Loại tài liệu:    Chỉ tìm trong: 
21-30 trong số 98 kết quả
A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2020
Bộ sưu tập: Metadata
ddc:  621.43
 
Demonstrate Mobility Energy Productivity Benefit of Intelligent Electric Vehicle Infrastructure Design Using Agent-Based...
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Office of the Assistant Secretary of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2019
Bộ sưu tập: Metadata
ddc:  623.8
 
Electricity rates for electric vehicle direct current fast charging in the United States [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Office of the Assistant Secretary of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2019
Bộ sưu tập: Metadata
ddc:  621.312
 
Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area reg...
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2019
Bộ sưu tập: Metadata
ddc:  629.223
 
A Machine-Learning Decision-Support Tool for Travel-Demand Modeling [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Office of the Assistant Secretary of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2019
Bộ sưu tập: Metadata
ddc:  629.2
 
A Deep Learning Approach for Transportation Network Companies Trip-Demand Prediction Considering Spatial-Temporal Features [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Office of the Assistant Secretary of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2019
Bộ sưu tập: Metadata
ddc:  629.22
 
What is the Impact of Utility Demand Charges on a DCFC host [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2015
Bộ sưu tập: Metadata
ddc:  623.881
 
Demand-Response in Smart Buildings
Tác giả: Denia Kolokotsa, Kostas Gobakis, Kostas Gobakis, Denia Kolokotsa, Gloria Pignatta, Gloria Pignatta
Xuất bản: Basel, Switzerland: MDPI - Multidisciplinary Digital Publishing Institute , 2020
Bộ sưu tập: Tài liệu truy cập mở
eBook (pdf)
ddc: 
 
PV Charging and Storage for Electric Vehicles
Tác giả: Pavol Bauer, Pavol Bauer, Gautham Ram Chandra Mouli, Gautham Ram Chandra Mouli
Xuất bản: Basel, Switzerland: MDPI - Multidisciplinary Digital Publishing Institute , 2021
Bộ sưu tập: Tài liệu truy cập mở
eBook (pdf)
ddc: 
 
New Trends in Enhanced, Hybrid and Integrated Geothermal Systems
Tác giả: Jatin Nathwani, Alireza Dehghanisanij, Alireza Dehghanisanij, Jatin Nathwani
Xuất bản: Basel, Switzerland: MDPI - Multidisciplinary Digital Publishing Institute , 2021
Bộ sưu tập: Tài liệu truy cập mở
eBook (pdf)
ddc: 
 

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