Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms

Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms

Renewable energy sources (RES) are seen as a means of the fuel and energy complex carbon footprint reduction but the stochastic nature of generation complicates RES integration with electric power systems. Therefore, it is necessary to develop and improve methods for forecasting of the power plants...

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Bibliographic Details
Main Authors: P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits
Format: Article
Language:Russian
Published: Belarusian National Technical University 2023-08-01
Series:Известия высших учебных заведений и энергетических объединенний СНГ: Энергетика
Subjects:
short-term forecasting
electricity generation
photovoltaic plant
renewable energy sources
meteorological factors
insolation
solar radiation
neural networks
data clustering
predictive model
data preprocessing
machine learning
principal component analysis
adaptive boosting
linear regression
Online Access:https://energy.bntu.by/jour/article/view/2287
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