scholarly journals A Typical Meteorological Year Generation Based on NASA Satellite Imagery (GEOS-I) for Sokoto, Nigeria

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Olayinka S. Ohunakin ◽  
Muyiwa S. Adaramola ◽  
Olanrewaju M. Oyewola ◽  
Richard L. Fagbenle ◽  
Fidelis I. Abam
Keyword(s):  
Energy Systems ◽  
Building Energy ◽  
Global Solar Radiation ◽  
Dew Point ◽  
Weather Data ◽  
Maximum Temperature ◽  
Building Energy Simulation ◽  
Dew Point Temperature ◽  
Northwest Region

Computer simulation of buildings and solar energy systems are being used increasingly in energy assessments and design. This paper evaluates the typical meteorological year (TMY) for Sokoto, northwest region, Nigeria, using 23-year hourly weather data including global solar radiation, dew point temperature, mean temperature, maximum temperature, minimum temperature, relative humidity, and wind speed. Filkenstein-Schafer statistical method was utilized for the creation of a TMY for the site. The persistence of mean dry bulb temperature and daily global horizontal radiation on the five candidate months were evaluated. TMY predictions were compared with the 23-year long-term average values and are found to have close agreement and can be used in building energy simulation for comparative energy efficiency study.

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.

scholarly journals A Modified Method to Generate Typical Meteorological Years from the Long-Term Weather Database

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Haixiang Zang ◽  
Qingshan Xu ◽  
Pengwei Du ◽  
Katsuhiro Ichiyanagi
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Atmospheric Pressure ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Weather Data ◽  
Radiation Data ◽  
Modified Method

A modified typical meteorological year (TMY) method is proposed for generating TMY from practical measured weather data. A total of eleven weather indices and novel assigned weighting factors are applied in the processing of forming the TMY database. TMYs of 35 cities in China are generated based on the latest and accurate measured weather data (dry bulb temperature, relative humidity, wind velocity, atmospheric pressure, and daily global solar radiation) in the period of 1994–2010. The TMY data and typical solar radiation data are also investigated and analyzed in this paper, which are important in the utilizations of solar energy systems.

Review of empirical solar radiation models for estimating global solar radiation of various climate zones of China

2019 ◽  
Vol 44 (2) ◽  
pp. 168-188
Author(s):  
Shaban G Gouda ◽  
Zakia Hussein ◽  
Shuai Luo ◽  
Qiaoxia Yuan
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Computational Cost ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Dew Point ◽  
Machine Learning Techniques ◽  
Accurate Information ◽  
Input Parameters

Utilizing solar energy requires accurate information about global solar radiation (GSR), which is critical for designers and manufacturers of solar energy systems and equipment. This study aims to examine the literature gaps by evaluating recent predictive models and categorizing them into various groups depending on the input parameters, and comprehensively collect the methods for classifying China into solar zones. The selected groups of models include those that use sunshine duration, temperature, dew-point temperature, precipitation, fog, cloud cover, day of the year, and different meteorological parameters (complex models). 220 empirical models are analyzed for estimating the GSR on a horizontal surface in China. Additionally, the most accurate models from the literature are summarized for 115 locations in China and are distributed into the above categories with the corresponding solar zone; the ideal models from each category and each solar zone are identified. Comments on two important temperature-based models that are presented in this work can help the researchers and readers to be unconfused when reading the literature of these models and cite them in a correct method in future studies. Machine learning techniques exhibit performance GSR estimation better than empirical models; however, the computational cost and complexity should be considered at choosing and applying these techniques. The models and model categories in this study, according to the key input parameters at the corresponding location and solar zone, are helpful to researchers as well as to designers and engineers of solar energy systems and equipment.

scholarly journals Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4115 ◽  
Author(s):  
Vincenzo Costanzo ◽  
Gianpiero Evola ◽  
Marco Infantone ◽  
Luigi Marletta
Keyword(s):  
Residential Building ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Weather Station ◽  
Simulation Tools ◽  
The Difference ◽  
Energy Simulations

Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.

