Daily Occupant Behavior Pattern Affecting Energy Use in Residential Buildings

Author(s):  
Yunjeong Mo ◽  
Dong Zhao ◽  
James Sorce
2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Frederick Paige ◽  
Philip Agee ◽  
Farrokh Jazizadeh

AbstractThe 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.


2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4117
Author(s):  
Tadeusz Kuczyński ◽  
Anna Staszczuk ◽  
Piotr Ziembicki ◽  
Anna Paluszak

The main objective of this paper is to demonstrate the effectiveness of increasing the thermal capacity of a residential building by using traditional building materials to reduce the risk of its excessive overheating during intense heat waves in a temperate climate. An additional objective is to show that the use of this single passive measure significantly reduces the risk of overheating in daytime rooms, but also, though to a much lesser extent, in bedrooms. Increasing the thermal mass of the room from light to a medium heavy reduced the average maximum daily temperature by 2.2K during the first heat wave and by 2.6K during the other two heat waves. The use of very heavy construction further reduced the average maximum temperature for the heat waves analyzed by 1.4K, 1.2K and 1.7K, respectively, giving a total possible reduction in maximum daily temperatures in the range of 3.6 °C, 3.8 °C and 4.3 °C. A discussion of the influence of occupant behavior on the use of night ventilation and external blinds was carried out, finding a significant effect on the effectiveness of the use of both methods. The results of the study suggest that in temperate European countries, preserving residential construction methods with heavy envelopes and partitions could significantly reduce the risk of overheating in residential buildings over the next few decades, without the need for night ventilation or external blinds, whose effectiveness is highly dependent on individual occupant behavior.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2917
Author(s):  
Mohammad Dabbagh ◽  
Moncef Krarti

This paper evaluates the potential energy use and peak demand savings associated with optimal controls of switchable transparent insulation systems (STIS) applied to smart windows for US residential buildings. The optimal controls are developed based on Genetic Algorithm (GA) to identify the automatic settings of the dynamic shades. First, switchable insulation systems and their operation mechanisms are briefly described when combined with smart windows. Then, the GA-based optimization approach is outlined to operate switchable insulation systems applied to windows for a prototypical US residential building. The optimized controls are implemented to reduce heating and cooling energy end-uses for a house located four US locations, during three representative days of swing, summer, and winter seasons. The performance of optimal controller is compared to that obtained using simplified rule-based control sets to operate the dynamic insulation systems. The analysis results indicate that optimized controls of STISs can save up to 81.8% in daily thermal loads compared to the simplified rule-set especially when dwellings are located in hot climates such as that of Phoenix, AZ. Moreover, optimally controlled STISs can reduce electrical peak demand by up to 49.8% compared to the simplified rule-set, indicating significant energy efficiency and demand response potentials of the SIS technology when applied to US residential buildings.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.


2021 ◽  
Vol 13 (4) ◽  
pp. 1595
Author(s):  
Valeria Todeschi ◽  
Roberto Boghetti ◽  
Jérôme H. Kämpf ◽  
Guglielmina Mutani

Building energy-use models and tools can simulate and represent the distribution of energy consumption of buildings located in an urban area. The aim of these models is to simulate the energy performance of buildings at multiple temporal and spatial scales, taking into account both the building shape and the surrounding urban context. This paper investigates existing models by simulating the hourly space heating consumption of residential buildings in an urban environment. Existing bottom-up urban-energy models were applied to the city of Fribourg in order to evaluate the accuracy and flexibility of energy simulations. Two common energy-use models—a machine learning model and a GIS-based engineering model—were compared and evaluated against anonymized monitoring data. The study shows that the simulations were quite precise with an annual mean absolute percentage error of 12.8 and 19.3% for the machine learning and the GIS-based engineering model, respectively, on residential buildings built in different periods of construction. Moreover, a sensitivity analysis using the Morris method was carried out on the GIS-based engineering model in order to assess the impact of input variables on space heating consumption and to identify possible optimization opportunities of the existing model.


2021 ◽  
Vol 13 (12) ◽  
pp. 6753
Author(s):  
Moiz Masood Syed ◽  
Gregory M. Morrison

As the population of urban areas continues to grow, and construction of multi-unit developments surges in response, building energy use demand has increased accordingly and solutions are needed to offset electricity used from the grid. Renewable energy systems in the form of microgrids, and grid-connected solar PV-storage are considered primary solutions for powering residential developments. The primary objectives for commissioning such systems include significant electricity cost reductions and carbon emissions abatement. Despite the proliferation of renewables, the uptake of solar and battery storage systems in communities and multi-residential buildings are less researched in the literature, and many uncertainties remain in terms of providing an optimal solution. This literature review uses the rapid review technique, an industry and societal issue-based version of the systematic literature review, to identify the case for microgrids for multi-residential buildings and communities. The study describes the rapid review methodology in detail and discusses and examines the configurations and methodologies for microgrids.


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