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

  • Jelena Ponoćko
Book
  • 196 Downloads

Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Jelena Ponoćko
    Pages 1-41
  3. Jelena Ponoćko
    Pages 99-143
  4. Jelena Ponoćko
    Pages 183-189
  5. Back Matter
    Pages 191-198

About this book

Introduction

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.


Keywords

Demand Side Management Distribution Network Smart Metering Demand Response Load Modelling Load Disaggregation Load Flexibility Sustainable Power Networks Data Analytics Data Mining

Authors and affiliations

  • Jelena Ponoćko
    • 1
  1. 1.Department of Electrical and Electronic EngineeringThe University of ManchesterManchesterUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-39943-6
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Energy
  • Print ISBN 978-3-030-39942-9
  • Online ISBN 978-3-030-39943-6
  • Series Print ISSN 2190-5053
  • Series Online ISSN 2190-5061
  • Buy this book on publisher's site
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