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Energies2019,12, 57
Wecalculatedthe initial costs Jki(b, s,w) andtheoperationcosts J l
o(b, s,w) as follows:
Jki(b, s,w) =Ck·nk·CRFk (5)
Jlo(b, s,w) =Cl·nl (6)
inwhichCandnare thepriceperunit and the installedunits, respectively, for eachcomponent k.
CRF representedthecapital recoveryfactor thatwasdefinedas [32,33,39]:
CRF= ir(1+ ir)ny
(1+ ir)ny−1 (7)
where ir is the inflationrate,whichwassetas1.26%inthispaperbyreferringto theaverageannual
changeofconsumerpriceindexofTaiwan[39],andny is theexpectedlifeof thecomponents. Theprice
andexpected lifeof thecomponentsare illustrated inTable4wereusedtocalculate thesystemcosts in
the followingexamples.
Table4.Component lifeandprice [32,33,39].
Component Life (year) Price ($)
Hybridsystem 15 N/A
Windturbine (3kW) 15 9666
PVarrays (1kW) 15 1833
Powerelectronicdevices (6kW) 15 1666
ChemicalH2generation 15 10,666
NaBH4 (60g) N/A 0.33
Electrolyzer (2.5kW–500L/h) N/A 10,666
PEMFC(3kW) N/A 6000
Battery (48V–100Ah) N/A 866
(2) Systemreliability: thereliabilityof thehybridsystemwasdefinedas the lossofpowersupply
(LPSP)as follows[32,33,39]:
LPSP= ∫ LPS(t)dt∫
P(t)dt (8)
inwhichLPS(t)was theshortage (lost)ofpowersupplyat time t,whileP(t)was thepowerdemandof
the loadprofileat time t. Therefore, ∫
LPS(t)dt indicatedthe insufficientenergysupplyand ∫
P(t)dt
represented the total energydemand for the entire simulation. If the power supplymet the load
demandatall times, (i.e.,LPS(t)=0,∀t), thenthesystemwascompletelyreliablewithLPSP=0.
(3) Systemsafety: systemsafetywasdefinedas theguaranteed sustainableperiodof thehybrid
powersystemunderextremeweatherconditionswhennosolarorwindenergywasavailable.
Suppose theenergystored in thesystemwasEstoreandtheaveragedailyenergyconsumption
wasEday; then, thesystemsafetycanbedefinedas follows:
Safety= Estore
Eday (9)
For example, averagedaily energydemand is 19.96, 30.41, and22.32kWh for thehousehold,
laboratory, and office, respectively (see Table 3). Therefore, if the energy stored in the battery
and hydrogen is 60 kWh, the system safety is 3.01, 1.97, and 2.69 days for the laboratory, office,
andhousehold, respectively.Whenconsideringtheefficiencyof thebatteryandinverterbothas90%,
thenthesystemsafety is2.70,1.78,and2.42days, respectively.
89
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