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Abstract

The research reported in 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. The thesis provides a very clear and comprehensive literature review in these two areas and states precisely the original contributions of the research. It 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, for the first time, different criteria in designing DSM programme to achieve several objectives of the network performance simultaneously, not only demand reduction as it is the current practice. Finally, it demonstrates the importance of considering realistic assumptions when planning and estimating the success of DSM programs, as these could have a strong impact on the network performance at both transmission and distribution level. The findings of the thesis have both scientific and practical significance, and can be further used as a guidance for application in industry. The thesis also represents an excellent basis for the continuation of research in the aforementioned areas. The research results presented in the thesis have been published in 2 leading international journal papers, 13 international conference papers and embeded in 21 technical reports. Finally, taking all the above into account, including excellent technical presentation of the thesis and a successful defence of the research by the student, the examiners agreed to award the thesis as written with no corrections needed.

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Ponoćko, J. (2020). The Need for and Application of Data Analytics in Distribution System Studies. In: Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-030-39943-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-39943-6_2

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