scholarly journals A GIS Open Source Software application for mapping solar energy resources in urban areas

2019 ◽  
Vol 116 ◽  
pp. 00060
Author(s):  
Małgorzata Pietras-Szewczyk
Keyword(s):  
Spatial Distribution ◽  
Solar Radiation ◽  
Solar Energy ◽  
Open Source ◽  
Urban Areas ◽  
Meteorological Data ◽  
Energy Resources ◽  
Geographical Information ◽  
Software Module ◽  
The Real

This paper presents the development of an open source geographical information system (GIS) software module for mapping solar energy resources for urban areas. The main goal of this work is to demonstrate the potential use of the r.sun module, a component of GRASS software, in calculating real solar radiation for urban areas. Modelling of the spatial distribution of solar radiation is one of the program functions. The r.sun module is dedicated for that purpose; however, it can only generate the spatial distribution of potential solar radiation. To get the real solar radiation maps it is advisable to use meteorological data, that describe diminution of solar radiation caused by cloud cover. In order to facilitate the generation of maps a GRASS source code modification was made. As a result, the r.sun module used in this work generates the real spatial distribution of solar radiation. The results are shown to be comparable with solar radiation satellite data obtained from the HelioClim project.

Artificial Intelligence Techniques for Solar Energy and Photovoltaic Applications

2013 ◽  
pp. 376-436 ◽  
Author(s):  
Radian Belu
Keyword(s):  
Artificial Intelligence ◽  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Energy Systems ◽  
Poor Quality ◽  
Quality Of Data ◽  
Information Patterns ◽  
Time Requirements

Artificial intelligence (AI) techniques play an important role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms employed to model, control, or to predict performances of the energy systems are complicated involving differential equations, large computer power, and time requirements. Instead of complex rules and mathematical routines, AI techniques are able to learn the key information patterns within a multidimensional information domain. Design, control, and operation of solar energy systems require long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer of a number of shortcomings (e.g. poor quality of data, insufficient long series, etc.). To overcome these problems AI techniques appear to be one of the strongest candidates. The chapter provides an overview of commonly used AI methodologies in solar energy, with a special emphasis on neural networks, fuzzy logic, and genetic algorithms. Selected AI applications to solar energy are outlined in this chapter. In particular, methods using the AI approach for the following applications are discussed: prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.

scholarly journals Solar Energy Potential in Turkey

2005 ◽  
Vol 23 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Havva Balat
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Geographical Location ◽  
Clean Energy ◽  
Energy Resources ◽  
Solar Thermal ◽  
Energy Potential ◽  
Yearly Average ◽  
Solar Thermal Applications

In this study, the solar energy potential of Turkey was investigated. Among the alternative clean energy resources in Turkey, the most important one is solar energy. Turkey's solar energy potential has been estimated to be 26.4 million toe as thermal and 8.8 million toe as electricity. Generally, solar energy is used for heating and the consumption of solar energy has increased from 5 ktoe in 1986 to 335 ktoe in 2003. Turkey's geographical location is highly favourable for utilization of solar energy. The yearly average solar radiation is 3.6 kWh/(m2 day) and the total yearly insulation period is approximately 2460 hours, which is sufficient to provide adequate energy for solar thermal applications.

scholarly journals SPATIAL DISTRIBUTION OF PULMONARY TUBERCULOSIS IN URBAN AREAS: A CASE FROM BELÉM, BRAZIL

2016 ◽  
Vol 7 (2) ◽  
pp. 1
Author(s):  
Marco Aurélio Arbage LOBO ◽  
Hermógenes De Carvalho PAIVA NETO ◽  
Leonardo Augusto Lobato BELLO
Keyword(s):  
Spatial Distribution ◽  
Pulmonary Tuberculosis ◽  
Low Income ◽  
Urban Areas ◽  
Geographical Information ◽  
Least Squares Regression ◽  
Census Tracts ◽  
Infected People ◽  
Low Income Families ◽  
Socioeconomic Data

<p>The precise location of areas with high incidence of pulmonary tuberculosis (TB) is important to improve public health actions. Official data records of the addresses and neighborhoods where the infected people live allow the mapping of the disease on this spatial scale. However, great socioeconomic diversity often exists inside neighborhoods, wherein high- and low-income families reside. This situation hampers the location of those areas that require close attention. Objective: This study aimed to estimate the risk of pulmonary TB infections in census tracts in Belém City (Brazil) from data on neighborhoods. Methods: A partial least-squares regression model was constructed in the scale of neighborhoods based on the record of addresses of TB-infected people and socioeconomic data from official sources. The model was then slightly modified and used to estimate the risk of TB prevalence in urban census tracts. The results were mapped using a geographical information system. Results: The percentages of explained variance of the set of independent variables and dependent variable were 86.4% and 30.2%, respectively. These values indicated that the model was acceptable for its purpose. Conclusion: The model’s results were consistent with the spatial distribution of socioeconomic and environmental characteristics of Belém City.</p>

scholarly journals An Advanced Simple Method for Generating Synthetic Average Instant Hourly Solar Energy

