典型文献
Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model
文献摘要：
This paper describes a novel approach in developing a model for forecasting of global insolation on a horizontal plane.In the proposed forecasting model,constraints,such as latitude and whole precipitable water content in vertical column of that location,are used.These parameters can be easily measurable with a global positioning system(GPS).The earlier model was developed by using the above datasets generated from different locations in India.The model has been verified by calculating theoretical global insolation for different sites covering east,west,north,south and the central region with the measured values from the same locations.The model has also been validated on a region,from which data was not used during the development of the model.In the model,clearness index coefficients(KT)are updated using the ensemble Kalman filter(EnKF)algorithm.The forecasting efficacies using the KT model and EnKF algorithm have also been verified by comparing two popular algorithms,namely the recursive least square(RLS)and Kalman filter(KF)algorithms.The minimum mean absolute percentage error(MAPE),mean square error(MSE)and correlation coefficient(R)value obtained in global solar insolation estimations using EnKF in one of the locations are 2.4％,0.0285 and 0.9866 respectively.
文献关键词：
中图分类号：
作者姓名：
Pravat Kumar Ray;Bidyadhar Subudhi;Ghanim Putrus;Mousa Marzband;Zunaib Ali
作者机构：
Department of Electrical Engineering,National Institute of Technology Rourkela,Rourkela-769008,India;School of Electrical Sciences,Indian Institute of Technology Goa,Goa 403401,India;Department of Maths,Physics and Electrical Engineering,Northumbria University,UK
文献出处：
引用格式：
[1]Pravat Kumar Ray;Bidyadhar Subudhi;Ghanim Putrus;Mousa Marzband;Zunaib Ali-.Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model)[J].中国电机工程学会电力与能源系统学报（英文版）,2022(04):1087-1096
A类：
Insolation,Clearness,clearness
B类：
Forecasting,Global,Solar,Using,Ensemble,Kalman,Filter,Based,Index,Model,This,paper,describes,novel,approach,developing,model,forecasting,global,insolation,horizontal,plane,proposed,constraints,such,latitude,whole,precipitable,water,content,vertical,column,that,used,These,parameters,can,easily,measurable,positioning,system,GPS,earlier,was,developed,by,using,above,datasets,generated,from,different,locations,India,has,been,verified,calculating,theoretical,sites,covering,west,north,south,central,region,measured,values,same,also,validated,which,not,during,development,coefficients,KT,updated,ensemble,filter,EnKF,efficacies,have,comparing,two,popular,algorithms,namely,recursive,least,square,RLS,minimum,mean,absolute,percentage,error,MAPE,MSE,correlation,obtained,solar,estimations,one,respectively
AB值：
0.575457
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