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 Identifying suitable general circulation model for future building cooling energy analysis

2019 ◽  
Vol 111 ◽  
pp. 06056
Author(s):  
Kuo-Tsang Huang ◽  
Yu-Teng Weng ◽  
Ruey-Lung Hwang
Keyword(s):  
General Circulation ◽  
Meteorological Data ◽  
Circulation Model ◽  
Building Energy ◽  
Building Simulation ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Global Circulation Models ◽  
The Future ◽  
Energy Use Intensity

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.

scholarly journals Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

2020 ◽  
Vol 12 (17) ◽  
pp. 6788 ◽  
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Vicente Gutiérrez González ◽  
Antonis Peppas ◽  
Carlos Fernández Bandera
Keyword(s):  
Energy Demand ◽  
Meteorological Data ◽  
Building Energy ◽  
Third Party ◽  
Weather Data ◽  
Data Sets ◽  
Weather Station ◽  
Energy Models ◽  
The Impact ◽  
Energy Strategies

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

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

scholarly journals MODELING AND SIMULATION OF RELIEF INFLUENCE ON EUCALYPTUS FORESTS: INTERACTION BETWEEN SOLAR IRRADIANCE AND PRODUCTIVITY

2016 ◽  
Vol 40 (2) ◽  
pp. 319-327
Author(s):  
Yhasmin Paiva Rody ◽  
Aristides Ribeiro ◽  
Aline Santana de Oliveira ◽  
Fernando Palha Leite
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Geographical Location ◽  
Area Index ◽  
Model Simulations ◽  
Incident Solar Radiation ◽  
Eucalyptus Forest ◽  
Vertical Location ◽  
Weather Stations ◽  
Study Sites

ABSTRACT This study aimed to verify the differences in radiation intensity as a function of distinct relief exposure surfaces and to quantify these effects on the leaf area index (LAI) and other variables expressing eucalyptus forest productivity for simulations in a process-based growth model. The study was carried out at two contrasting edaphoclimatic locations in the Rio Doce basin in Minas Gerais, Brazil. Two stands with 32-year-old plantations were used, allocating fixed plots in locations with northern and southern exposure surfaces. The meteorological data were obtained from two automated weather stations located near the study sites. Solar radiation was corrected for terrain inclination and exposure surfaces, as it is measured based on the plane, perpendicularly to the vertical location. The LAI values collected in the field were used. For the comparative simulations in productivity variation, the mechanistic 3PG model was used, considering the relief exposure surfaces. It was verified that during most of the year, the southern surfaces showed lower availability of incident solar radiation, resulting in up to 66% losses, compared to the same surface considered plane, probably related to its geographical location and higher declivity. Higher values were obtained for the plantings located on the northern surface for the variables LAI, volume and mean annual wood increase, with this tendency being repeated in the 3PG model simulations.

Continuous Monitoring, Modeling, and Evaluation of Actual Building Energy Systems

2014 ◽  
Author(s):  
Maxim L. Sankey ◽  
Sheldon M. Jeter ◽  
Trevor D. Wolf ◽  
Donald P. Alexander ◽  
Gregory M. Spiro ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Continuous Monitoring ◽  
Energy System ◽  
Building Energy ◽  
Energy Performance ◽  
Weather Data ◽  
Practical Procedure ◽  
Heating And Cooling ◽  
Institute Of Technology

Residential and commercial buildings account for more than 40% of U.S. energy consumption, most of which is related to heating, ventilation and air conditioning (HVAC). Consequently, energy conservation is important to building owners and to the economy generally. In this paper we describe a process under development to continuously evaluate a building’s heating and cooling energy performance in near real-time with a procedure we call Continuous Monitoring, Modeling, and Evaluation (CMME). The concept of CMME is to model the expected operation of a building energy system with actual weather and internal load data and then compare modeled energy consumption with actual energy consumption. For this paper we modeled two buildings on the Georgia Institute of Technology campus. After creating our building models, internal lighting loads and equipment plug-loads were collected through electrical sub-metering, while the building occupancy load was recorded using doorway mounted people counters. We also collected on site weather and solar radiation data. All internal loads were input into the models and simulated with the actual weather data. We evaluated the building’s overall performance by comparing the modeled heating and cooling energy consumption with the building’s actual heating and cooling energy consumption. Our results demonstrated generally acceptable energy performance for both buildings; nevertheless, certain specific energy inefficiencies were discovered and corrective actions are being taken. This experience shows that CMME is a practical procedure for improving the performance of actual well performing buildings. With improved techniques, we believe the CMME procedure could be fully automated and notify building owners in real-time of sub-optimal building performance.

