Probabilistic Forecasting for photovoltaic power generation based on Bayes Ridge regression
Konferenz: EMIE 2022 - The 2nd International Conference on Electronic Materials and Information Engineering
15.04.2022 - 17.04.2022 in Hangzhou, China
Tagungsband: EMIE 2022
Seiten: 3Sprache: EnglischTyp: PDF
Autoren:
Jin, Fei; Liu, Jingli; Zhou, Yu (State Grid Weifang County Power Supply Company, Weifang, Shan Dong, China)
Yin, Ziyang (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, China)
Inhalt:
With the large-scale integration of new energy sources such as photovoltaics, the uncertainty of their output has brought more significant challenges to the safe and stable operation of the power system. Therefore, this paper proposes a photovoltaic prediction method based on Bayesian ridge regression (BRR) to solve this problem. This method can achieve the prediction of photovoltaic output through probabilistic analysis. At the same time, it provides data support for power system optimal dispatch based on uncertainty modeling.