Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks (Springer Theses) - Softcover

Book 695 of 797: Springer Theses

Ponoćko, Jelena

 
9783030399450: Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks (Springer Theses)

Synopsis

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.


"synopsis" may belong to another edition of this title.

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.

From the Back Cover

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 practicalsignificance; 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.


"About this title" may belong to another edition of this title.

Other Popular Editions of the Same Title

9783030399429: Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks (Springer Theses)

Featured Edition

ISBN 10:  3030399427 ISBN 13:  9783030399429
Publisher: Springer, 2020
Hardcover