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

A Comparative Study on Building Energy Performance between Movable and Fixed Shading Materials

2012 ◽  
Vol 164 ◽  
pp. 85-88
Author(s):  
Xiao Chang Yang ◽  
Jian Yao
Keyword(s):  
Energy Use ◽  
Residential Building ◽  
Building Energy ◽  
Energy Performance ◽  
Simulation Software ◽  
Public Building ◽  
Building Energy Performance ◽  
Energy Demands ◽  
Building Energy Use ◽  
Better Than

The purpose of this paper is to investigate the effect of movable shading on building energy demands. A public building and a residential building with movable shading and fixed shading were modeled by the building energy use simulation software DOE-2. Cooling and heating energy demands were calculated. The results showed that movable shading is better than fixed shading.

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 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.

scholarly journals Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

2018 ◽  
Vol 10 (8) ◽  
pp. 2635 ◽  
Author(s):  
Vivian Tam ◽  
Laura Almeida ◽  
Khoa Le
Keyword(s):  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Design Stage ◽  
Occupant Behaviour ◽  
Building Energy Use ◽  
Key Variables ◽  
The Difference ◽  
The One ◽  
Building Life Cycle

It is essential to understand how significantly occupants’ actions impact the performance of a building, as a whole, in terms of energy use. Consequently, this paper reviews the available resources on energy-related occupant behaviour and its implications in energy use in a building. A chronological review on energy-related occupant behaviour and its implications in energy use has been conducted. As a main existing gap, it was identified by researchers the difference between real energy performance and the one that is predicted during the design stage of a building. The energy predicted during the design stage of a building may be over twice the energy used in the operation stage. Buildings are one of the most energy intensive features in a country. They are affected by the interaction and correlation of several different variables, such as: its physical characteristics, technical systems, equipment, occupants, etc. Therefore, buildings are considered to be complex systems that require a careful and intensive analysis. Moreover, one of the key variables impacting real building energy use is occupant behaviour. The way occupants behave and their motivations are some of the main aspects that need to be considered in a building life-cycle.

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 Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings

Buildings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 122
Author(s):  
Bongchan Jeong ◽  
Jungsoo Kim ◽  
Zhenjun Ma ◽  
Paul Cooper ◽  
Richard de Dear
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Use ◽  
Residential Buildings ◽  
Significant Proportion ◽  
Building Energy ◽  
Energy Performance ◽  
Time Of Day ◽  
Performance Simulation ◽  
Building Energy Performance

Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and actual energy use. The objective of this study was to develop a stochastic model for predicting occupant behaviour relating to A/C cooling and heating in residential buildings located in the Subtropical Sydney region of Australia. Multivariate logistic regression was used to estimate the probability of using A/C in living rooms and bedrooms, based on a range of physical environmental (outdoor and indoor) and contextual (season, day of week, and time of day) factors observed in 42 Sydney region houses across a two-year monitoring period. The resulting models can be implemented in building energy performance simulation (BEPS) tools to more accurately predict indoor environmental conditions and energy consumption attributable to A/C operation.

scholarly journals The ambivalence of personal control over indoor climate – how much personal control is adequate?

2020 ◽  
Vol 172 ◽  
pp. 06010
Author(s):  
Runa T. Hellwig ◽  
Marcel Schweiker ◽  
Atze Boerstra
Keyword(s):  
User Satisfaction ◽  
Perceived Control ◽  
Energy Use ◽  
Sick Building Syndrome ◽  
Personal Control ◽  
Building Energy ◽  
Energy Performance ◽  
Indoor Climate ◽  
Building Energy Use ◽  
Automation Systems

Literature sets personal control over indoor environmental conditions in relation to the gap between predicted and actual energy use, the gap between predicted and observed user satisfaction, and health aspects. A focus on building energy performance often leads to the proposal of more automated and less occupant control of the indoor environment. However, a high degree of personal control is desirable because research shows that a low degree (or no) personal control highly correlates with indoor environmental dissatisfaction and sick building syndrome symptoms. These two tendencies seem contradictory and optimisation almost impossible. Based on current efficiency classes describing the effect of room automation systems on building energy use during operation, fundamental thoughts related to thermophysiology and control, recent laboratory experiments, important lessons learnt from post-occupancy studies, and documented conceptual frameworks on the level of control perceived, we discuss the ambivalence of personal control and how much personal control is adequate. Often-proposed solutions ranging from fully automated controls, over manual controls to dummy controls are discussed according to their effect on a) building energy use during operation and b) occupants perceived control. The discussion points to the importance of adequate personal control. In order to meet the goals for nearly zero energy buildings and for a human-centric design, there is the need to establish design procedures for adequate personal control as part of the design process.

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