Digital platform of reliability management systems for operation of microgrids

19067 6 102979 2 314276 document 102979 1-s2.0-S2352484723012787-main.pdf application/pdf eca5c3063f61485f30df469abc78c8c4 MD5 1749523 2023-09-21 08:29:46 https://pure.iiasa.ac.at/id/eprint/19067/1/1-s2.0-S2352484723012787-main.pdf 19067 1 1 application/pdf text en public cc_by_4

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published 102980 1 314282 document 102980 indexcodes.txt text/x-c++ d2388474a0fab63ed533dfa0add69bd9 MD5 11606 2023-09-21 08:39:55 https://pure.iiasa.ac.at/id/eprint/19067/2/indexcodes.txt 19067 2 2 text/x-c++ other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/102979 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/102979 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/102979 archive 353 disk0/00/01/90/67 2023-09-21 08:31:00 2023-09-21 08:31:00 2023-09-21 08:31:00 article show Krupenev D. Komendantova N. 1880 0000-0003-2568-6179 Boyarkin D. Iakubovskii D. Digital platform of reliability management systems for operation of microgrids pub ASA CAT Microgrids, Power supply reliability, Digital transformation, Reliability systems management, Digital platform, Prosumers, Machine learning This paper deals with the issue of ensuring the reliability of microsystems in the modern-day development of digital control technologies. The use of digital technologies to manage the reliability of microsystems stems from the development of various modern energy technologies with complex structures that require enhanced management systems to ensure their reliability. In this paper, we propose the use of digital platforms to manage the reliability of microsystems. The way digital platforms function makes it possible to automate the process of collecting, processing, and storing the necessary information about both power equipment and the operating modes of distribution networks and, in so doing, to assess and ensure the reliability of microsystems at all stages of the life cycle. In this paper, we present the main operational characteristics and principles of digital platforms. To analyze the reliability of microsystems within the framework of the functioning of digital platforms, we propose the use of machine learning methods. We suggest two algorithms for assessing the reliability of microsystems. In the first algorithm, the model is trained to analyze the regime indicators of the microsystem and, on the basis of these, to determine the reliability indicators. In the second algorithm, the model is trained to immediately determine the reliability indicators of the microsystem. Practical results have shown the effectiveness of the proposed algorithms in terms of the speed of assessing the reliability of microsystems while maintaining the required accuracy of calculations. 2023-11 published doi:10.1016/j.egyr.2023.09.048 161 public Energy Reports 10 2486-2495 TRUE 2352-4847 no info:eu-repo/semantics/article