GIS-AIDED GEOGRAPHICAL AND METEOROLOGICAL DATA OVERVIEW OF SOLAR RADIATION MAPPING FOR MALAYSIA – AN EXPLANATORY STUDY BASED ON SOLAR RADIATION PREDICTION MODELING USING NEURAL NETWORK APPROACH

Authors

  • Mohd Rizman Sultan Mohd Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Shah Alam, 40450, Shah Alam, Malaysia https://orcid.org/0000-0001-8054-8313
  • Fazlina Ahmat Ruslan Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Shah Alam, 40450, Shah Alam, Malaysia
  • Juliana Johari Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Shah Alam, 40450, Shah Alam, Malaysia

DOI:

https://doi.org/10.11113/jurnalteknologi.v83.16634

Keywords:

GIS, Spatial, Solar Radiation, Prediction Modeling, Neural Network

Abstract

Solar radiation mapping has used geographical and meteorological data. To obtain geographical and meteorological data, a Geographic Information System (GIS) is required. GIS is defined as an integrated geographic resource that presents data in terms of spatial information. This data is important for Neural Networks as it will be used as input parameters for the development of solar radiation prediction models. Solar radiation prediction is one way to map the sun's rays in certain places where there are insufficient resources or space to build a complete solar radiation measurement station. Since predictions about solar radiation require meteorological and geographical data, this paper will give an overview of GIS-assisted geographical and meteorological data to be used as input parameters for solar radiation mapping which will eventually be used as input for prediction models developed for the whole country of Malaysia using Neural Networks. Based on the results, the prediction model developed managed to obtain a coefficient of determination, R2 value of 0.9329.

Downloads

Published

2021-09-21

Issue

Section

Science and Engineering

How to Cite

GIS-AIDED GEOGRAPHICAL AND METEOROLOGICAL DATA OVERVIEW OF SOLAR RADIATION MAPPING FOR MALAYSIA – AN EXPLANATORY STUDY BASED ON SOLAR RADIATION PREDICTION MODELING USING NEURAL NETWORK APPROACH. (2021). Jurnal Teknologi (Sciences & Engineering), 83(6), 19-33. https://doi.org/10.11113/jurnalteknologi.v83.16634