Pandey Amit Kumar Padmanaban Sanjeevikumar (22 results)

Condition: good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.

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Condition: New. 1st edition NO-PA16APR2015-KAP.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days. 453.

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Hardcover. Condition: new. Hardcover. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids. It further presents optimization-based computing techniques like fuzzy logic, and neural networks to enhance the computational speed.FeaturesDiscusses heuristic techniques and evolutionary algorithms in microgrids optimization problemsCovers operation management, distributed control approaches, and conventional control methods for microgridsPresents intelligent control for energy management and battery charging systemsHighlights a comprehensive treatment of power sharing in DC microgridsExplains control of low-voltage microgrids with master-slave architecture, where distributed energy resources interface with the grid by means of conventional current-driven invertersIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and environmental engineering. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New. In.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: new. Hardcover. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids. It further presents optimization-based computing techniques like fuzzy logic, and neural networks to enhance the computational speed.FeaturesDiscusses heuristic techniques and evolutionary algorithms in microgrids optimization problemsCovers operation management, distributed control approaches, and conventional control methods for microgridsPresents intelligent control for energy management and battery charging systemsHighlights a comprehensive treatment of power sharing in DC microgridsExplains control of low-voltage microgrids with master-slave architecture, where distributed energy resources interface with the grid by means of conventional current-driven invertersIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and environmental engineering. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condition: new. Hardcover. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids. It further presents optimization-based computing techniques like fuzzy logic, and neural networks to enhance the computational speed.FeaturesDiscusses heuristic techniques and evolutionary algorithms in microgrids optimization problemsCovers operation management, distributed control approaches, and conventional control methods for microgridsPresents intelligent control for energy management and battery charging systemsHighlights a comprehensive treatment of power sharing in DC microgridsExplains control of low-voltage microgrids with master-slave architecture, where distributed energy resources interface with the grid by means of conventional current-driven invertersIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and environmental engineering. The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: Brand New. 328 pages. 9.19x6.13x9.21 inches. In Stock.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids. It further presents optimization-based computing techniques like fuzzy logic, and neural networks to enhance the computational speed.FeaturesDiscusses heuristic techniques and evolutionary algorithms in microgrids optimization problemsCovers operation management, distributed control approaches, and conventional control methods for microgridsPresents intelligent control for energy management and battery charging systemsHighlights a comprehensive treatment of power sharing in DC microgridsExplains control of low-voltage microgrids with master-slave architecture, where distributed energy resources interface with the grid by means of conventional current-driven invertersIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and environmental engineering. 304 pp. Englisch.

Condition: New. PRINT ON DEMAND.

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Amit Kumar Pandey completed his PhD in microelectronics and VLSI from MNNIT Allahabad. He earned his MTech from NIT Allahabad and BE in Electronics Engineering from Swami Ramanand Teerth Marathwada University Nanded. He has been an assis.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book discusses principles of optimization techniques for microgrid applications specifically for microgrid system stability, smart charging, and storage units. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids. It further presents optimization-based computing techniques like fuzzy logic, and neural networks to enhance the computational speed.FeaturesDiscusses heuristic techniques and evolutionary algorithms in microgrids optimization problemsCovers operation management, distributed control approaches, and conventional control methods for microgridsPresents intelligent control for energy management and battery charging systemsHighlights a comprehensive treatment of power sharing in DC microgridsExplains control of low-voltage microgrids with master-slave architecture, where distributed energy resources interface with the grid by means of conventional current-driven invertersIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and environmental engineering.