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Energies2018,11, 1449
loaddecreaseson rainyandsnowydaysonaccountof thedecelerationof e-buses,which leads to
adecrease in thedailydrivingmileageandcharging timesaswell as the reductionof total load in
thechargingstation. Tothisend, rainyandsnowydaysareanothervital factor thataffects the load
characteristicsofe-buschargingstations.
Figure4.Relationshipbetweenweatherconditionsanddaily load.
2.3. BusDispatching
Theschedulingofdeparture timeandoff-runningtimeisamomentous taskforbusoperation
companies. In lightof thedailyplanofbusdispatching,differentcharging intensitiesofe-buses in the
stationcausechanges in thedaily loadcurve in thechargingstationatdifferentperiods.Moreover,
diversedemandsof thepublic, traffic jams,andsuddensituationsrequire theadditionof temporary
e-buses toenhance transport capacity,whichbringsaboutchanges inbusschedulingondifferentdays.
Busdispatching isoneof thedirect reasons for thefluctuationofdaily loadcurveandthedistinction
of loadcurvesamongdays. According to thedispatchplanmade inadvance, the totalnumberof
e-buses thatneedtobechargedonapredicteddaycanbeestimated;namely, theaccumulatednumber
ofe-buseschargeddaily,which isusedasanindicator toreflect theeffectofbusdispatchingonthe
loadof thequick-changee-buschargingstation.
3.Methodology
3.1. FuzzyClustering
FC analysis is a mathematical technique that achieves classification of objects through the
establishmentof fuzzysimilarity relationsbasedontheir characteristics, familiarityandcomparability.
Thefuzzyequivalentmatrixdynamicclusteringmethodis implemented in thispaper.
Supposen samplesonthepredictedday, that isX=[x1,x2,...,xn]. Eachsamplexj comprisesm
indicators, expressedasxj= [
xj1,xj2,...,xjm ]T, j=1,2,...,n.
ThespecificstepsofFCcanbeexplainedas follows:
(1)Datastandardization.Consideringdifferentdimensionsandordersofmagnitude, thedata
mustbestandardizedasEquation(1) [27].
x′jk=(xjk−xkmin)/(xkmax−xkmin), (j=1, 2, ... ,n; k=1, 2, ...,m) (1)
where xjk is the raw data, xkmin and xkmax are theminimum andmaximum of x1k,x2k, · · · ,xnk,
respectively,x′jk is thestandardizeddata.
(2)Establishmentof fuzzysimilarity relationmatrix. Inorder tomeasure thecomparabilityof the
classifiedsamples, a fuzzysimilarity relationmatrixR= {
rij }
needs tobeconstructedbysimilarityof
323
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