... Web of Conferences. Vol.139. ID: 01018. 2019. 6 p. DOI: 10.1051/e3sconf/201913901018 This study presents the algorithms for modeling of scheduled repairs of generating equipment when assessing the resource adequacy of electric power systems by the Monte Carlo method that relies on random events. We present an analysis of the algorithms adopted in the available software and computer systems used to assess the resource adequacy and highlight their shortcomings. We propose an algorithm for modeling ...
Теги: electric power system , generating unit , monte carlo method , resource adequacy , scheduled repairs , electric power systems , generating equipments , numerical experiments , monte carlo methodsБояркин Д.А., Крупенев Д.С., Якубовский Д.В. Использование методов машинного обучения при оценке надёжности электроэнергетических систем методом Монте-Карло // Вестник ЮУрГУ. Серия «Математическое моделирование и программирование». Т.11. №4. 2018. C.146-153. DOI: 10/14529/mmp18041 В статье рассматривается вопрос повышения вычислительной эффективности процедуры оценки балансовой надежности электроэнергетических систем при использовании метода статистических испытаний (метод Монте-Карло). При использовании...
Теги: электроэнергетические системы , оценка надежности , метод монте-карло , машинное обучение , electric power systems , adequacy assessment , monte carlo method , machine learning... Modelling, Programming and Computer Software. Vol.11. No.4. 2018. P.146-153. DOI: 10.14529/mmp180411 The article considers the question of increasing the computational efficiency of the procedure for electric power systems adequacy assessment using the Monte Carlo method. In the framework of using this method, it is necessary to randomly generate a certain number of system states. As it is known the speed and accuracy of the calculation depends on the number of such states to be analyzed, so one of ...
Теги: adequacy assessment , electric power systems , machine learning , monte carlo methodBoyarkin D.., Krupenev D.S., Iakubovskiy D.., Sidorov D.N. Machine learning in electric power systems adequacy assessment using Monte-Carlo method // Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. ID: 8109871. P.201-205. ISBN (print): 9781538615966. DOI: 10.1109/SIBIRCON.2017.8109871 This paper deals with the computational efficiency related problem appearing in electric power systems adequacy assessment using Monte-Carlo method...
Теги: adequacy assessment , electric power systems , machine learning , monte carlo method , random forest , support vector machine , artificial intelligence , computational efficiency , decision trees , efficiency , learning systems , problem solving , support vector mach
