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Photovoltaic (PV) system could be implemented to mitigate global warming and lack of energy. To maximize its effectiveness, the monthly average daily solar radiation (MADSR) should be accurately estimated, and then an accurate MADSR map could be developed for final decision-makers. However, there is a limitation in improving the accuracy of the MADSR map due to the lack of weather stations. This is because it is too expensive to measure the actual MADSR data using the remote sensors in all the sites where the PV system would be installed. Thus, this study aimed to develop the MADSR map with improved estimation accuracy using the advanced case-based reasoning (A-CBR), finite element method (FEM), and kriging method. This study was conducted in four steps: (i) data collectionMergeCell (ii) estimation of the MADSR data in the 54 unmeasured locations using the A-CBR modelMergeCell (iii) estimation of the MADSR data in the 89 unmeasured locations using the FEM modelMergeCell and (iv) development of the MADSR map using the kriging method. Compared to the previous MADSR map, the proposed MADSR map was determined to be improved in terms of its estimation accuracy and classification level.Department of Building Services Engineering2016-2017 > Academic research: refereed > Publication in refereed journalbcr

DEVELOPMENT OF THE MONTHLY AVERAGE DAILY SOLAR RADIATION MAP USING A-CBR, FEM, AND KRIGING METHOD