Impact of Solar Model Selection on Building Energy Analysis for Kuwait

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
Adnan Al-Anzi ◽  
Donghyun Seo ◽  
Moncef Krarti
Keyword(s):  
Model Selection ◽  
Solar Radiation ◽  
Energy Analysis ◽  
Simulation Analysis ◽  
Building Energy ◽  
Weather Data ◽  
Solar Model ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
The Impact

This paper summarizes the results of a comparative analysis for four models utilized to predict solar radiation in Kuwait City, Kuwait. The four models include the Kasten model, Zhang and Huang model, Muneer model, and neural network based model. The analysis was based on hourly measured solar data for Kuwait City. The measured hourly solar radiation data are obtained for the year 1994 and include global, direct, and diffuse solar radiations. Nonsolar weather data for the same year and site are obtained from the US National Climatic Data Center (NCDC). Weather files suitable for building energy simulation are developed using measuered data as well as predictions from the four solar models. A series of simulation analysis to determine the impact of solar model selection for the weather file on the energy uses predictions from a whole-building simulation program using office buildings in Kuwait. The results of the validation analysis and the simulation evaluation indicate that Zhang and Huang model is suitable for the predicting hourly solar radiation suitable for energy analysis of buildings in Kuwait.

Impact of Solar Model Selection on Building Energy Analysis for Kuwait

Solar Energy ◽  
2006 ◽  
Author(s):  
Adnan Al-Anzi ◽  
Donghyun Seo ◽  
Moncef Krarti
Keyword(s):  
Model Selection ◽  
Solar Radiation ◽  
Energy Analysis ◽  
Simulation Analysis ◽  
Building Energy ◽  
Weather Data ◽  
Solar Model ◽  
Climatic Data ◽  
Diffuse Solar Radiation ◽  
The Impact

This paper summarizes the results of a comparative analysis for four models utilized to predict solar radiation in Kuwait City, Kuwait. The four models include the Kasten model, Zhang and Huang model, Muneer model, and neural network based model. The analysis was based on hourly measured solar data for Kuwait City. The measured hourly solar radiation data are obtained for the year 1994 and include global, direct, and diffuse solar radiation. Non-solar weather data for the same year and site are obtained from the US National Climatic Data Center (NCDC). Weather files suitable for building energy simulation are developed using measured data as well as predictions from the four solar models. A series of simulation analysis to determine the impact of solar model selection for the weather file on the energy use predictions from a whole-building simulation program using office buildings in Kuwait. The results of the validation analysis and the simulation evalaution indicate that Zhang and Huang model is suitable for the predicting hourly solar radiation suitable for energy analysis of buildings in Kuwait.

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 Proposal to Refine Solar Radiation of Typical Meteorological Year Database and Evaluation on the Influence of Air-Conditioning Load

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 524
Author(s):  
Jihui Yuan ◽  
Kazuo Emura ◽  
Craig Farnham
Keyword(s):  
Solar Radiation ◽  
Air Conditioning ◽  
Energy Savings ◽  
Energy Resource ◽  
Global Solar Radiation ◽  
Resource Assessment ◽  
Weather Data ◽  
Diffuse Solar Radiation ◽  
Chinese Standard ◽  
The Impact

The Typical meteorological year (TMY) database is often used to calculate air-conditioning loads, and it directly affects the building energy savings design. Among four kinds of TMY databases in China—including Chinese Typical Year Weather (CTYW), International Weather for Energy Calculations (IWEC), Solar Wind Energy Resource Assessment (SWERA) and Chinese Standard Weather Data (CSWD)—only CSWD is measures solar radiation, and it is most used in China. However, the solar radiation of CSWD is a measured daily value, and its hourly value is separated by models. It is found that the cloud ratio (diffuse solar radiation divided by global solar radiation) of CSWD is not realistic in months of May, June and July while compared to the other sets of TMY databases. In order to obtain a more accurate cloud ratio of CSWD for air-conditioning load calculation, this study aims to propose a method of refining the cloud ratio of CSWD in Shanghai, China, using observed solar radiation and the Perez model which is a separation model of high accuracy. In addition, the impact of cloud ratio on air-conditioning load has also been discussed in this paper. It is shown that the cloud ratio can yield a significant impact on the air conditioning load.

scholarly journals The Regional Snowfall Index

2014 ◽  
Vol 95 (12) ◽  
pp. 1835-1848 ◽  
Author(s):  
Michael F. Squires ◽  
Jay H. Lawrimore ◽  
Richard R. Heim ◽  
David A. Robinson ◽  
Mathieu R. Gerbush ◽  
...  
Keyword(s):  
United States ◽  
Data Center ◽  
Historical Perspective ◽  
The United States ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Impact Scale ◽  
Population Information ◽  
Regional Index ◽  
The Impact

This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.

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.

scholarly journals The criterion of the presumption of biophysiological temperature and the cooling guide for the determination of human comfort in the City of Rutba

2018 ◽  
Vol 227 (2) ◽  
pp. 307-316
Author(s):  
Lect. Intisar Sukkar Khioun
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Climatic Data ◽  
Human Comfort ◽  
Air Movement ◽  
The Impact ◽  
The Relationship ◽  
The City ◽  
Climate Studies

     The relationship between man and climate is of great importance in climate studies, as climate is the most natural climatic element in the sense of comfort or distress of man, and humans can live comfortably if the degree of heat between (17-31 m) and the human feeling of heat and cold and then rest or discomfort not only caused by the air temperature but depends on many elements including solar radiation, air movement, relative humidity, the level of human activity and the type of clothing worn, and the presumption has used Biophysiological temperature and Cooling guide in this study to demonstrate the impact of climate on human comfort in the city of Rutba and relying on the climatic data for thirty years.

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 Impact Assessment of Climate Change on Paddy Yield: A Case Study of Nepal Agriculture Research Council (NARC), Tarahara, Nepal

1970 ◽  
Vol 8 (3) ◽  
pp. 147-167 ◽  
Author(s):  
Yam K Rai ◽  
Bhakta B Ale ◽  
Jawed Alam
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Research Council ◽  
Crop Yields ◽  
Rice Yield ◽  
Weather Data ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Impact

Climate change and global warming are burning issues, which significantly threat agriculture and global food security. Change in solar radiation, temperature and precipitation will influence the change in crop yields and hence economy of agriculture. It is possible to understand the phenomenon of climate change on crop production and to develop adaptation strategies for sustainability in food production, using a suitable crop simulation model. CERES-Rice model of DSSAT v4.0 was used to simulate the rice yield of the region under climate change scenarios using the historical weather data at Nepal Agriculture Research Council (NARC) Tarahara (1989-2008). The Crop Model was calibrated using the experimental crop data, climate data and soil data for two years (2000-2001) and was validated by using the data of the year 2002 at NARC Tarahara. In this study various scenarios were undertaken to analyze the rice yield. The change in values of weather parameters due to climate change and its effects on the rice yield were studied. It was observed that increase in maximum temperature up to 2°C and 1°C in minimum temperature have positive impact on rice yield but beyond that temperature it was observed negative impact in both cases of paddy production in ambient temperature. Similarly, it was observed that increased in mean temperature, have negative impacts on rice yield. The impact of solar radiation in rice yield was observed positive during the time of study period. Adjustments were made in the fertilizer rate, plant density per square meter, planting date and application of water rate to investigate suitable agronomic options for adaptation under the future climate change scenarios. Highest yield was obtained when the water application was increased up to 3 mm depth and nitrogen application rate was 140 kg/ha respectively. DOI: http://dx.doi.org/10.3126/jie.v8i3.5941 JIE 2011; 8(3): 147-167

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