Building Energy Performance Using Sheap

1992 ◽  
pp. 43-56
Author(s):  
Mat Nawi Wan Hassan ◽  
Mohd Yusoff Senawi
Keyword(s):  
Energy Analysis ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Weighting Factor ◽  
Climatic Conditions ◽  
Heat Extraction ◽  
Weather Data ◽  
Commercial Building ◽  
Analysis Package

This paper describes a Simplified Hourly Energy Analysis Package (SHEAP) for the computation of annual energy consumption in non-residential buildings. The package, developed at the Mechanical Engineering Faculty, uses the transmission matrix method in calculating conduction heat gains through opaque building sections, and adopts the weighting factor method for the calculations of cooling loads, heat extraction rates and actual space air dry bulb temperatures. Typical daily profiles of measured hourly weather data are used to approximate the external climatic conditions over a one-year period. A preliminary validation study indicates that SHEAP produces, reasonably good estimates when compared to the predictions by BUNYIP, a commercial building energy analysis package.

scholarly journals Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 802
Author(s):  
Kristian Skeie ◽  
Arild Gustavsen
Keyword(s):  
Solar Radiation ◽  
Web Service ◽  
Meteorological Data ◽  
Surface Wind ◽  
Building Energy ◽  
Energy Performance ◽  
Geospatial Data ◽  
Weather Data ◽  
Building Site ◽  
Incident Solar Radiation

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

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 Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang
Keyword(s):  
Large Scale ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Modeling ◽  
Office Buildings ◽  
Building Energy Modeling ◽  
Downtown Area ◽  
Point Of Interest

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.

Development of a numerical approach to assess the effect of coupled heat and moisture transfer on energy consumption of residential buildings in Moroccan context

2021 ◽  
pp. 174425912110560
Author(s):  
Yassine Chbani Idrissi ◽  
Rafik Belarbi ◽  
Mohammed Yacine Ferroukhi ◽  
M’barek Feddaoui ◽  
Driss Agliz
Keyword(s):  
Energy Consumption ◽  
Building Materials ◽  
Moisture Transfer ◽  
Residential Buildings ◽  
Building Design ◽  
Energy Performance ◽  
Climatic Conditions ◽  
Heat And Moisture Transfer ◽  
Coupled Heat And Moisture ◽  
Heat And Moisture

Hygrothermal properties of building materials, climatic conditions and energy performance are interrelated and have to be considered simultaneously as part of an optimised building design. In this paper, a new approach to evaluate the energy consumption of residential buildings in Morocco is presented. This approach is based on the effect of coupled heat and moisture transfer in typical residential buildings and on their responses to the varied climatic conditions encountered in the country. This approach allows us to evaluate with better accuracy the response of building energy performance and the indoor comfort of building occupants. Annual energy consumption, cooling and heating energy requirements were estimated considering the six climatic zones of Morocco. Based on the results, terms related to coupled heat and moisture transfer can effectively correct the existing energy consumption calculations of the six zones of Morocco, which currently do not consider energy consumption due to coupled heat and moisture transfer.

PERFORMANCE INDICATORS FOR ENERGY EFFICIENCY RETROFITTING IN MULTIFAMILY RESIDENTIAL BUILDINGS

2019 ◽  
Vol 14 (2) ◽  
pp. 109-136
Author(s):  
Chaitali Basu ◽  
Virendra Kumar Paul ◽  
M.G. Matt Syal
Keyword(s):  
Energy Efficiency ◽  
Performance Assessment ◽  
Performance Indicators ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Assessment Process ◽  
Second Phase ◽  
A Priority

