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

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

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

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

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

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

by Jelena Ponocko

Hardcover(1st ed. 2020)

$109.99 
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Overview

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.


Product Details

ISBN-13: 9783030399429
Publisher: Springer International Publishing
Publication date: 01/29/2020
Series: Springer Theses
Edition description: 1st ed. 2020
Pages: 198
Product dimensions: 6.10(w) x 9.25(h) x (d)

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.

Table of Contents

Introduction.- The Need for and Application of Data Analytics in Distribution System Studies.- Advanced Demand Profiling.- Multi-objective Demand Side Management at Distribution Network Level.- Conclusions and Further Work

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