Weather Forecasting Using Artificial Neural Network and Bayesian Network

2014 ◽  
Vol 18 (5) ◽  
pp. 812-817 ◽  
Author(s):  
Klent Gomez Abistado ◽  
◽  
Catherine N. Arellano ◽  
Elmer A. Maravillas ◽  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bayesian Network ◽  
Weather Forecasting ◽  
Weather Conditions ◽  
Dew Point ◽  
Weather Data ◽  
Maximum Temperature ◽  
Prevailing Wind Direction ◽  
Artificial Neural

This paper presents a scheme of weather forecasting using artificial neural network (ANN) and Bayesian network. The study focuses on the data representing central Cebu weather conditions. The parameters used in this study are as follows: mean dew point, minimum temperature, maximum temperature, mean temperature, mean relative humidity, rainfall, average wind speed, prevailing wind direction, and mean cloudiness. The weather data were collected from the PAG-ASA Mactan-Cebu Station located at latitude: 10°19´, longitude: 123°59´ starting from January 2011 to December 2011 and the values available represent daily averages. These data were used for training the multi-layered backpropagation ANN in predicting the weather conditions of the succeeding days. Some outputs from the ANN, such as the humidity, temperature, and amount of rainfall, are fed to the Bayesian network for statistical analysis to forecast the probability of rain. Experiments show that the system achieved 93%–100% accuracy in forecasting weather conditions.

scholarly journals Study of Affecting Factors of Meteorological Parameters on Solar Radiation on Pokhara

2020 ◽  
pp. 45-52
Author(s):  
Prakash M. Shrestha ◽  
Jeevan Regmi ◽  
Usha Joshi ◽  
Khem N. Poudyal ◽  
Narayan P. Chapagain ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Negative Correlation ◽  
Meteorological Parameters ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Maximum Temperature ◽  
Affecting Factors ◽  
Clearness Index ◽  
Annual Average ◽  
Radiation Data

Solar radiation data are of great significance for solar energy systems. This study aimed to estimate monthly and seasonal average of daily global solar radiation on a horizontal surface in Pokhara (Lat.:28.21o N, Long.: 84o E and alt. 827 m above sea level), Nepal, by using CMP6 pyranometer in 2015. As a result of this measurement, monthly and yearly mean solar radiation values were 20.37 ±5.62 MJ/m2/ day in May, 11.37 ± 2.38 MJ/m2/ day in December and 16.82 ±5.24 MJ/m2/ day respectively. Annual average of clearness index and extinction coefficient are 0.51±0.14 and 0.53±0.31 respectively. There is positive correlation of maximum temperature and negative correlation of with global solar radiation.

scholarly journals Combat climate change challenges in considering climatic vulnerabilities and risk factors for wheat production

2017 ◽  
Vol 14 (2) ◽  
pp. 137-149
Author(s):  
MM Rahman ◽  
MG Miah ◽  
SR Saha
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Water Levels ◽  
Agricultural Drought ◽  
Maximum Temperature ◽  
Climatic Data ◽  
Wheat Production ◽  
Combat Climate Change ◽  
Northwest Region

The present study was undertaken for assessing the impacts of climate variability on wheat production as well as the field based suggestions opined by the wheat growers to combat the future challenges particularly climate variability during November 2014 to March 2015. The study was conducted at northwest region at Dinajpur sadar and Kaharul upazilas in Dinajpur of Bangladesh. One hundred sixty wheat farmers were selected by using previously pre-tested interview schedules adopting multistage proportionate systematic random sampling technique. Climatic variability was assessed by analysis of long term data of local meteorological station. Assessment of long term climatic data particularly for wheat growing season revealed that minimum temperature has been increased, while maximum temperature and rainfall were decreased. Farmer’s opinions on these aspects were almost similar. Farmers opined that both surface and ground water levels have been decreased, resulting agricultural drought. Farmer’s also opined regarding suitable technology to combat climate change impact on wheat production revealed the use of newly recommended varieties. Finally, the outcome of the results could help researchers as well as government and NGOs to take appropriate climate change adaptation policy thus facilitating farmers in sustaining their livelihoods against changing climate in the near future of Northwest region in Bangladesh.SAARC J. Agri., 14(2): 137-149 (2016)

Simulation of New Solar Heating System for Heating Biogas Digesters above Ground in Cold Regions

2013 ◽  
Vol 291-294 ◽  
pp. 89-95 ◽  
Author(s):  
A.A.M. Hassanein ◽  
Ling Qiu
Keyword(s):  
Solar Energy ◽  
Biogas Production ◽  
Heating System ◽  
Building Energy ◽  
Simulation Software ◽  
Solar Heating ◽  
Cold Weather ◽  
Weather Data ◽  
Building Energy Simulation ◽  
Energy Plus

The biogas amounts with stable flowing rate require heating in cold weather. This study focuses on using solar energy for heating biogas digester. In this research we used energy plus building energy simulation software and real weather data for simulation the heating of biogas digester with 8760 hours simulation .The research was carried out in two parts: The first one is one biogas digester above ground without heating. The Second part of this study is a simulation of one biogas digester with solar heating by using a new design based on double plastic cover. It has shown that the use of solar energy can achieve the optimum temperature for biogas production process almost the year time. Using double plastic cover is the most suitable method with economic form for heating biogas digester above ground.

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