flEECe, an energy use and occupant behavior dataset for net-zero energy affordable senior residential buildings

Abstract

The behaviors of building occupants have continued to perplex scholars for years in our attempts to develop models for energy efficient housing. Building simulations, project delivery approaches, policies, and more have fell short of their optimistic goals due to the complexity of human behavior. As a part of a multiphase longitudinal affordable housing study, this dataset represents energy and occupant behavior attributes for 6 affordable housing units over nine months in Virginia, USA which are not performing to the net-zero energy standard they were designed for. This dataset provides researchers the ability to analyze the following variables: energy performance, occupant behaviors, energy literacy, and ecological perceptions. Energy data is provided at a 1 Hz sampling rate for four circuits: main, hot water heater, dryer, and HVAC. Building specifications, occupancy, weather data, and neighboring building energy use data are provided to add depth to the dataset. This dataset can be used to update building energy use models, predictive maintenance, policy frameworks, construction risk models, economic models, and more.

Strategies and scenarios to reduce energy consumption and CO2 emission in the urban, rural and sustainable neighbourhoods

“…In fact, temperature variation directly modifies the cooling and heating loads. Energy consumption and carbon emissions are dependent upon the behaviour of the occupants of buildings and their living modes (de Meester et al, 2013;Paige et al, 2019). (Paige et al (2019) claimed that researchers were perplexed for a long time by the behaviour of inhabitants within their residences.…”

“…Energy consumption and carbon emissions are dependent upon the behaviour of the occupants of buildings and their living modes (de Meester et al, 2013;Paige et al, 2019). (Paige et al (2019) claimed that researchers were perplexed for a long time by the behaviour of inhabitants within their residences. In reality, the major goal of energy optimisation in buildings is difficult to achieve because of the lack of total control and the complexity of behaviours exhibited by the occupants.…”

“…Many global researchers use the empirical models developed in 1960 to assess the regulation of indoor climate; however, this is mainly based on standards that were developed for an average middle-aged male. It is imperative to assess the behaviours of both sexes to understand the overall behaviours of occupants (Kingma & Wouter van Marken, 2015), as well as the needs of the elderly (de Meester et al, 2013;Paige et al, 2019). In residential neighbourhoods, carbon emissions and energy consumption (in respect to heating and cooling) are increasing rapidly; this is, in part, because of the large variations exhibited in the outdoor climate (Chuan et al, 2019).…”

CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets

“…Authors in 36 offer data related to outdoor and indoor environment, as well as energy and occupant behavior collected from 17 cell offices over the period of four years. Authors in 37 provide data on energy use and occupant behavior recorded from six net-zero energy senior housing units over the period of nine months. And, authors in 38 provide data on room-level occupant counts and environmental data of three rooms in a building recorded over the period of 44 days.…”

Effects of Pro-Ecological Investments on an Example of the Heating Industry—Case Study

“…Changes in lighting methods (led) and energy creation (photovoltaics, wind turbines, nuclear power plants) [53][54][55][56] The investment process consists of a thoughtful, responsible action to abandon current consumption and to use these funds for a specific purpose, one that is intended to bring certain benefits in the future [60][61][62][63]. All investments must be of a long-term nature and involve a certain rate of return.…”