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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 3433 it the inputgateofLSTM gt the inputnodeofLSTM ot theoutputgateofLSTM ht theoutputvalueofLSTM RMSE rootmeansquarederror MAE meanabsoluteerror MAPE meanabsolutepercenterror VMF variationalmodefunction EMF empiricalmodefunction References 1. Ekonomou,L.;Christodoulou,C.A.;Mladenov,V.Ashort-term load forecastingmethodusingartificial neuralnetworksandwaveletanalysis. Int. J.PowerSyst. 2016,1, 64–68. 2. Mirowski, P.; Chen, S.; Ho, T.K.; Yu, C.-N.Demand forecasting in smart grids. Bell Syst. Tech. J. 2014, 18, 135–158. [CrossRef] 3. Zhang,X.Short-termloadforecastingforelectricbuschargingstationsbasedonfuzzyclusteringandleast squaressupportvectormachineoptimizedbywolfpackalgorithm.Energies2018,11, 1449. [CrossRef] 4. Fiot, J.-B.;Dinuzzo,F.Electricitydemandforecastingbymulti-task learning. IEEETrans. SmartGrid2018, 9, 544–551. [CrossRef] 5. Dahl,M.;Brun,A.;Kirsebom,O.;Andresen,G. Improvingshort-termheat loadforecastswithcalendarand holidaydata.Energies2018,11, 1678. [CrossRef] 6. Teeraratkul,T.;O’Neill,D.;Lall, S.Shape-basedapproachtohouseholdelectric loadcurveclusteringand prediction. IEEETrans. SmartGrid2018,9, 5196–5206. [CrossRef] 7. Wang,Y.;Zhang,N.;Chen,Q.;Kirschen,D.S.;Li,P.;Xia,Q.Data-drivenprobabilisticnet loadforecasting withhighpenetrationofbehind-the-meterpv. IEEETrans. PowerSyst. 2018,33, 3255–3264. [CrossRef] 8. Haben,S.; Singleton,C.;Grindrod,P.Analysisandclusteringof residential customersenergybehavioral demandusingsmartmeterdata. IEEETrans. SmartGrid2016,7, 136–144. [CrossRef] 9. Stephen,B.;Tang,X.;Harvey,P.R.;Galloway,S.; Jennett,K.I. Incorporatingpractice theory insub-profile models for short termaggregatedresidential load forecasting. IEEETrans. SmartGrid2017,8, 1591–1598. [CrossRef] 10. Hayes,B.P.;Gruber, J.K.;Prodanovic,M.Multi-nodal short-termenergyforecastingusingsmartmeterdata. IETGener. Transm.Dis. 2018,12, 2988–2994. [CrossRef] 11. Xie, J.;Chen,Y.;Hong,T.;Laing,T.D.Relativehumidity for loadforecastingmodels. IEEETrans. SmartGrid 2018,9, 191–198. [CrossRef] 12. Xie, J.;Hong,T.Temperaturescenariogenerationforprobabilistic loadforecasting. IEEETrans. SmartGrid 2018,9, 1680–1687. [CrossRef] 13. Li,P.;Zhang, J.;Li,C.;Zhou,B.;Zhang,Y.;Zhu,M.;Li,N.Dynamicsimilarsub-seriesselectionmethodfor timeseries forecasting. IEEEAccess2018,6, 32532–32542. [CrossRef] 14. Lin,L.;Xue,L.;Hu,Z.;Huang,N.Modularpredictor forday-aheadloadforecastingandfeatureselection fordifferenthours.Energies2018,11, 1899. [CrossRef] 15. Xie, J.;Hong,T.Variableselectionmethods forprobabilistic loadforecasting: Empiricalevidence fromseven statesof theunitedstates. IEEETrans. SmartGrid2018,9, 6039–6046. [CrossRef] 16. Li, B.; Zhang, J.; He, Y.;Wang,Y. Short-term load-forecastingmethodbasedonwavelet decomposition withsecond-ordergrayneuralnetworkmodelcombinedwithadf test. IEEEAccess2017,5, 16324–16331. [CrossRef] 17. Rafiei,M.;Niknam,T.;Aghaei, J.; Shafie-khah,M.;Catalão, J.P.S.Probabilistic load forecastingusingan improvedwaveletneuralnetworktrainedbygeneralizedextremelearningmachine. IEEETrans. SmartGrid 2018,9, 6961–6971. [CrossRef] 18. Auder,B.;Cugliari, J.;Goude,Y.;Poggi, J.-M.Scalableclusteringof individualelectrical curves forprofiling andbottom-upforecasting.Energies2018,11, 1893. [CrossRef] 19. Qiu,X.;Ren,Y.; Suganthan,P.N.;Amaratunga,G.A.J.Empiricalmodedecompositionbasedensembledeep learningfor loaddemandtimeseries forecasting.Appl. SoftComput. 2017,54, 246–255. [CrossRef] 79
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Short-Term Load Forecasting by Artificial Intelligent Technologies
Title
Short-Term Load Forecasting by Artificial Intelligent Technologies
Authors
Wei-Chiang Hong
Ming-Wei Li
Guo-Feng Fan
Editor
MDPI
Location
Basel
Date
2019
Language
English
License
CC BY 4.0
ISBN
978-3-03897-583-0
Size
17.0 x 24.4 cm
Pages
448
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Category
Informatik
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Short-Term Load Forecasting by Artificial Intelligent Technologies