scholarly journals Influence of User-Related Parameters on Calculated Energy Use in Low-Energy School Buildings

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2985 ◽  
Author(s):  
Branko Simanic ◽  
Birgitta Nordquist ◽  
Hans Bagge ◽  
Dennis Johansson
Keyword(s):  
Energy Use ◽  
Ventilation System ◽  
Building Energy ◽  
Energy Performance ◽  
Hot Water ◽  
Low Energy ◽  
Building Energy Use ◽  
Low Energy Buildings ◽  
Demand Controlled Ventilation ◽  
The Impact

Literature and experience show that there are large discrepancies between the calculated and measured building energy usages, where user-related parameters are significant factors with regard to energy use in low-energy buildings. Furthermore, the difficulties encountered when quantifying these parameters compound these discrepancies. The main aim of this study was to provide feedback that would help the building industry and research communities to predict more accurately the impact of the user-related parameters on energy performance. The results of the study would, subsequently, contribute to minimizing the discrepancies between calculated and measured energy use. This article analyses simulated building energy use based on randomly chosen combinations of measured user-related parameters in three recently built low-energy schools in Sweden. The results show that energy performance can span from 30 to 160 kWh/(m² y) simply by varying the combination of previously measured user-related parameters in building energy simulations. The study shows that the set points for indoor air temperatures during the heating season and the energy required to run a demand-controlled ventilation system have an extensive influence, while tenant electricity use has a slightly lower influence on building energy use. Variations in occupancy rates and energy for hot water usage have the smallest influences on building energy use.

scholarly journals Evaluation of Urban-Scale Building Energy-Use Models and Tools—Application for the City of Fribourg, Switzerland

2021 ◽  
Vol 13 (4) ◽  
pp. 1595
Author(s):  
Valeria Todeschi ◽  
Roberto Boghetti ◽  
Jérôme H. Kämpf ◽  
Guglielmina Mutani
Keyword(s):  
Machine Learning ◽  
Energy Use ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Space Heating ◽  
Engineering Model ◽  
Building Energy Use ◽  
The Impact ◽  
The City

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.

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

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Frederick Paige ◽  
Philip Agee ◽  
Farrokh Jazizadeh
Keyword(s):  
Affordable Housing ◽  
Energy Use ◽  
Residential Buildings ◽  
Building Energy ◽  
Hot Water ◽  
Occupant Behavior ◽  
Zero Energy ◽  
Net Zero Energy ◽  
Net Zero ◽  
Building Energy Use

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.

Thermal Bridges Minimizing through Typical Details in Low Energy Designing

2014 ◽  
Vol 899 ◽  
pp. 62-65 ◽  
Author(s):  
Rastislav Ingeli ◽  
Boris Vavrovič ◽  
Miroslav Čekon
Keyword(s):  
Energy Efficiency ◽  
Thermal Insulation ◽  
Energy Demand ◽  
Building Energy ◽  
Building Envelope ◽  
Low Energy ◽  
Building Energy Efficiency ◽  
Low Energy Buildings ◽  
Thermal Bridges ◽  
The Impact

Energy demand reduction in buildings is an important measure to achieve climate change mitigation. It is essential to minimize heat losses in designing phase in accordance of building energy efficiency. For building energy efficiency in a mild climate zone, a large part of the heating demand is caused by transmission losses through the building envelope. Building envelopes with high thermal resistance are typical for low-energy buildings in general. In this sense thermal bridges impact increases by using of greater thickness of thermal insulation. This paper is focused on thermal bridges minimizing through typical system details in buildings. The impact of thermal bridges was studied by comparative calculations for a case study of building with different amounts of thermal insulation. The calculated results represent a percentage distribution of heat loss through typical building components in correlation of various thicknesses of their thermal insulations.

Evaluation of the Impact of Window Shading on the Anti-Insulation Phenomenon in Building Energy Use

MRS Advances ◽  
2018 ◽  
Vol 3 (34-35) ◽  
pp. 2063-2073
Author(s):  
R. K. Rabasoma ◽  
D. D. Serame ◽  
O.T. Masoso
Keyword(s):  
Solar Radiation ◽  
Energy Use ◽  
Common Knowledge ◽  
Building Design ◽  
Building Energy ◽  
Climatic Regions ◽  
Building Energy Use ◽  
The World ◽  
Building Design Decisions ◽  
The Impact

ABSTRACTBefore 2008, it was common knowledge around the world that insulation always saved air conditioning energy in buildings. In 2008 a phenomenon called anti-insulation was brought to light by Masoso & Grobler. They demonstrated that there are instances when insulation materials in a building directly increase building energy use. Researchers around the world then echoed the message. Recent work by some of the authors investigated the anti-insulation phenomenon in summer and winter for both hot climatic regions (Botswana) and cold climatic regions (Canada). Their study concluded that there is still a mystery of exaggerated sources of heat inside the building aggravating the anti-insulation phenomenon. They hypothesized that incident solar radiation through the windows could be one of the causes. This paper therefore focuses on eliminating direct solar radiation through windows by applying external shadings on a previously anti-insulation building. The energy saved is evaluated and the possible reversal of anti-insulation studied. The study is useful to energy policy makers and the building industry as it showcases the existence of a possible silent killer (anti-insulation) and demonstrates that investing large sums of money on insulation in buildings may not be the most economic thing to do in building design decisions.

