UK office buildings archetypal model as methodological approach in development of regression models for predicting building energy consumption from heating and cooling demands

2013 ◽  
Vol 60 ◽  
pp. 152-162 ◽  
Author(s):  
Ivan Korolija ◽  
Ljiljana Marjanovic-Halburd ◽  
Yi Zhang ◽  
Victor I. Hanby
Keyword(s):  
Energy Consumption ◽  
Regression Models ◽  
Methodological Approach ◽  
Building Energy ◽  
Office Buildings ◽  
Building Energy Consumption ◽  
Heating And Cooling

scholarly journals Long-Term Prediction of Weather for Analysis of Residential Building Energy Consumption in Australia

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4805
Author(s):  
Shu Chen ◽  
Zhengen Ren ◽  
Zhi Tang ◽  
Xianrong Zhuo
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Residential Building ◽  
Building Energy ◽  
Space Heating ◽  
Building Energy Consumption ◽  
Climate Zones ◽  
Impact Of Climate Change ◽  
Heating And Cooling ◽  
The Impact

Globally, buildings account for nearly 40% of the total primary energy consumption and are responsible for 20% of the total greenhouse gas emissions. Energy consumption in buildings is increasing with the increasing world population and improving standards of living. Current global warming conditions will inevitably impact building energy consumption. To address this issue, this report conducted a comprehensive study of the impact of climate change on residential building energy consumption. Using the methodology of morphing, the weather files were constructed based on the typical meteorological year (TMY) data and predicted data generated from eight typical global climate models (GCMs) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) from 2020 to 2100. It was found that the most severe situation would occur in scenario RCP8.5, where the increase in temperature will reach 4.5 °C in eastern Australia from 2080–2099, which is 1 °C higher than that in other climate zones. With the construction of predicted weather files in 83 climate zones all across Australia, ten climate zones (cities)—ranging from heating-dominated to cooling-dominated regions—were selected as representative climate zones to illustrate the impact of climate change on heating and cooling energy consumption. The quantitative change in the energy requirements for space heating and cooling, along with the star rating, was simulated for two representative detached houses using the AccuRate software. It could be concluded that the RCP scenarios significantly affect the energy loads, which is consistent with changes in the ambient temperature. The heating load decreases for all climate zones, while the cooling load increases. Most regions in Australia will increase their energy consumption due to rising temperatures; however, the energy requirements of Adelaide and Perth would not change significantly, where the space heating and cooling loads are balanced due to decreasing heating and increasing cooling costs in most scenarios. The energy load in bigger houses will change more than that in smaller houses. Furthermore, Brisbane is the most sensitive region in terms of relative space energy changes, and Townsville appears to be the most sensitive area in terms of star rating change in this study. The impact of climate change on space building energy consumption in different climate zones should be considered in future design strategies due to the decades-long lifespans of Australian residential houses.

Tool for Hourly Energy Consumption Estimation in Existing Office Buildings

2014 ◽  
Author(s):  
Nelson Fumo ◽  
Pedro J. Mago ◽  
Emily Ledbury
Keyword(s):  
Energy Consumption ◽  
Cooling System ◽  
Good Practice ◽  
Cost Effective ◽  
Weather Conditions ◽  
Building Energy ◽  
Office Buildings ◽  
Building Energy Consumption ◽  
Energy Profiles ◽  
Building Operation

Building energy consumption analysis is a difficult task because it depends on the characteristics and interaction among the building, the heating/cooling system, and the surroundings. Since the evaluation of building energy consumption usually requires building energy profiles on an hourly basis, which often is not available for existing buildings, the hourly energy consumption must be estimated. The dynamic behavior of the weather conditions and building operation makes computer simulations a good practice for reliable solutions. However, an energy building computer simulation requires a significant amount of experience, time, and effort to enter detailed building parameters, which is a drawback for a cost-effective solution. Therefore, simplified models based on statistics or a combination of statistics and simulations may be a better solution with reasonable uncertainty. This paper presents a tool to estimate hourly building energy consumption for existent office buildings. The proposed tool, developed in Microsoft Excel, uses simulation data from EnergyPlus Commercial Reference Buildings to convert monthly energy consumption from utility bills into hourly energy consumption. Results account for baseline and variable energy consumption for electricity and fuel. The site weather conditions, for which the energy consumption is estimated, are considered using the sixteen climate zones of the U.S.

Tool for Small Office Buildings Energy Consumption Estimation

2010 ◽  
Author(s):  
N. Fumo ◽  
P. J. Mago
Keyword(s):  
Energy Consumption ◽  
Computer Simulations ◽  
Cooling System ◽  
Good Practice ◽  
Cost Effective ◽  
Weather Conditions ◽  
Building Energy ◽  
Office Buildings ◽  
Building Energy Consumption ◽  
The U.S

