Issue |
E3S Web Conf.
Volume 216, 2020
Rudenko International Conference “Methodological problems in reliability study of large energy systems” (RSES 2020)
|
|
---|---|---|
Article Number | 01010 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.1051/e3sconf/202021601010 | |
Published online | 14 December 2020 |
Research of the influence of power engineering equipment accident rate on the indicators of adequacy and the value of operating reserve of electrical power system
1 Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), 130 Lermontov Street, Irkutsk, 664033, Russia
2 Irkutsk National Research Technical University (INRTU), 83 Lermontov Street, Irkutsk, 664074, Russia
* Corresponding author: krupenev@isem.irk.ru
Reliable source information is necessary for a correct adequacy assessment of electric power systems. Among a wide set of initial information, coefficients of accident rates of power engineering equipment are important. The analysis of methods for determining the coefficients of accident rates of power engineering equipment, which are used in the assessment of the adequacy of electric power systems, is presented in the article, also the features of accounting for coefficients of accident rates are elicited. The experimental part of the article is showed the influence of generating aggregates accident rate on the level of operating reserve on the example ofthe Unified Energy System of Russia.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.