scholarly journals Big-data for building energy performance: Lessons from assembling a very large national database of building energy use

2015 ◽  
Vol 140 ◽  
pp. 85-93 ◽  
Author(s):  
Paul A. Mathew ◽  
Laurel N. Dunn ◽  
Michael D. Sohn ◽  
Andrea Mercado ◽  
Claudine Custudio ◽  
...  
Keyword(s):  
Big Data ◽  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
National Database ◽  
Building Energy Performance ◽  
Building Energy Use ◽  
Large National Database

scholarly journals How Smart Meter Data Analysis Can Support Understanding the Impact of Occupant Behavior on Building Energy Performance: A Comprehensive Review

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2502
Author(s):  
Jacqueline Nicole Adams ◽  
Zsófia Deme Bélafi ◽  
Miklós Horváth ◽  
János Balázs Kocsis ◽  
Tamás Csoknyai
Keyword(s):  
Western Europe ◽  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Smart Meter ◽  
Occupant Behavior ◽  
Psychological Determinants ◽  
Data Limitations ◽  
Holistic Understanding ◽  
The Impact

The goal of this literature review was to outline the research currently conducted on smart meter (SM) adoption and its connection to building occupant behavior to better understand both SM technology and SM customers. We compiled our findings from the existing literature and developed a holistic understanding of the socio-demographic factors that lead to more or less energy use, the methods used to group and cluster occupants on the basis of energy use, how occupant energy use profiles are developed, and which socio-psychological determinants may influence SM adoption. Our results highlight 11 demographic variables that impact building energy use, find 9 methods commonly used to profile occupants on the basis of energy usage, and highlight 13 socio-psychological variables than can be utilized to better understand SM adoption intentions. The review findings two major deficiencies in the existing literature. First, this review highlights the lack of existing interdisciplinary research that combines occupant behavior with SM data and a clear socio-psychological framework. Second, this review underscores certain data limitations in existing SM research, with most research being conducted only on residential or office buildings and geographically in North America or Western Europe. Final policy recommendations center on increased need for interdisciplinary SM research and the need for an expanded understanding of occupant behavior and SM research across different geographies.

scholarly journals The Impact of Trees on Building Energy Use

2019 ◽  
Author(s):  
Ulrike Passe ◽  
Jan Thompson ◽  
Baskar Ganapathysubramanian ◽  
Boshun Gao ◽  
Breanna Marmur ◽  
...  
Keyword(s):  
Energy Use ◽  
Building Energy ◽  
Building Energy Use ◽  
The Impact

scholarly journals Analysis of the Impact of the Fireplace Heating on the Energy Performance of the Family House

2020 ◽  
Vol 64 (2) ◽  
pp. 145-149
Author(s):  
Rastislav Ingeli ◽  
Peter Buday
Keyword(s):  
Energy Efficient ◽  
Energy Use ◽  
Energy Performance ◽  
Building Envelope ◽  
Cold Climate ◽  
Hot Water ◽  
Energy Class ◽  
Main Concern ◽  
Technical Equipment ◽  
The Impact

Reduction of energy use in buildings is an important measure to achieve climate changes of mitigation. It is essential to minimize heat losses when designing energy efficient buildings. For energy efficient building in a cold climate, a large part of the space heating demand is caused by transmission losses through the building envelope. In compliance with the today's trend of designing sustainable and energy-saving architecture, it is necessary firstly to solve the factors influencing the energy balance. This year the subsidy for houses has been valued at € 8,000. The condition is that the building is classified in the energy class A0 according to the Energy Performance Act. Energy class A0 characterizes nearly zero energy buildings. The main concern is for the public to become interested in such buildings. The subsidy is designed to reward and promote those buildings that their heat and technical characteristics and modern technical equipment that meet energy class. In addition to a good plan to raise the profile of such buildings, there has been a lot of speculation to help make buildings in energy class A0. They are mainly owners of family houses where there is no gasification and are forced to have electricity as a source of heat and hot water. Electricity has a high primary energy factor, which means that buildings do not have to be approved.

scholarly journals Impact of space layout on energy performance of office buildings coupling daylight with thermal simulation

2019 ◽  
Vol 111 ◽  
pp. 03077 ◽  
Author(s):  
Tiantian Du ◽  
Sabine Jansen ◽  
Michela Turrin ◽  
Andy van den Dobbelsteen
Keyword(s):  
Architectural Design ◽  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Thermal Simulation ◽  
Floor Plan ◽  
Building Energy Performance ◽  
Artificial Lighting ◽  
Space Layout ◽  
The Impact

Space layout design is one of the most important phases in architectural design, and current studies have shown that it can affect building energy performance. However, its influence has not been quantified. This paper aims at investigating the impact of space layouts on building energy performance. We use the floor plan of an office building in the Netherlands as reference, and propose eleven space layouts based on the reference. Calculations are performed with the tools Honeybee and Ladybug in Grasshopper, which are developed based on Daysim and EnergyPlus, to simulate lighting, cooling and heating demand of these layouts. In addition, we couple daylight with thermal simulation, by importing the artificial lighting schedule calculated in Daysim to EnergyPlus. The result shows that the heating demand of the worst layout is 12% higher than the best layout, the cooling demand of the worst layout is 10% higher than the best layout, and the lighting demand of the worst layout is 65% higher than the best layout. The total final energy use of the worst layout is 19% higher than the best layout.

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