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Energies2018,11, 1948
(b) SimPowerSystem model. LOAD
WIND
SOLAR
HYDROGEN GENERATOR
CHEMICAL HYDROGEN GENERATOR
PEMFC
Figure1.Thegeneralhybridpowersystem.
Table1.Speciļ¬cationsof thehybridsystem[19ā25].
Component Type Speciļ¬cation
PEMFCModule M-FieldTMLPH8020 SeeReference [19]
SolarModule [20] ASEC-220G6S MaximumPower: 220W
OpenCircuitVoltage: 33.86V
ShortCircuitCurrent: 8.61A
WindTurbine [21] JPS-200 RatedPower: 200W
VoltageOutput:DC12V
RotorDiameter: 0.68m
LiFePO4Battery [22] NA NominalVoltage: 52.8V
NominalCapacity: 23Ah
DC/DCConverter [23] M-FieldTMS/N:00051 InputVoltage:DC44ā85V
OutputVoltage:DC42ā57V
MaximumPower: 3kW
DC/ACInverter [20] MWTMTS-3000-148 InputVoltage:DC42ā60V
OutputVoltage:AC110V
MaximumPower: 4.5kW
PEMElectrolyzer [24] HGL-1000U GasFlowRate: 1000mL/min
PowerConsumption: <430W
InputVoltage:AC100ā240V
ChemicalHydrogenGeneration
Module [25] NA InputVoltage:DC24VOutput:
SeeReference [25]
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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