Neural Network for Estimating Daily Global Solar Radiation Using Temperature, Humidity and Pressure as Unique Climatic Input Variables

  title={Neural Network for Estimating Daily Global Solar Radiation Using Temperature, Humidity and Pressure as Unique Climatic Input Variables},
  author={Victor A. Jimenez and Amelia Barrionuevo and Adrian Will and Sebastian Rodriguez},
  journal={Smart Grid and Renewable Energy},
Solar radiation is one of the most important parameters for applications, development and research related to renewable energy. However, solar radiation measurements are not a simple task for several reasons. In the cases where data are not available, it is very common the use of computational models to estimate the missing data, which are based mainly on the search for relationships between weather variables, such as temperature, humidity, precipitation, cloudiness, sunshine hours, etc. But… 

Figures and Tables from this paper

Assessing Neural Network Approaches for Solar Radiation Estimates Using Limited Climatic Data in the Mediterranean Sea
One of the most crucial variables in Agricultural Meteorology is Solar Radiation (Rs), although it is measured in a very limited number of weather stations due to its high cost in both installation
Modelling Hourly Global Horizontal Irradiance from Satellite-Derived Datasets and Climate Variables as New Inputs with Artificial Neural Networks
More accurate data of hourly Global Horizontal Irradiance (GHI) are required in the field of solar energy in areas with limited ground measurements. The aim of the research was to obtain more precise
Short-term forecasting for solar irradiation based on the multi-layer neural network with the Levenberg-Marquardt algorithm and meteorological data: application to the Gandon site in Senegal
This paper proposes a short-term forecast of the solar irradiation on the Gandon site in Senegal, based on the multi-layer artificial neural networks, with the Levenberg-Marquardt algorithm. The
Variation in Direct Solar Trradiation with Relative Humidity and Atmospheric Temperature
A class first Pyranometer was used to measure the direct solar irradiation and the obtained results were analyzed. Separate sensors were used to measure the relative humidity and the atmospheric
Building Soft Sensors using Artificial Intelligence: Use Case on Daily Solar Radiation
Both approaches for building soft sensors are compared and combined in order to utilize the best of both worlds and show the best performance on the artificial neural network.
Today the problem of prediction of short-term electricity consumption or Short Term Load Forecasting (STLF), is a matter of capital importance for energy companies, since it allows more efficient
Evaluation of Optimal Occasional Tilt on Photovoltaic Power Plant Energy Efficiency and Land Use Requirements, Iran
The paper studies the optimum panel horizontal orientation angle toward the Sun and the optimum time interval of the panel’s movement. The optimum time intervals or panel movement can change the rate
MeteoMex: open infrastructure for networked environmental monitoring and agriculture 4.0
The use of low-end Wemos D1 mini boards to connect environmental sensors to the open-source platform ThingsBoard and a prototype for monitoring wastewater treatment is shown, which exemplifies the capabilities of the Wemos board for signal processing.


Hourly Solar Radiation Estimation Using Ambient Temperature and Relative Humidity Data
This paper presents hourly solar radiation estimation methods using ambient temperature and relative humidity data. The methods are based on the decomposition model that is calculating each of solar
Estimating global solar radiation from common meteorological data in Aranjuez, Spain
This study aimed to calibrate existing models and develop a new model for estimating global solar radiation data using commonly and available measured meteorological records such as precipitation or
Empirical models for estimating global solar radiation: A review and case study
Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina
The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation,