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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 1948 productionof1L/min[24]. Theelectrolyzerhas fouroperationmodes:warmup,production, standby, andshutdown.WedevelopedahydrogenelectrolysismodelusingtheMatlab/SimPowerSystemTM andappliedthe followingmanagementstrategies (seeFigure4b): 1. Warmup:Theextra-renewableenergy is regardedasredundantenergywhenthebatterySOCis greater thananupper limitof95%. 2. Production: The electrolyzer is switched on after 10 min, when the integrated redundant renewableenergy ∫10 0 (Prenew−Pload)dt increases. Prenew andPload represent thepowersources fromtherenewableenergyandpowerconsumptionof the loads, respectively. 3. Standby:Theelectrolyzerisswitchedoffwhenthehydrogentankisfull(reachesthehigh-pressurelimit). 4. Shutdown:Thehydrogenelectrolyzer isswitchedoffwhenthebatterySOCfalls to the lower limitof85%. Toavoidfrequentswitching, theelectrolyzer isallowedtoproducehydrogenwhenthebattery SOCisbetween85%and95%. (a) System layout. (b) Management strategy. 3UHVVXUH+ ġ 0DVV+ ġ $& 3RZHUġ +\GURJHQ VWRUDJH +\GURJHQ SURGXFWLRQ : +\GURJHQġ (OHFWULFLW\ġ ,JHQHUDWRUġ Figure4.Thehydrogenelectrolyzationsystem. A3Lhydrogencylinderwasusedtoconducttheelectrolyzationexperiments.Theresultsareshownin Figure5,wheretheinitialandfinalpressuresofthecylinderare8.6barand10bar,respectively.Asacheck 199
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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
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Short-Term Load Forecasting by Artificial Intelligent Technologies