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
CAN COSKUN
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Open Source ◽  
Energy Parameter ◽  
Global Solar Radiation ◽  
Simple Method ◽  
Open Source Data ◽  
Time In Literature ◽  
Irradiance Data ◽  
First Time

The main objective of this study is to generate accurate synthetic hourly solar radiation data by using an easily accessible open source data. In this regard, a new approach is proposed for estimation of synthetic hourly global solar radiation during the day by utilizing only annual solar energy data. First time in literature, a model has been developed for prediction hourly and daily solar radiation based on annual solar energy parameter in this study. Parameters of the model were generated and tested for Turkey and one of them was presented as a case study within this paper. Long term measured hourly horizontal solar irradiance data from a network of Turkish meteorological stations was used to calibrate the model function. The predictions are compared with the solar data available in literature for Turkey. The advanced simple new model is utilized in open source computer program and has the potential to be adapted to other countries. 

scholarly journals Global solar radiation modeling using different machine learning and empirical models in Northeast China

2021 ◽  
Author(s):  
Yue Jia ◽  
Yongjun Su ◽  
Fengchun Wang ◽  
Pengcheng Li ◽  
Shuyi Huo
Keyword(s):  
Machine Learning ◽  
Solar Radiation ◽  
Solar Energy ◽  
Northeast China ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Learning Models ◽  
Machine Learning Models

Abstract Reliable global solar radiation (Rs) information is crucial for the design and management of solar energy systems for agricultural and industrial production. However, Rs measurements are unavailable in many regions of the world, which impedes the development and application of solar energy. To accurately estimate Rs, this study developed a novel machine learning model, called a Gaussian exponential model (GEM), for daily global Rs estimation. The GEM was compared with four other machine learning models and two empirical models to assess its applicability using daily meteorological data from 1997–2016 from four stations in Northeast China. The results showed that the GEM with complete inputs had the best performance. Machine learning models provided better estimates than empirical models when trained by the same input data. Sunshine duration was the most effective factor determining the accuracy of the machine learning models. Overall, the GEM with complete inputs had the highest accuracy and is recommended for modeling daily Rs in Northeast China.

scholarly journals Assessing the Impact of Builtup Areas on Development of Urban Heat Island in Lahore, Pakistan

2020 ◽  
Vol 10 (4) ◽  
pp. 64-68
Author(s):  
Safdar Ali Shirazi ◽  
Khadija Shakrullah ◽  
Saadia Sultan Wahla ◽  
Mareena Khurshid
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Urban Forest ◽  
Meteorological Data ◽  
Geographical Information ◽  
Heat Island ◽  
Landsat 7 ◽  
Urban Heat ◽  
The Impact

The aim of present study is to evaluate and assess the impact of built-up areas on development of the urbanheat island (UHI).The study mainly focused on Lahore, which is one of the mega cities of Pakistan. In terms ofpopulation size, Lahore is the second largest city of Pakistan with 11.13 million inhabitants. The geospatial techniques(Remote Sensing and Geographical Information System) along with statistical applications were applied to find out theLand Cover Land Uses changes and consequent development of builtup areas over the period of 2000 and 2015. Tostudy the UHI, the meteorological data of each 30 minutes for 36 days starting from 30th June 2015 to 4th August 2015were collected through direct on site observation by using digital weather station. The results of UHI were crosschecked by obtaining land surface temperature by using thermal infrared (TIR) band 6 of the Landsat-7 TM. The resultsshow that the LCLU and built environment have direct impact on development of UHI. The areas where there wasmore vegetation cover had less temperature while in urban areas, the temperature was measured higher. Over the periodof 36 days, the average UHI remained 5.5°C and the highest intensity of UHI was observed as 8.3°C thus augmentedresearch rationale. The study suggests establishment of a thick network of automatic weather stations in Lahore togauge the urban heat island intensity and to plant indigenous trees on vacant swaths and develop urban forest tomitigate city’s rising temperature.

scholarly journals Bioclimatic Analysis and Spatial Distribution of Livestock Fascioliasis in Iran

