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Energies2018,11, 3442
Figure1.CategorywiseTECgrowth inIndia (1947–2018).
Thegraphical representationof theDomestic,Commercial, Industrial,AgriculturalandTraction
sectorsfortheperiod2000–2018hasbeenshowninFigure2. Thevaluefortheyear2018isanestimated
valuecomparedtoall theothervalues. The industrial sectorhasseenasteep increasesince thestartof
thecenturywhichusuallywillbe thecase foranycountry. Andall theother sectorshaveshowna
gradual increase. Theagricultureandthedomesticcategorieshaveshownsomefluctuationswhereas
theothersectorshaveshownasteadyincrease.
Figure2.SectorwiseEnergyConsumptionsince theCentury(2000–2018).
By the end of India’s 12th plan the split among all the sectors is shown above in Figure 3.
Thedomesticandtheagriculturewhichweregoinghandtohand, fewdecadesearlierwere found
to showavisible contrastofover6%between them. The industrial sector’s consumptionover the
yearshasdecreasedconsiderablyeventhoughithappenedtobe thevital consumerofall thesectors.
Andthesametrendisexpectedtocontinueover theyearswhichmight transformIndia frombeingan
Agriculturebasedeconomy.
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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
- Kategorie
- Informatik