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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.
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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
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