?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Machine+learning+and+geographic+information%0D%0Asystems+for+large-scale+wind+energy+potential%0D%0Aestimation+in+rural+areas&rft.creator=Assouline%2C+Dan&rft.creator=Mohajeri%2C+Nahid&rft.creator=Mauree%2C+Dasaraden&rft.creator=Scartezzini%2C+Jean-Louis&rft.description=Clean%2C+safe%2C+affordable+and+available+in+the+long-term%2C+wind+is+one+of+the+most+promising+sources+of+renewable+energy.+Its+optimized+and+profitable+use%2C+however%2C+requires+an+estimation+of+the+potential+in+locations+of+interest%2C+given+its+very+volatile+behavior+in+various+settings.+In+the+present+study%2C+we+propose+a+methodology+using+a+combination+of+Machine+Learning+(Random+Forests)%2C+Geographic+Information+Systems+and+wind+parametric+models+to+estimate+the+large-scale+theoretical+wind+speed+potential+in+rural+areas+over+the+entire+Switzerland.+The+monthly+wind+speed+over+rural+areas+is+estimated+based+on+wind+speed+measurements+and+several+meteorological%2C+topographic%2C+and+wind-specific+features+available+accross+the+country.+Wind+speed+values+and+their+associated+uncertainty+are+computed+at+the+scale+of+200+x+200+%5Bm2%5D+pixels+covering+the+territory%2C+at+a+typical+height+for+rural+commercial+wind+turbine+installation%2C+that+is%2C+z%3D100m.+The+developed+methodology%2C+is%2C+however%2C+applicable+to+any+large+region%2C+given+the+availability+of+data+of+interest.+The+results+show+that+in+the+case+of+Switzerland%2C+wind+turbines+could+approximately+represent+an+non-negligible+installed+power+capacity+of%2C+for+each+pixel+and+for+each+turbine+installation%2C+on+average+80+kW+in+Swiss+rural+areas%2C+and+up+to+1600+kW+in+most+suitable+pixels.&rft.publisher=IOP+Publishing&rft.date=2019&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A++Journal+of+Physics%3A+Conference+Series.++(pp.+012036).++IOP+Publishing%3A+Bristol%2C+UK.+(2019)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10200260%2F1%2FAssouline_2019_J._Phys.__Conf._Ser._1343_012036.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10200260%2F&rft.rights=open