Application of Machine Learning and Deep Learning Methods to Power System Problems (Hardcover, 1st ed. 2021)


This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

R2,172
List Price R3,731
Save R1,559 42%

Or split into 4x interest-free payments of 25% on orders over R50
Learn more

Discovery Miles21720
Mobicred@R204pm x 12* Mobicred Info
Free Delivery
Delivery AdviceShips in 12 - 17 working days



Product Description

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

Customer Reviews

No reviews or ratings yet - be the first to create one!

Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Power Systems

Release date

October 2021

Availability

Expected to ship within 12 - 17 working days

First published

2021

Editors

, , , , ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

391

Edition

1st ed. 2021

ISBN-13

978-3-03-077695-4

Barcode

9783030776954

Categories

LSN

3-03-077695-6



Trending On Loot