Solar Radiation Estimation Using Data Mining Techniques for Remote Areas—A Case Study in Ethiopia

Bizuayehu Abebe Worke, Hans Bludszuweit and José A. Domínguez-Navarro
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Bizuayehu Abebe Worke: Electrical Engineering Department, EINA, University of Zaragoza, 50018 Zaragoza, Spain
Hans Bludszuweit: CIRCE Foundation, 50018 Zaragoza, Spain
José A. Domínguez-Navarro: Electrical Engineering Department, EINA, University of Zaragoza, 50018 Zaragoza, Spain

Energies, 2020, vol. 13, issue 21, 1-15

Abstract: High quality of solar radiation data is essential for solar resource assessment. For remote areas this is a challenge, as often only satellite data with low spatial resolution are available. This paper presents an interpolation method based on topographic data in digital elevation model format to improve the resolution of solar radiation maps. The refinement is performed with a data mining method based on first-order Sugeno type Adaptive Neuro-Fuzzy Inference System. The training set contains topographic characteristics such as terrain aspect, slope and elevation which may influence the solar radiation distribution. An efficient sampling method is proposed to obtain representative training sets from digital elevation model data. The proposed geographic information system based approach makes this method reproducible and adaptable for any region. A case study is presented on the remote Amhara region in North Shewa, Ethiopia. Results are shown for interpolation of solar radiation data from 10 km × 10 km to a resolution of 1 km × 1 km and are validated with data from the PVGIS and SWERA projects.

Keywords: solar radiation modeling; GIS; interpolation; digital elevation model; data mining; ANFIS (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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