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Название: Inappropriate Machine Learning Application in Real Power Industry Cases
Авторы: Khalyasmaa, A.
Matrenin, P.
Eroshenko, S.
Дата публикации: 2022
Издатель: Institute of Advanced Engineering and Science
Institute of Advanced Engineering and Science
Библиографическое описание: Khalyasmaa A. Inappropriate Machine Learning Application in Real Power Industry Cases / A. Khalyasmaa, P. Matrenin, S. Eroshenko. — DOI 10.19181/socjour.2021.27.3.8427 // International Journal of Electrical and Computer Engineering. — 2022. — Vol. 12. — Iss. 3. — P. 3023-3032.
Аннотация: Global digital transformation of the energy sector has led to the emergence of multiple digital platform solutions, the implementation of which have revealed new problems associated with continuous growth of data volumes requiring new approaches to their processing and analysis. This article is devoted to the improper application of machine learning approaches and flawed interpretation of their output at various stages of decision support systems development: data collection; model development, training and testing as well as industrial implementation. As a real industrial case study, the article examines the power generation forecasting problem of photovoltaic power plants. The authors supplement the revealed problems with the corresponding recommendation for industrial specialists and software developers. © 2022 Institute of Advanced Engineering and Science. All rights reserved.
Ключевые слова: DIGITAL TRANSFORMATION
INTELLIGENT SYSTEM
MACHINE LEARNING APPLICATION
PHOTOVOLTAIC POWER PLANTS
POWER GENERATION FORECASTING
URI: http://hdl.handle.net/10995/111084
Условия доступа: info:eu-repo/semantics/openAccess
Идентификатор SCOPUS: 85126446498
ISSN: 2088-8708
DOI: 10.19181/socjour.2021.27.3.8427
Сведения о поддержке: The reported study was supported by Russian Foundation for Basic Research RFBR, research project No. 20-010-00911.
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