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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 1948 an improvement insystemcostsaftersizeadjustment.ChenandWang[10] includedirradiationand winddatainahybridsystemmodeltooptimizesystemcostsandreliability. Thepresentpaperwillalso utilizehistoricweatherdataandloadconditionswhenanalyzingthe impactsof systemconfigurations. Thepaperisarrangedasfollows: Section2introducesageneralhybridpowersystemthatconsists of solar cells,WTs, a fuel cell, hydrogenelectrolysis, chemical hydrogengeneration, andbatteries. Weextendaprevioushybridpowermodel [4]byaddingWTandhydrogenelectrozationmodules. Then, systemcostandreliability functionsaredefinedtoevaluatesystemperformance. Basedonthis generalhybridpowermodel,weapply threestandard loadconditions (laboratory,office,andhouse) to fourspecifiedhybridpowersystemstoestimate the impactofsystemconfigurationonperformance. Section3discusses theoptimizationof the fourhybridpowermodelsandshowsthatbothsystemcost andreliabilitycanbe improvedbytuningthesystemcomponentsizes. Basedontheresults, thesolar batterysystemispreferablebecauseofhighhydrogencostsatpresent.Wealsopredict the system costsatwhichhydrogenenergycouldbecomefeasible. Last, conclusionsaredrawninSection4. 2.Results This section builds a general hybrid powermodel that consists of a PV array, aWT, a PEMFC, hydrogenelectrolysis,chemicalhydrogengeneration,andbatteries.WeappliedaMatlab/SimPowerSystem (r2014a,MathWorks, Inc.,Natick,MA,USA)model topredict theperformanceof fourdifferenthybrid powersystemsunderthreetypical loads. Furthermore,costandreliability indexesweredefinedtoquantify performancemeasuresofthehybridsystems. 2.1.HybridPowerSystems Figure1ashowsageneralhybridpowersystem,whichconsistsofa3kWPEMFC,achemical hydrogenproduction systemwith sodiumborohydride (NaBH4), a 410Whydrogen electrolyzer, 1.32kWPVarrays,a0.2kWWT,a15AhLi-Febatteryset, andpowerelectronicdevices. Thesystem specifications are illustrated inTable 1 [19–25]. The systemhas three energy sources (solar,wind, andaPEMFC)andtwoenergystoragemethods (batteryandhydrogenelectrolysis). Regarding energy sources, solar power is connected directly to a DC bus. Wind power is transferredbya controller andconnects to theDCbus. Asboth solarpower andwindpowerare significantly influencedbytheweather,aPEMFCisusedtoprovidereliableenergywhennecessary. ThePEMFCcantransformhydrogenenergytoelectricityandcanprovidecontinuouspoweras long as thehydrogensupply is sufficient. Twohydrogensupplymethodsare considered: the chemical reactionofNaBH4andhydrogenelectrolysis. Theformercanprovidepowerwithhigh-energydensity using anauto-batching systemdevelopedpreviously [25,26]; the latter canbe regardedas energy storage,becauseredundantrenewableenergycanbestored in the formofhydrogen[24]. For energy storage, a Li-Fe battery is used for short-termelectricity storage [17] because the batteryhashighefficiency(about90%),andcanabsorbpowersurgeswhenthe loadchangesrapidly. Hydrogenelectrolysis is used for long-termstorage, considering the self-dischargingproblemsof batteries. Abenefit of the electrolysis process is that it doesnotproduce contaminants. However, theenergyconversionefficiency ismuchlower thanof thebattery [16]. WedevelopedthegeneralhybridpowermodelusingtheMatlab/SimPowerSystem,asshownin Figure1b,andanalyzedthe impactsofdifferentenergysourcesandstoragemethodsonthesystem. Inaprevious study [4], a SimPowerSystemmodelwasbuilt to includeaPEMFC,anLi-Febattery set, PV arrays, and a chemical hydrogen production system. Themodel parameterswere tuned basedonexperimentaldata toenable thesimulationmodel topredict theresponses/behaviorof the experimental systemundervarious conditions. Currently, PEMFC,PVarrays, chemicalhydrogen production,andbatterysetsareoperatedas follows[4,17,25,26]: 1. The PEMFC is switched on to provide a default current of 20 A with the highest energy efficiency[20]whenthebatterystate-of-charge (SOC) is30%. If theSOCcontinuouslydecreases to25%, thePEMFCcurrentoutput is increasedbyupto50A,accordingto load,until theSOCis 194
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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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