| 书目名称 | Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of |
| 编辑 | Jelena Ponoćko |
| 视频video | |
| 概述 | 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 m |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | .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 prese |
| 出版日期 | Book 2020 |
| 关键词 | Demand Side Management; Distribution Network; Smart Metering; Demand Response; Load Modelling; Load Disag |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-39943-6 |
| isbn_softcover | 978-3-030-39945-0 |
| isbn_ebook | 978-3-030-39943-6Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer Nature Switzerland AG 2020 |
发表于 2025-3-21 17:09:39
