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Content Provider | IEEE Xplore Digital Library |
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Author | Chenxing Yang Qingshan Xu Xiaohui Xu Pingliang Zeng Xiaodong Yuan |
Copyright Year | 2014 |
Description | Author affiliation: Jiangsu Electr. Power Res. Inst., Nanjing, China (Xiaodong Yuan) || China Electr. Power Res. Inst., Beijing, China (Xiaohui Xu; Pingliang Zeng) || Sch. of Electr. Eng., Southeast Univ., Nanjing, China (Chenxing Yang; Qingshan Xu) |
Abstract | In order to obtain the solar radiation data (SRD), which are crucial for the photovoltaic power station planning, for the unmeasurable areas in China, both an inverse distance weighting (IDW) method and an artificial neural network (ANN) method are adopted to generate monthly global solar radiation (MGSR) data for the studied cities in this paper. For both methods, typical MGSR data for all the cities concerned are acquired by applying the typical meteorological year (TMY) method. The results show that the IDW method is only suitable for the case where the sampled cities and the studied city have relatively concentrated distribution and similar altitudes, while the ANN method performs well not only for the forementioned case but also for the case where the cities have comparatively dispersed distribution and different altitudes. |
Starting Page | 1 |
Ending Page | 5 |
File Size | 1858925 |
Page Count | 5 |
File Format | |
ISBN | 9781479964154 |
DOI | 10.1109/PESGM.2014.6939206 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-07-27 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Cities and towns Artificial neural networks Solar radiation Renewable energy sources Photovoltaic systems typical meteorological year (TMY) method artificial neural network (ANN) method inverse distance weighting (IDW) method monthly global solar radiation (MGSR) solar radiation data (SRD) estimation |
Content Type | Text |
Resource Type | Article |
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