Building energy consumption analysis is a difficult task because it depends on the characteristics and interaction among the building, the heating/cooling system, and the surroundings (weather). Since building energy profiles are usually required on an hourly basis, which often is not available for existing buildings, the hourly energy consumption must be estimated or predicted. The dynamic behavior of the weather conditions and building operation makes computer simulations a good practice for reliable solutions. However, energy building computer simulations require considerable amount of detailed input data and user time, which is a drawback for a cost-effective solution. Therefore, simplified models based on statistics or a combination of statistics and simulations may be a better solution with reasonable uncertainty. This paper presents the tool Small Office Hourly Energy Consumption Estimator (SOHECE). The tool estimates hourly building energy consumption for small office buildings. The proposed tool has been developed in Microsoft Excel and it uses simulation data from EnergyPlus benchmark models to convert monthly energy consumption from utility bills into hourly energy consumption. Since benchmark models were developed by the U.S. government to provide a consistent baseline of comparison, energy consumption data from simulations of the benchmark models are considered reasonable representations of energy consumption profiles. Results account for baseline and variable energy consumption for electricity and fuel. The site weather conditions, for which the energy consumption is estimated, are considered using the sixteen climate zones of the U.S. benchmark models. The tool has been applied to a hypothetical building placed in Meridian, MS, and errors obtained for the estimated hourly energy consumption are mainly lower than ten percent.

scholarly journals Energy Analysis of 4625 Office Buildings in South Korea

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1114
Author(s):  
Ki Ahn ◽  
Han Shin ◽  
Cheol Park
Keyword(s):  
Energy Consumption ◽  
South Korea ◽  
Energy Analysis ◽  
Cooling System ◽  
Building Energy ◽  
Office Buildings ◽  
Building Energy Efficiency ◽  
Building Energy Consumption ◽  
Energy Codes ◽  
Building Energy Codes

The purpose of the present study was to investigate the relevance of building thermal performance and characteristics to building energy consumption. This paper reports an energy analysis of 4625 office buildings in Seoul, South Korea, using data from the Korean national building energy database and architectural database. The following four research questions were investigated: (1) Do old buildings consume more energy than new ones? (2) Have strict prescriptive building energy codes contributed to the reduction in energy use intensity (EUI, kWh/m2·year) over the past several decades? (3) What are the characteristics of building energy consumption in terms of season, age, and cooling system (electric chiller vs absorption chiller)? (4) Which factors in the Korean building energy database are relevant to building energy consumption? The analyses revealed that, contrary to common assumptions, new buildings did not always consume less energy than old buildings, and it may be wrong to attribute intensification of prescriptive building energy codes directly to building energy efficiency improvements. In addition, the building characteristics (i.e., district, year built, number of floors, number of elevators, and total floor area) available in the Korean building energy database do not adequately explain building energy consumption, and the existing data collection method needs further improvement.

The Impact of Double Skin Facade on Building Energy Consumption in Daylighting Control Mode

2013 ◽  
Vol 353-356 ◽  
pp. 3105-3108 ◽  
Author(s):  
Hua Yang ◽  
Xiang Xiang Sun ◽  
Guo Qiang Xia ◽  
Chun Hua Sun ◽  
Cai Ling Chen
Keyword(s):  
Energy Consumption ◽  
Building Energy ◽  
Control Mode ◽  
Building Energy Consumption ◽  
Air Cavity ◽  
Heating And Cooling ◽  
Double Skin ◽  
Daylighting Control ◽  
The Impact ◽  
Cavity Width

Energyplus is used to discuss the impact of double skin façade (DSF) on building lights, heating and cooling energy consumption in daylighting control mode by simulating the building lights, heating and cooling energy consumption with different height of double skin façade (DSF) and different air cavity width .Thus the influence rules on the lights, heating and cooling energy in daylighting control mode can be found.

scholarly journals Review on Urban Heat Island in China: Methods, Its Impact on Buildings Energy Demand and Mitigation Strategies

2021 ◽  
Vol 13 (2) ◽  
pp. 762
Author(s):  
Liu Tian ◽  
Yongcai Li ◽  
Jun Lu ◽  
Jue Wang
Keyword(s):  
Energy Consumption ◽  
Urban Heat Island ◽  
Building Energy ◽  
Design Stage ◽  
Heat Island ◽  
Building Energy Consumption ◽  
Rapid Urbanization ◽  
Substantial Impact ◽  
Urban Heat ◽  
The Impact

High population density, dense high-rise buildings, and impervious pavements increase the vulnerability of cities, which aggravate the urban climate environment characterized by the urban heat island (UHI) effect. Cities in China provide unique information on the UHI phenomenon because they have experienced rapid urbanization and dramatic economic development, which have had a great influence on the climate in recent decades. This paper provides a review of recent research on the methods and impacts of UHI on building energy consumption, and the practical techniques that can be used to mitigate the adverse effects of UHI in China. The impact of UHI on building energy consumption depends largely on the local microclimate, the urban area features where the building is located, and the type and characteristics of the building. In the urban areas dominated by air conditioning, UHI could result in an approximately 10–16% increase in cooling energy consumption. Besides, the potential negative effects of UHI can be prevented from China in many ways, such as urban greening, cool material, water bodies, urban ventilation, etc. These strategies could have a substantial impact on the overall urban thermal environment if they can be used in the project design stage of urban planning and implemented on a large scale. Therefore, this study is useful to deepen the understanding of the physical mechanisms of UHI and provide practical approaches to fight the UHI for the urban planners, public health officials, and city decision-makers in China.

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