupancy schedules directly lead to changes in energy consumption of buildings [4] , [5] , [6] , so the changes in habits induced by COVID-19 lockdowns could affect building energy consumption patterns, although to our knowledge, this is largely undocumented at this point.…”

Section: Introductionmentioning

confidence: 96%

Impacts of the COVID-19 lockdown on energy consumption in a Canadian social housing building

2021

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The COVID-19 pandemic hit societies in full force in 2020 and compelled people all around the world to change their lifestyle. The time spent at home significantly surged during the pandemic and this change in occupancy can have a direct impact on building energy consumption. COVID-19 lockdowns also accelerated the transition towards telework, a trend that many expect to last. Changes in energy consumption under lockdown is thus a valuable asset to forecast how energy could be consumed in buildings in the future. Here, we aim to quantify the impacts of the COVID-19 lockdown on the energy consumption (electricity, hot water and space heating) in residential buildings by answering these two questions: (i) Did the lockdown lead to changes in total energy consumption?, and (ii) Did the lockdown lead to changes in consumption patterns (i.e. time of the day at which energy is consumed)? To do so, we compared the energy consumption measured in a 40-dwelling social housing building located in Quebec City (Canada) during four months of lockdown to those of the months that preceded the lockdown. It is found that consumption patterns for electricity and hot water changed for the first two months of the lockdown, when the most intensive lockdown measures were applied. Overall consumption slightly increased for these two energy expenditures, but the more important change was that consumption occurred throughout the day instead of being concentrated in the evening as observed before the lockdown. Results shed light on the impact of lockdown on energy bills for consumers and on how energy utilities might be solicited during this kind of episode.

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Section: Introductionmentioning

confidence: 96%

Impacts of the COVID-19 lockdown on energy consumption in a Canadian social housing building

2021

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“…Individual households have different electricity demand patterns, and it is unlikely that all customers have their peak demands occurring simultaneously. This is known as electricity demand diversity [17]. As a result, the peak demand of the aggregated group will be less than the sum of the individual maximum demand of each household in the group.…”

Section: Electricity Demand Diversitymentioning

confidence: 99%

Impact of Spatial Aggregation on Electricity Profiles

Alaa¹,

Krayem²,

Wallin³

2022

Preprint

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The increasing use of renewable energy and the spread of smart energy services require detailed studies of the system load. The data from the advanced metering infrastructure assist these requirements by providing detailed picture of electricity consumption patterns and profiles. However, high resolution electricity data can cause computational challenges and privacy concerns. As a result, the data are often spatially aggregated. This paper investigates the impact of data aggregation on the data understanding and the electricity load characteristics. The study looks at the similarity among different groups combinations within the same aggregation level, the variation in the load diversity and peaks occurrences, and on the hourly electricity variations between the individual customer and its aggregated group. The study concludes that the individual customers' behaviors are lost with the increasing levels of aggregation, and that the similarity among groups on the same aggregation level increases with the aggregation level.

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“…Methodologies are experimentally implemented. Accuracy of the model is calculated using R 2 and mean absolute percentage error in [108].…”

Section: A General Approachesmentioning

confidence: 99%

Building Occupancy Behavior and Prediction Methods: A Critical Review and Challenging Locks

et al. 2021

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Energy use in buildings is increasing to provide optimal comfort for the occupants. People spend 90% of their lifetime in buildings. Therefore, indoor environment quality and comfort management have a crucial role in maintaining occupants' health and productivity. Reducing energy consumption for optimal comfort management is important to minimize CO 2 emission and global warming by the building sector. According to the literature, it is possible to control and reduce energy consumption by monitoring occupants' behavior and estimating the number of occupants. A critical review is carried out in this paper to analyze the existing methodologies for modeling occupant behavior and prediction with respect to comfort and energy management. A comprehensive analysis is also performed on recent developments and challenges in modeling, along with recommendations and future perspectives.

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Impacts of diversity in commercial building occupancy profiles on district energy demand and supply

Cited by 43 publications

References 42 publications

Impacts of the COVID-19 lockdown on energy consumption in a Canadian social housing building

Impacts of the COVID-19 lockdown on energy consumption in a Canadian social housing building

Impact of Spatial Aggregation on Electricity Profiles

Building Occupancy Behavior and Prediction Methods: A Critical Review and Challenging Locks

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