Overview
- Tackles energy equipment management and monitoring challenges in Ukrainian power systems and smart grid technology
- Presents solutions include network modeling, renewable energy optimization, energy storage, and power plant improvements
- Covers research in forecasting, voltage control, microgrids, EV charging, enhancing reliability, and efficiency
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 512)
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Table of contents (16 chapters)
Keywords
About this book
This book covers new technologies and methods related to models for short-term forecasting of electricity imbalances in the IPS of Ukraine, taking into account the impact of forecasts of energy production from renewable sources on the accuracy of the imbalance forecast. The book proposed architecture and mathematical model of an artificial neural network for deep learning forecasting of short-term electricity imbalances using hourly data. Using a model to aggregate data with an hourly resolution followed by forecasting to reduce forecast error, the quasi-dynamic modeling method was used to analyze the impact of periodic generation on the network. The application of quasi-dynamic modeling also allows taking into account the system load curve, generation profile, storage system, as well as renewable energy sources (RES) operation in this area. The use of models makes it possible to achieve realistic estimates of generation for the required period. The book considers a local hybrid renewable energy system (HRES) based on different types of RES, which is more efficient than a system with one type of source.
Editors and Affiliations
Bibliographic Information
Book Title: Power Systems Research and Operation
Book Subtitle: Selected Problems III
Editors: Olexandr Kyrylenko, Serhii Denysiuk, Ryszard Strzelecki, Ihor Blinov, Ievgen Zaitsev, Artur Zaporozhets
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-031-44772-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-44771-6Published: 22 November 2023
Softcover ISBN: 978-3-031-44774-7Due: 23 December 2023
eBook ISBN: 978-3-031-44772-3Published: 21 November 2023
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XII, 371
Number of Illustrations: 58 b/w illustrations, 117 illustrations in colour
Topics: Energy Systems, Electrical Engineering, Power Electronics, Electrical Machines and Networks