The energy performance of an existing building is the amount of energy consumed to meet various needs associated with the standardized use of a building and is reflected in one or more indicators known as Building Energy Performance Indicators (EnPIs). These indicators are distributed amongst six main factors influencing energy consumption: climate, building envelope, building services and energy systems, building operation and maintenance, occupants' activities and behaviour, and indoor environmental quality. Any improvement made to either the existing structure or the physical and operational upgrade of a building system that enhances energy performance is considered an energy efficiency retrofit. The main goal of this research is to support the implementation of multifamily residential building energy retrofits through expert knowledge consensus on EnPIs for energy efficiency retrofit planning. The research methodology consists of a comprehensive literature review which has identified 35 EnPIs for assessing performance of existing residential buildings, followed by a ranking questionnaire survey of experts in the built-environment to arrive at a priority listing of indicators based on mean rank. This was followed by concordance analysis and measure of standard deviation. A total of 280 experts were contacted globally for the survey, and 106 completed responses were received resulting in a 37.85% response rate. The respondents were divided into two groups for analysis: academician/researchers and industry practitioners. The primary outcome of the research is a priority listing of EnPIs based on the quantitative data from the knowledge-base of experts from these two groups. It is the outcome of their perceptions of retrofitting factors and corresponding indicators. A retrofit strategy consists of five phases for retrofitting planning in which the second phase comprises an energy audit and performance assessment and diagnostics. This research substantiates the performance assessment process through the identification of EnPIs.

scholarly journals How Climate Trends Impact on the Thermal Performance of a Typical Residential Building in Madrid

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 237 ◽  
Author(s):  
S. Soutullo ◽  
E. Giancola ◽  
M. J. Jiménez ◽  
J. A. Ferrer ◽  
M. N. Sánchez
Keyword(s):  
Residential Buildings ◽  
Minimum Energy ◽  
Residential Building ◽  
Energy Performance ◽  
Weather Data ◽  
Design Strategies ◽  
Climate Trends ◽  
Average Value ◽  
Minimum Energy Consumption ◽  
The Impact

Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of residential buildings in order to derive potential design strategies. Different climate file inputs of Madrid have been used to quantify comparatively the thermal needs of two reference residential buildings located in this city. One of them represents buildings older than 40 years built according to the applicable Spanish regulations prior to 1979. The other refers to buildings erected in the last decade under more energy-restrictive constructive regulations. Three different climate databases of Madrid have been used to assess the impact of the evolution of the climate in recent years on the thermal demands of these two reference buildings. Two of them are typical meteorological years (TMY) derived from weather data measured before 2000. On the contrary, the third one is an experimental file representing the average values of the meteorological variables registered in Madrid during the last decade. Annual and monthly comparisons are done between the three climate databases assessing the climate changes. Compared to the TMYs databases, the experimental one records an average air temperature of 1.8 °C higher and an average value of relative humidity that is 9% lower.

Development of Extreme Reference Years for Building Energy Simulation Scenarios

2019 ◽  
Vol 887 ◽  
pp. 129-139 ◽  
Author(s):  
Giovanni Pernigotto ◽  
Alessandro Prada ◽  
Andrea Gasparella
Keyword(s):  
Development Process ◽  
Building Energy ◽  
Energy Performance ◽  
Solar Irradiation ◽  
Weather Data ◽  
Building Energy Simulation ◽  
Technical Standard ◽  
Alpine Regions ◽  
Cross Correlations

Typical years are developed from the analysis of multi-year series, selecting actual months to assembly in a single reference year, representative of the long-term typical weather. Some statistical techniques are generally involved in the development process to ensure true frequencies, sequences and cross-correlations of the weather quantities: as regard the reference year built according to the European technical standard EN ISO 15927-4:2005, TRYEN, the method is based on the Finkelstein-Schafer statistics. In this work, we exploit the same statistic with a different target: to develop an extreme reference year, ERY, by identifying those candidate months far from being representative of the long-term weather data distribution. These new artificial extreme years are composed of statistically “non-representative” months warmer in the summer and colder in the winter - which means with daily dry bulb temperature and global solar irradiation higher in summer or lower in winter than the long-term averages respectively. The analysis is performed for five Italian localities belonging to the Alpine Regions and to Sicily. Aiming to assess the efficacy of the proposed procedure, TRYEN and ERY are compared and both used to simulate the energy performance of 48 simplified buildings, parametrically built by varying insulation level, windows’ size, orientation and SHGC and kind of opaque elements.

Building energy performance diagnosis using energy bills and weather data

2018 ◽  
Vol 172 ◽  
pp. 181-191 ◽  
Author(s):  
Yang Geng ◽  
Wenjie Ji ◽  
Borong Lin ◽  
Jiajie Hong ◽  
Yingxin Zhu
Keyword(s):  
Building Energy ◽  
Energy Performance ◽  
Weather Data ◽  
Building Energy Performance ◽  
Performance Diagnosis
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