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Utilizing Machine Learning to Evaluate the Impact of Policy Shift for Scheduling Mechanism of IPPs to Mitigate Power and Economic Deficit /

TextPublisher: USPCAS-E, NUST, Islamabad : 2019Subject(s): MS-EEP Thesis MS ThesisDDC classification: 621.3 Summary: TH-168

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Item type	Current location	Home library	Call number	Status	Date due	Barcode	Item holds
Thesis	US-Pakistan Center for Advanced Studies in Energy (USPCAS-E)	US-Pakistan Center for Advanced Studies in Energy (USPCAS-E)	621.3 BIL (Browse shelf)	Available		CAS-ETH0000168

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Previous	621.3 BEE Performance Evaluation of Optimal DG Placement Using MCDA in Smart Distribution Networks /	621.3 ,BEG Extra high voltage ac transmission engineering/	621.3 BEH Spectrum Splitting of Solar Radiation for Efficient Conversion via Photovoltaics /	621.3 BIL Utilizing Machine Learning to Evaluate the Impact of Policy Shift for Scheduling Mechanism of IPPs to Mitigate Power and Economic Deficit /	621.3 BUS Fabrication & characterization of an effective electron transport layer for perovskite solar cells /	621.3 DAA Cu@Co NCNTs Cathode Catalyst derived from ZIF-67 for ORR in PEMFC /	621.3 DAN Tariff setting for independent hydro power producers in perspective of Pakistan's electric power market /	Next

TH-168

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