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Predicting the Power Generation Renewable Energy Sources by using ANN

dc.contributor.authorRubanenko, O.en
dc.contributor.authorGundebommu, S. L.en
dc.contributor.authorCosovic, M.en
dc.contributor.authorLesko, V.en
dc.date.accessioned2021-11-17T12:58:20Z
dc.date.available2021-11-17T12:58:20Z
dc.date.issued2021
dc.description.abstractThe analysis of decreasing trend in prediction of CO2 emission is presented in this paper. Different reasons of CO2 reduction in Ukraine are presented; one is by increasing generation by renewable energy sources (RES). This on the other hand creates a new problem of RES power generation compensation instability. Means of ensuring the balance reliability of the power system in terms of RES integration are presented. The installation of charging stations for electric vehicles and the use of hydrogen technologies and modern storage can provide power grid balance. Also, decreasing the deviation of the current (real) value the predicted value of power generation is a way to compensate for power unbalance. This paper proposes power generation forecasting for photovoltaic power plants by using Adaptive Neuro-Fuzzy Inference Systems library in MATLAB and taking into account meteorological factors.en
dc.identifier.citationPredicting the Power Generation Renewable Energy Sources by using ANN [Text] / O. Rubanenko, S. L. Gundebommu, M. Cosovic, V. Lesko // 20th International Symposium INFOTEH-JAHORINA, 17-19 March 2021. – Bosnia and Herzegovina, 2021. – P. 1-6.en
dc.identifier.doi10.1109/INFOTEH51037.2021.9400527
dc.identifier.urihttp://ir.lib.vntu.edu.ua/handle/123456789/34196
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.relation.ispartof20th International Symposium INFOTEH-JAHORINA, 17-19 March 2021 : 1-6.en
dc.subjectrenewable energy sourcesen
dc.subjectpower griden
dc.subjectpower balanceen
dc.subjectoptimal controlen
dc.titlePredicting the Power Generation Renewable Energy Sources by using ANNen
dc.typeArticle

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