Seite - 266 - in Short-Term Load Forecasting by Artificial Intelligent Technologies

Energies2018,11, 1678 5. Grosswindhager,S.;Voigt,A.;Kozek,M.OnlineShort-TermForecastofSystemHeatLoadinDistrictHeating Networks. InProceedingsof the31st InternationalSymposiumonforecasting,Prague,CzechRepublic, 26–29 June2011. 6. Nielsen,H.A.;Madsen,H.Modelling theheat consumption indistrictheatingsystemsusingagrey-box approach. EnergyBuild. 2006,38, 63–71, doi:10.1016/j.enbuild.2005.05.002. [CrossRef] 7. Idowu, S.; Saguna, S.; Åhlund,C.; Schelén,O. Forecastingheat load for smartdistrict heating systems: Amachine learningapproach. InProceedingsof the2014 IEEEInternationalConferenceonSmartGrid Communications (SmartGridComm),Venice, Italy,3–6November2014. 8. Izadyar,N.;Ghadamian,H.;Ong,H.C.;Moghadam,Z.; Tong,C.W.; Shamshirband, S. Appraisal of the supportvectormachine to forecast residentialheatingdemandfor theDistrictHeatingSystembasedon themonthlyoverallnaturalgasconsumption. Energy2015,93, 1558–1567, doi:10.1016/j.energy.2015.10.015. [CrossRef] 9. Kusiak,A.;Li,M.;Zhang,Z. Adata-drivenapproachforsteamloadprediction inbuildings. Appl. Energy 2010,87, 925–933, doi:10.1016/j.apenergy.2009.09.004. [CrossRef] 10. Powell,K.M.; Sriprasad,A.;Cole,W.J.; Edgar,T.F. Heating, cooling, andelectrical load forecasting fora large-scaledistrictenergysystem. Energy2014,74, 877–885, doi:10.1016/j.energy.2014.07.064. [CrossRef] 11. Kato,K.;Sakawa,M.; Ishimaru,K.;Ushiro,S.;Shibano,T.Heat loadpredictionthroughrecurrentneural network indistrictheatingandcoolingsystems. InProceedingsof the2008IEEEInternationalConference onSystems,ManandCybernetics,Singapore,15–16May2008;pp. 1401–1406. 12. Nielsen,T.S.;Madsen,H. ControlofSupplyTemperature inDistrictHeatingSystems. InProceedingsof the 8th InternationalSymposiumonDistrictHeatingandCooling,Trondheim,Norway,14–16August2002. 13. Hernández,L.;Baladrón,C.;Aguiar, J.M.;Calavia,L.;Carro,B.; Sánchez-Esguevillas,A.;García,P.;Lloret, J. Experimentalanalysisof the inputvariables’ relevance to forecastnextday’saggregatedelectricdemand usingneuralnetworks. Energies2013,6, 2927–2948. [CrossRef] 14. Saha, S.; Moorthi, S.; Pan, H.L.; Wu, X.; Wang, J.; Nadiga, S.; Tripp, P.; Kistler, R.; Woollen, J.; Behringer, D.; et al. TheNCEPClimate Forecast SystemReanalysis. Bull. Am. Meteorol. Soc. 2010, 91, 1015–1057, doi:10.1175/2010BAMS3001.1. [CrossRef] 15. Unden, P.; Rontu, L.; Järvinen, H.; Lynch, P.; Calvo, J.; Cats, G.; Cuxart, J.; Eerola, K.; Fortelius, C.; Garcia-Moya, J.A.; etal. HIRLAM-5ScientificDocumentation; TechnicalReport;SwedishMeteorologicaland Hydrological Institute:Norrkoping,Sweden,2002. 16. HolidaysinDenmark. Availableonline:www.timeanddate.com/holidays/denmark/(accessedon13June2017). 17. Crawley, D.B.; Hand, J.W.; Kummert,M.; Griffith, B.T. Contrasting the capabilities of building energy performancesimulationprograms. Build. Environ. 2008,43, 661–673, doi:10.1016/j.buildenv.2006.10.027. [CrossRef] 18. Dahl,M.; Brun,A.;Andresen,G.B. Decision rules for economic summer-shutdownofproductionunits in largedistrictheatingsystems. Appl. Energy2017,208C, 1128–1138, doi:10.1016/j.apenergy.2017.09.040. [CrossRef] 19. Alpaydin,E. Introduction toMachineLearning;MITPress:Cambridge,MA,USA,2014. 20. Bishop,C.M.PatternRecognitionandMachineLearning; Springer:NewYork,NY,USA,2006. 21. Hochreiter, S.; Schmidhuber, J. Longshort-termmemory. NeuralComput. 1997,9, 1735–1780. [CrossRef] [PubMed] 22. Drucker, H.; Burges, C.J.; Kaufman, L.; Smola, A.J.; Vapnik, V. Support vector regressionmachines. InAdvances inNeural InformationProcessingSystems;MITPress:Cambridge,MA,USA,1997;pp. 155–161. 23. Pedregosa,F.;Varoquaux,G.;Gramfort,A.;Michel,V.;Thirion,B.;Grisel,O.;Blondel,M.;Prettenhofer,P.; Weiss, R.; Dubourg, V.; et al. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 2011, 12, 2825–2830. 24. Dahl,M.;Brun,A.;Andresen,G.B. Usingensembleweatherpredictions indistrictheatingoperationand loadforecasting. Appl. Energy2017,193, 455–465, doi:10.1016/j.apenergy.2017.02.066. [CrossRef] 25. Scott,D.W.Onoptimalanddata-basedhistograms. Biometrika1979,66, 605–610. [CrossRef] c©2018bytheauthors. LicenseeMDPI,Basel,Switzerland. Thisarticle isanopenaccess articledistributedunder the termsandconditionsof theCreativeCommonsAttribution (CCBY) license (http://creativecommons.org/licenses/by/4.0/). 266