Skip to main content
Book cover

Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks

  • Book
  • © 2020

Overview

  • Provides an exhaustive summary of the latest tendencies in demand side management
  • Presents examples of data analytics and text mining applied to power system studies
  • Offer in-depth analysis of smart metering requirements in support of distribution network operation

Part of the book series: Springer Theses (Springer Theses)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (5 chapters)

Keywords

About this book

This thesis deals with two important and very timely aspects of the future power system operation - assessment of demand flexibility and advanced demand side management (DSM) facilitating flexible and secure operation of the power network. It provides a clear and comprehensive literature review in these two areas and states precisely the original contributions of the research.

The book first demonstrates the benefits of data mining for a reliable assessment of demand flexibility and its composition even with very limited observability of the end-users. It then illustrates the importance of accurate load modelling for efficient application of DSM and considers different criteria in designing DSM programme to achieve several objectives of the network performance simultaneously. Finally, it demonstrates the importance of considering realistic assumptions when planning and estimating the success of DSM programs.

The findings presented here have both scientific and practical significance; they gained her BSc and MSc degrees in electrical engineering from the University of Belgrade in 2011 and 2012 respectively. She graduated with her PhD from the University of Manchester. She has presented at several conferences, and has won runner-up prizes in poster presentation at three. She has authored or co-authored more than 40 journal, conference and technical papers.provide a basis for further research, and can be used to guide future applications in industry.



Authors and Affiliations

  • Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK

    Jelena Ponoćko

About the author

Dr Jelena Ponocko received her BSc and MSc degrees in Electrical Engineering from the University of Belgrade, Serbia, in 2011 and 2012, respectively, and her PhD degree from The University of Manchester. She has authored or co-authored more than 40 research publications and technical reports, and has given presentations at international conferences and seminars around the world.

Bibliographic Information

  • Book Title: Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks

  • Authors: Jelena Ponoćko

  • Series Title: Springer Theses

  • DOI: https://doi.org/10.1007/978-3-030-39943-6

  • Publisher: Springer Cham

  • eBook Packages: Energy, Energy (R0)

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Hardcover ISBN: 978-3-030-39942-9Published: 28 January 2020

  • Softcover ISBN: 978-3-030-39945-0Published: 28 January 2021

  • eBook ISBN: 978-3-030-39943-6Published: 27 January 2020

  • Series ISSN: 2190-5053

  • Series E-ISSN: 2190-5061

  • Edition Number: 1

  • Number of Pages: XXVI, 198

  • Number of Illustrations: 14 b/w illustrations, 109 illustrations in colour

  • Topics: Energy Systems, Power Electronics, Electrical Machines and Networks, Data Engineering, Sustainability Management

Publish with us