Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс:
http://elar.urfu.ru/handle/10995/101378
Название: | Simulated annealing, differential evolution and directed search methods for generator maintenance scheduling |
Авторы: | Gubin, P. Y. Oboskalov, V. P. Mahnitko, A. Petrichenko, R. |
Дата публикации: | 2020 |
Издатель: | MDPI AG |
Библиографическое описание: | Simulated annealing, differential evolution and directed search methods for generator maintenance scheduling / P. Y. Gubin, V. P. Oboskalov, A. Mahnitko, et al. — DOI 10.3390/en13205381 // Energies. — 2020. — Vol. 13. — Iss. 20. — 5381. |
Аннотация: | Generator maintenance scheduling presents many engineering issues that provide power system personnel with a variety of challenges, and one can hardly afford to neglect these engineering issues in the future. Additionally, there is vital need for further development of the repair planning task complexity in order to take into account the vast majority of power flow constraints. At present, the question still remains as to which approach is the simplest and most effective, as well as appropriate for further application in the power flow-oriented statement of the repair planning problem. This research compared directed search, differential evolution, and very fast simulated annealing methods based on a number of numerical calculations and made conclusions about their prospective utilization in terms of a more complicated mathematical formulation of the repair planning task. A comparison of results shows that the effectiveness of directed search methods should not be underestimated, and that the pure differential evolution and very fast simulated annealing approaches are not essentially reliable for repair planning. The experimental results demonstrate the perspectivity of unifying single-procedure methods in order to net out risk associated with specific features of these approaches. © 2020 by the authors. |
Ключевые слова: | DIFFERENTIAL EVOLUTION DIRECTED SEARCH GENERATOR MAINTENANCE SCHEDULING SIMULATED ANNEALING ELECTRIC LOAD FLOW EVOLUTIONARY ALGORITHMS NUMERICAL METHODS REPAIR SCHEDULING DIFFERENTIAL EVOLUTION DIRECTED SEARCHES FAST SIMULATED ANNEALING GENERATOR MAINTENANCE SCHEDULING MATHEMATICAL FORMULATION NUMERICAL CALCULATION POWER FLOWS REPAIR PLANNING SIMULATED ANNEALING |
URI: | http://elar.urfu.ru/handle/10995/101378 |
Условия доступа: | info:eu-repo/semantics/openAccess |
Идентификатор SCOPUS: | 85093110531 |
Идентификатор WOS: | 000582902800001 |
Идентификатор PURE: | 87acbbfc-87be-472b-babf-915231a30608 14163184 |
ISSN: | 19961073 |
DOI: | 10.3390/en13205381 |
Сведения о поддержке: | This work was funded by the European Regional Development Fund within the Activity 1.1.1.2 “Postdoctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Programme “Growth and Employment” (No. 1.1.1.2/VIAA/1/16/021). This research has also been supported by the Latvian Council of Science project: Management and Operation of an Intelligent Power System (I-POWER) (No. lzp-2018/1-0066). |
Располагается в коллекциях: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
---|---|---|---|---|
2-s2.0-85093110531.pdf | 6,25 MB | Adobe PDF | Просмотреть/Открыть |
Все ресурсы в архиве электронных ресурсов защищены авторским правом, все права сохранены.