Open AccessShort-term forecast methods of electricity generation by solar power plants and its classification
Author(s) -
Dmitry Tyunkov,
A. S. Gritsay,
V. I. Potapov,
Р. Н. Хамитов,
A. V. Blohin,
L. K. Kondratukova
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1260/5/052033
Subject(s) - term (time) , electricity generation , electricity , computer science , solar power , meteorology , econometrics , environmental science , power (physics) , engineering , mathematics , geography , physics , quantum mechanics , electrical engineering
The article provides a classification of existing forecast models the generation of electricity by solar power plants and discusses various options for forecast methods for each of the selected models. As a result of the study, it was concluded that the most promising forecast methods are hybrid statistical-adaptive methods.