28 June 2015 to 3 July 2015
Africa/Johannesburg timezone
SAIP2015 Proceeding published on 17 July 2016

A comparative study of the three empirical solar models in North West, South Africa.

1 Jul 2015, 16:10
1h 50m
Board: G.380
Poster Presentation Track G - Theoretical and Computational Physics Poster2

Speaker

Ms Sophie Mulaudzi (University of Venda)

Please indicate whether<br>this abstract may be<br>published online<br>(Yes / No)

Yes

Would you like to <br> submit a short paper <br> for the Conference <br> Proceedings (Yes / No)?

No

Abstract content <br> &nbsp; (Max 300 words)<br><a href="http://events.saip.org.za/getFile.py/access?resId=0&materialId=0&confId=34" target="_blank">Formatting &<br>Special chars</a>

Energy crisis in South Africa (SA) is causing a lot of problems for every one and it has a negative impact on the growth of our economy. There is a dire need to implement the 2020 strategies to harness renewable energy and evidently it needs the knowledge of the amount of solar energy falling in different areas of SA. With this knowledge the renewable energy systems can be meaningfully developed so as to sustain the outdoor conditions. The use of pyrheliometers, pyranometers, etc., to measure direct, global, etc., also plays an important role. However they cannot be installed in many areas due to lack of funds, the alternative method is to estimate these irradiances. It is of a vital importance that a model to be selected should give a reasonable estimate. This paper gives a comparative study of three modified empirical solar radiation models (Angstrom; Hargreaves & Samani and Glower & McCulloch) on a horizontal surface from sunshine hours and temperatures of different stations in North West (-〖25.8080〗^°;〖25.5430〗^°). A five year meteorological data from the four ARC stations were used to estimate the global solar radiation for this region. The estimated monthly solar irradiance data was compared with observed data using the statistical parameters such as, the mean bias error (MBE); Mean percentage error (MPE) and root mean square (RMSE). The Angstrom and temperature based models give better estimations for North West province.

Main supervisor (name and email)<br>and his / her institution

Prof. V.Sankaran, vaith.sankaran.ac.za; University of venda

Apply to be<br> considered for a student <br> &nbsp; award (Yes / No)?

YES

Level for award<br>&nbsp;(Hons, MSc, <br> &nbsp; PhD, N/A)?

PhD

Primary author

Ms Sophie Mulaudzi (University of Venda)

Co-authors

Dr Eric Maluta (University of Venda) Mr Fulufhelo Nemangwele (University of Venda)

Presentation Materials

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