Verwandte Artikel zu Physics-Aware Machine Learning for Integrated Energy...

Physics-Aware Machine Learning for Integrated Energy Systems Management (Advances in Intelligent Energy Systems) - Softcover

 
9780443329845: Physics-Aware Machine Learning for Integrated Energy Systems Management (Advances in Intelligent Energy Systems)

Inhaltsangabe

Physics-Aware Machine Learning for Integrated Energy Systems Management, a new release in the Advances in Intelligent Energy Systems series, guides the reader through this state-of-the-art approach to computational methods, from data input and training to application opportunities in integrated energy systems. The book begins by establishing the principles, design, and needs of integrated energy systems in the modern sustainable grid before moving into assessing aspects such as sustainability, energy storage, and physical-economic models. Detailed, step-by-step procedures for utilizing a variety of physics-aware machine learning models are provided, including reinforcement learning, feature learning, and neural networks. Supporting students, researchers, and industry engineers to make renewable-integrated grids a reality, this book is a holistic introduction to an exciting new approach in energy systems management.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorinnen und Autoren

Mohammadreza Daneshvar, PhD, is an Assistant Professor, founder and head of the Laboratory of Multi-Carrier Energy Networks Modernization at the Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. Prior to that, he was a postdoctoral research fellow in the field of modern multi-energy networks at the Smart Energy Systems Lab of the University of Tabriz for two years. He obtained his MSc and PhD degrees in Electrical Power Engineering from the University of Tabriz, all with honors. He has (co)authored more than 50 technical journal and conference articles, 10 books, 28 book chapters, and 10 national and international research projects in the field. Dr. Daneshvar is a member of the Editorial Board of the Energy and Built Environment Journal and the Early Career Editorial Board of the Sustainable Cities and Society Journal. He also served as the guest editor for the Sustainable Cities and Society, and Sustainable Energy Technologies and Assessments journals. Moreover, he serves as an active reviewer with more than 120 top journals, and was ranked among the top 1% of reviewers in Engineering and Cross-Field based on Publons global reviewer database. His research interests include Smart Grids, Transactive Energy, Energy Management, Renewable Energy Sources, Integrated Multi-Energy Systems, Grid Modernization, Electrical Energy Storage Systems, Sustainable Cities and Society, Microgrids, Energy Hubs, Machine Learning and Deep Learning, Digital Twin, and Optimization Techniques and AI.

Dr. Behnam Mohammadi-Ivatloo, PhD, is a Professor of sector coupling in energy systems at LUT University, Lappeenranta, Finland. He has a mix of high-level experience in research, teaching, administration and voluntary jobs at the national and international levels. He was PI or CO-PI in more than 20 externally funded research projects including grants from EU Horiozn and Business Finland. He is a Senior Member of IEEE since 2017 and a Member of the Governing Board of Iran Energy Association since 2013, where he was elected as President in 2019. He is Editor of IEEE Transactions on Power Systems and IEEE Transactions of Transportation Electrifications. His main areas of interest are integrated energy systems, sector coupling, renewable energies, energy storage systems, microgrids, and smart grids.



Dr. Kazem Zare, PhD, SMIEEE received the B.Sc. and M.Sc. degrees in electrical engineering from University of Tabriz, Tabriz, Iran, in 2000 and 2003, respectively, and Ph.D. degree from Tarbiat Modares University, Tehran, Iran, in 2009. Currently, he is a Professor of the Faculty of Electrical and Computer Engineering, University of Tabriz. His research areas include distribution networks operation and planning, power system economics, microgrid and energy management.



Jamshid Aghaei is currently a Full Professor with the School of Engineering and Technology at Central Queensland University, Australia. His research interests include smart grids, renewable energy systems, electricity markets, and power system operation, optimization, and planning. He was a Guest Editor of the Special Section on “Industrial and Commercial Demand Response” of the IEEE Transactions on Industrial Informatics, in November 2018, and the Special Issue on “Demand Side Management and Market Design for Renewable Energy Support and Integration” of the IET Renewable Power Generation, in April 2019. He is an Associate Editor of the IEEE Transactions on Smart Grid, IEEE Systems Journal, IEEE Transactions on Cloud Computing, IEEE Open Access Journal of Power and Energy, and IET Renewable Power Generation, and a Subject Editor of IET Generation Transmission and Distribution.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

EUR 5,50 für den Versand von Italien nach USA

Versandziele, Kosten & Dauer

Suchergebnisse für Physics-Aware Machine Learning for Integrated Energy...

Beispielbild für diese ISBN

Daneshvar, Mohammadreza
Verlag: Elsevier, 2025
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Softcover
Print-on-Demand

Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: new. Questo è un articolo print on demand. Bestandsnummer des Verkäufers IVNAF7KGKW

Verkäufer kontaktieren

Neu kaufen

EUR 153,91
Währung umrechnen
Versand: EUR 5,50
Von Italien nach USA
Versandziele, Kosten & Dauer

Anzahl: Mehr als 20 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Verlag: Elsevier, 2025
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Softcover

Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. Bestandsnummer des Verkäufers 410589019

Verkäufer kontaktieren

Neu kaufen

EUR 170,81
Währung umrechnen
Versand: EUR 7,44
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

Anzahl: 3 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Verlag: Elsevier, 2025
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Softcover

Anbieter: Books Puddle, New York, NY, USA

Verkäuferbewertung 4 von 5 Sternen 4 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. Bestandsnummer des Verkäufers 26403613828

Verkäufer kontaktieren

Neu kaufen

EUR 177,70
Währung umrechnen
Versand: EUR 3,42
Innerhalb der USA
Versandziele, Kosten & Dauer

Anzahl: 3 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Daneshvar, Mohammadreza (Editor)/ Mohammadi-ivatloo, Behnam (Editor)/ Zare, Kazem (Editor)/ Aghaei, Jamshid (Editor)
Verlag: Elsevier Science Ltd, 2025
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Paperback

Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Paperback. Zustand: Brand New. 300 pages. 9.00x6.00x9.02 inches. In Stock. Bestandsnummer des Verkäufers __0443329842

Verkäufer kontaktieren

Neu kaufen

EUR 168,64
Währung umrechnen
Versand: EUR 14,31
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

Anzahl: 2 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Verlag: Elsevier, 2025
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Softcover

Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. Bestandsnummer des Verkäufers 18403613838

Verkäufer kontaktieren

Neu kaufen

EUR 190,60
Währung umrechnen
Versand: EUR 9,95
Von Deutschland nach USA
Versandziele, Kosten & Dauer

Anzahl: 3 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Mohammadreza Daneshvar
ISBN 10: 0443329842 ISBN 13: 9780443329845
Neu Paperback

Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Paperback. Zustand: new. Paperback. Physics-Aware Machine Learning for Integrated Energy Systems Management, a new release in the Advances in Intelligent Energy Systems series, guides the reader through this state-of-the-art approach to computational methods, from data input and training to application opportunities in integrated energy systems. The book begins by establishing the principles, design, and needs of integrated energy systems in the modern sustainable grid before moving into assessing aspects such as sustainability, energy storage, and physical-economic models. Detailed, step-by-step procedures for utilizing a variety of physics-aware machine learning models are provided, including reinforcement learning, feature learning, and neural networks.Supporting students, researchers, and industry engineers to make renewable-integrated grids a reality, this book is a holistic introduction to an exciting new approach in energy systems management. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9780443329845

Verkäufer kontaktieren

Neu kaufen

EUR 166,86
Währung umrechnen
Versand: EUR 42,37
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb