Version 1
: Received: 6 December 2018 / Approved: 7 December 2018 / Online: 7 December 2018 (03:55:55 CET)
How to cite:
Gillani, S.M.A. Solar Power Interpolation and Analysis Using Spatial Autocorrelation. Preprints2018, 2018120091. https://doi.org/10.20944/preprints201812.0091.v1
Gillani, S.M.A. Solar Power Interpolation and Analysis Using Spatial Autocorrelation. Preprints 2018, 2018120091. https://doi.org/10.20944/preprints201812.0091.v1
Gillani, S.M.A. Solar Power Interpolation and Analysis Using Spatial Autocorrelation. Preprints2018, 2018120091. https://doi.org/10.20944/preprints201812.0091.v1
APA Style
Gillani, S.M.A. (2018). Solar Power Interpolation and Analysis Using Spatial Autocorrelation. Preprints. https://doi.org/10.20944/preprints201812.0091.v1
Chicago/Turabian Style
Gillani, S.M.A. 2018 "Solar Power Interpolation and Analysis Using Spatial Autocorrelation" Preprints. https://doi.org/10.20944/preprints201812.0091.v1
Abstract
To reduce solar power production invariance, it is critical to study varying patterns of power production in the concerned region. Analyzing the patterns of past power production trends can help simulate power production scenarios for future. The current study area is around Amsterdam, located in Netherlands. PVoutput.org website is used to mine 6 months of solar power production data for 120 stations around Amsterdam city. FME Workbench software is used to actively fetch the data from the mentioned website and manage in a MySQL database. Solar attenuation maps created using ArcGIS, helped to graphically visualize the variations in solar power production at different times and locations. Further, spatial autocorrelation is checked between the stations using semi-variograms in geostatistical tool of ArcMap. This feature allows to check whether the stations located close to each other are more correlated to each other rather than stations which are far apart. The statistical data analysis of power production can aid solar power production companies to better interpolate and predict solar power in advance for the concerned study region.
Keywords
solar power interpolation; solar power attenuation; spatial autocorrelation; semi-variograms; geosatistics
Subject
Engineering, Energy and Fuel Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