2019 ◽  
Author(s):  
Mohamad GHANIMATDAN ◽  
Abdolali CHALECHALE ◽  
Farid REZAEI ◽  
Mohamad Bagher ROKNI ◽  
Seyed Reza SHAHROKHI
Keyword(s):  
Information System ◽  
Spatial Distribution ◽  
Life Cycle ◽  
Intermediate Host ◽  
Geographical Information System ◽  
Meteorological Data ◽  
Geographical Information ◽  
Risk Map ◽  
Parasite Life Cycle ◽  
Gilan Province

Background: This study aimed to investigate the prevalence of fascioliasis and to perform a climatological analysis of different regions of Iran based on the current situation of the parasite and its intermediate host using Geographical Information System (GIS). Methods: Meteorological data were obtained from Iran Meteorological Organization. Risk map of fascioliasis transmission was prepared based on this data and using forecasting indices. Further, the number of fascioliasis cases from 31 provinces reported to the Iran Veterinary Organization were collected and prevalence maps of livestock fascioliasis were drawn. Results: The main risk hotspots were found in Northern provinces like Golestan, Mazandaran and Gilan as well as some Southern provinces such as Kohgiluyeh and Boyer-Ahmad and Chaharmahal and Bakhtiari and Fars, which have ideal conditions for completion of the parasite life cycle. Moreover, Gilan Province with 10.83% had the highest rate of fascioliasis infection in slaughtered animal. Conclusion: Iran is one of the most important foci of fascioliasis globally. Several provinces of Iran have appropriate conditions for evolution of parasite life cycle and presence of its intermediate host. These regions require special attention and serious determination in order to control fascioliasis in human and animals.

A solar energy resources assessment in Mozambique

2006 ◽  
Vol 17 (4) ◽  
pp. 76-85 ◽  
Author(s):  
B C Cuamba ◽  
M L Chenene ◽  
G Mahumane ◽  
D Z Quissico ◽  
J Lovseth ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Solar Radiation ◽  
Solar Energy ◽  
Energy Resources ◽  
Direct Solar Radiation ◽  
Small Scale ◽  
Renewable Energy Resources ◽  
Fuel Wood ◽  
Sustainable Rural Development ◽  
Starting Point

Just as with other Southern African Development Community (SADC) countries, Mozambique faces severe, interrelated problems of energy and environment linked, with massive consumption of fuel wood biomass. The conventional power grid provides less than 7% of the energy needs for the country’s 17 million inhabitants, and about 83% of the energy consumed in the country comes from biomass. Renewable energy resources can play an important role in the process of development of the country. From the vast renewable energy resources available in the country, solar energy represents one of those with the highest potential. Thus, the evaluation of the potential of solar energy systems in small-scale applications suitable for villages is a strategically good starting point for promotion of sustainable rural development. One of the major impediments in carrying out such studies is the fact that the exact behaviour of solar energy resources throughout the country has not been well studied. In this paper a general characterisation of the global, diffuse and direct solar radiation fields in Mozambique is presented. The study is based on experimental data measured by the National Institute of Meteorology (INAM) in the period 1970- 2000. For these analyses global, diffuse and direct solar radiation data from three stations along the coast line and three stations in the interior of the country have been used. The six stations were representative of the three main regions of the country, namely south, centre and north. Furthermore, sunshine hours data of one selected station was analysed.

scholarly journals Solar Radiation: Models and Measurement Techniques

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
C. K. Pandey ◽  
A. K. Katiyar
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Measurement Techniques ◽  
Research Work ◽  
Diffuse Radiation ◽  
Geometrical Parameters ◽  
Efficient Utilization ◽  
Energy Potential

In order to grasp the significance of the work accomplished by the author, it is necessary to keep abreast of the present developments in this field. The research work reported in the paper is an attempt to get knowledge to assess the solar energy potential for practical and efficient utilization in India. Our work is centered on estimating realistic values of solar (global and diffuse) radiation on horizontal and tilted surfaces using measured meteorological data and geographical and geometrical parameters for India.

Models for Determination of Solar Energy Potential

2008 ◽  
Vol 26 (5) ◽  
pp. 281-292 ◽  
Author(s):  
Kadir Bakirci
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Global Radiation ◽  
Statistical Error ◽  
Mean Bias Error ◽  
Bias Error ◽  
Energy Potential ◽  
Monthly Average ◽  
Correlation Models

Many solar energy systems require monthly average meteorological data as a basis for design. In the study, it was investigated whether existing solar radiation models are suitable to determine the values of solar radiation, and new empirical equations were developed which correlate the monthly average daily global radiation using sunshine hour data. The correlation models were compared by using statistical error tests such as mean bias error (MBE) and root mean square error (RMSE). The new correlation models demonstrate close agreement with the observed data. An application of this study was performed using the experimental data measured for Erzurum, Turkey.

Sign in / Sign up

Export Citation Format

Share Document