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Modeling and Estimation of Solar Radiation through Artificial Neural Network using known Solar Data

  • Authors (legacy)
    Corresponding: Naeem Sadiq
    Co-authors: Atif Idrees, Naeem Sadiq, Mahwish Mobeen Khan, Ahmed Hassan, Zaheer Uddin
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  • gnest_04605_published.pdf
  • Paper ID
    gnest_04605
  • Paper status
    Published
  • Date paper submitted
  • Date paper accepted
  • Date paper online
DOI
https://doi.org/10.30955/gnj.004605
Graphical abstract
Abstract

The paper attempts to discover a city's global, direct beam, and diffused solar radiation with the help of known solar radiation of its neighbor(s). Two distinctive architecture have been used to find the solar radiation of a city. In the first architecture, we used single input and a single hidden layer of the neuron to find the solar radiation of the city. The solar radiation of Lahore, Multan, and Quetta was found via the solar radiation of Karachi. In the second architecture scheme, we used three inputs and ten neurons' hidden layers to find the solar radiation of a city in the region bounded by three cities lying at the vertices of a triangle. Multan was assumed as such an area; its neighboring cities, Lahore, Quetta, and Karachi, form a triangle, and Multan lies inside the triangle area. In both architectures, three types of solar radiation, DSR, BSR, and GSR, were found with an accuracy of 99.8 %. The coefficient of determination in each case was 0.99. It shows that the results obtained through ANN models agree well with the known values.

Keywords
Artificial Neural Network Global Radiation Diffused radiation Direct beam solar radiation
Cite this article
Naeem, S. et al. (2023) “Modeling and Estimation of Solar Radiation through Artificial Neural Network using known Solar Data”, Global NEST Journal, 25(8). Available at: https://doi.org/10.30955/gnj.004605.
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  • gnest_04605_published.pdf