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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 1948 2.5.OptimizationofFourHybridPowerModels Basedonthegeneralhybridpowermodel, as showninFigure1,weconsidered the following fourhybridpowersystemswithdifferentcombinationsofenergysourcesandstorage: 1. Solar_Wind(SW)system:Thesystemcontains twoenergysources (asolarpanelandWT)and oneenergystoragemethod(Li-Febattery). 2. Solar_Wind_PEM_HE(SWPH)system:Thesystemcontains threeenergysources (asolarpanel, WT,andPEMFC)andtwoenergystoragemethods (aLi-Febatteryandahydrogenelectrolyzer). 3. Solar_Wind_PEM_CHG(SWPC)system:Thesystemcontains threeenergysources (asolarpanel, WT,andPEMFC)withachemicalhydrogengeneratorandoneenergystoragemethods (anLi-Fe battery). 4. Solar_Wind_PEM_HE_CHG(SWPHC)system:Thesystemcontains threeenergysources (asolar panel,WT,andPEMFC)withachemicalhydrogengeneratorandtwoenergystoragemethods (anLi-Febatteryandahydrogenelectrolyzer). ThecorrespondingSimPowerSystemmodelsare illustrated inFigure8. 6:3+&ġ6:3 6:ġ 39 DUUD\Vġ +\GURJHQ HOHFWURO\]HUġ /L32 %DWWHU\ġ /RDGġ +\GURJHQġ (OHFWULFLW\ġ :LQG WXUELQHġ :LQG FRQWUROOHUġ +\GURJH Q VWRUDJHġ )XHO FHOOġ &KHPLFDO K\GURJHQ JHQHUDWRUġ '& '& &RQYHUWHUġ '& $& ,QYHUWHUġ 6:3 Figure8.Thefourhybridpowermodels. Threestandard loadconditions,asshowninFigure7a,wereappliedto the fourhybridpower models to predict systems responses. Then, we used Equations (5)–(11) to evaluate system cost andreliabilityusingdifferentcomponentsizes. TheresultingreferenceplotsareshowninFigure9, where thenumberofWTswasset tozero,becauseusingaWTtendedto increase thesystemcosts. Theoptimalsystemcostsof the fourhybridpowersystemsare illustrated inTable3. 204
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Short-Term Load Forecasting by Artificial Intelligent Technologies
Titel
Short-Term Load Forecasting by Artificial Intelligent Technologies
Autoren
Wei-Chiang Hong
Ming-Wei Li
Guo-Feng Fan
Herausgeber
MDPI
Ort
Basel
Datum
2019
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-03897-583-0
Abmessungen
17.0 x 24.4 cm
Seiten
448
Schlagwörter
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Kategorie
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Short-Term Load Forecasting by Artificial Intelligent Technologies