Predicting the Power Generation Renewable Energy Sources by using ANN
Author
Rubanenko, O.
Gundebommu, S. L.
Cosovic, M.
Lesko, V.
Рубаненко, О. О.
Лесько, В. О.
Date
2021Metadata
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- Наукові роботи каф. ЕСС [342]
Abstract
The 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.
URI:
http://ir.lib.vntu.edu.ua//handle/123456789/34196