scholarly journals Whole building validation for simulation programs including synthetic users and heating systems: experimental design

2020 ◽  
Vol 172 ◽  
pp. 22003
Author(s):  
Matthias Kersken ◽  
Paul Strachan ◽  
Eirini Mantesi ◽  
Graeme Flett
Keyword(s):  
Experimental Design ◽  
Large Scale ◽  
Measurement Data ◽  
Internal Heat ◽  
Quality Measurement ◽  
Building Energy ◽  
Energy Performance ◽  
Weather Data ◽  
Air Source Heat Pump ◽  
Definition Of

A large-scale study for validating building energy simulation programs against measured data was undertaken within IEA EBC Annex 71 “Building energy performance assessment based on optimized in-situ measurements” as a more complex and realistic successor of the dataset created previously in IEA EBC Annex 58. The validation method consists of a set of high quality measurement data and a precise documentation of all boundary conditions. This enables a user to create a complete model of the different validation scenarios. The results of this model can be compared to the real measurement data. Because of the detailed modelling, the remaining deviations should indicate the limitations of the tool under investigation. The definition of the scenarios consists of extensive weather data and a detailed description of the building geometry, components compositions, thermal bridges, air tightness, ventilation, etc. In addition to the previous Annex 58 dataset this experiment contains synthetic users with internal heat and moisture gains, operated doors and windows and underfloor heating with an air source heat pump. This paper sets out the experimental design, a key element in ensuring a useful experimental dataset.

Near-extreme summer meteorological data set for sub-tropical climates

2016 ◽  
Vol 38 (2) ◽  
pp. 197-208 ◽  
Author(s):  
Kevin Ka-Lun Lau ◽  
Edward Yan-Yung Ng ◽  
Pak-Wai Chan ◽  
Justin Ching-Kwan Ho
Keyword(s):  
Meteorological Data ◽  
Energy Performance ◽  
Weather Data ◽  
Building Performance ◽  
Extreme Conditions ◽  
Night Time ◽  
Data Set ◽  
Performance Simulation ◽  
Building Performance Simulation ◽  
Tropical Climates

Building performance simulation requires representative weather data of specific locations. Test Reference Year (TRY) and Typical Meteorological Year (TMY) are common hourly dataset for typical year conditions. In sub-tropical climates, overheating is very common in buildings due to high temperature and intense solar radiation. However, there are no universal approaches to develop a dataset for estimating summer discomfort in naturally ventilated and free-running buildings. This article employs the concept of Summer Reference Years (SRY) in order to represent the near-extreme summer conditions in Hong Kong. The derived SRY is able to capture the near-extreme conditions in the multi-year series. The SRY was found to represent the high Tdry values reasonably well during daytime when such near-extreme conditions occur. On the contrary, according to the number of HN-DHs, the SRY does not satisfactorily represent high night-time Tdry. It is possible to incorporate the sorting of Tdry-min in the SRY adjustment in order to better reflect night-time situations in sub-tropical climate. Further studies are therefore required to confirm whether such modifications give more accurate results in the assessment of building energy performance. Nonetheless, the SRY dataset can be applied in building performance simulation and the assessment of indoor thermal comfort. Practical application: The present study found that there are deficiencies for the SRY to represent the high night-time Tdry, which affects the building performance assessment in sub-tropical climates. It suggests potential improvement to the existing adjustment of SRY for representing the near-extreme summer conditions in order to obtain more accurate results of building assessment.

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