<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Photovoltaic power system is taking a significant percentage of power system and the demands for accurate forecasting of the power outputs is surging. In prior works, the forecasting problem was formulated as a regression problem, however, which most cannot guarantee that the forecasted outputs is nonnegative. To solve this problem, we proposed a novel probabilistic model by using nonlinear regression and Bayesian learning method. In the paper, we present the detailed theoretical derivations and interpretations. The simulation results show the validity and feasibility of the proposed algorithm by comparing with the traditional SVM algorithm.</p></abstract>

Photovoltaic power system is taking a significant percentage of power system and the demands for accurate forecasting of the power outputs is surging. In prior works, the forecasting problem was formulated as a regression problem, however, which most cannot guarantee that the forecasted outputs is nonnegative. To solve this problem, we proposed a novel probabilistic model by using nonlinear regression and Bayesian learning method. In the paper, we present the detailed theoretical derivations and interpretations. The simulation results show the validity and feasibility of the proposed algorithm by comparing with the traditional SVM algorithm.

An Bayesian Learning and Nonlinear Regression Model for Photovoltaic Power Output Forecasting

Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment, Ministry of Education

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Photovoltaic power system is taking a significant percentage of power system and the demands for accurate forecasting of the power outputs is surging. In prior...

An Bayesian Learning and Nonlinear Regression Model for Photovoltaic Power Output Forecasting

Online veröffentlicht: 15. Sept. 2020

Seitenbereich: 531 - 542

Eingereicht: 24. Feb. 2020

Akzeptiert: 26. Mai 2020

DOI: https://doi.org/10.2478/amns.2020.2.00032

Schlüsselwörter
Bayesian Learning, Power Output Forecasting, Data-based Regression, Probabilistic Model

© 2020 Wengen Gao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An Bayesian Learning and Nonlinear Regression Model for Photovoltaic Power Output Forecasting

Online veröffentlicht: 15. Sept. 2020

Seitenbereich: 531 - 542

Eingereicht: 24. Feb. 2020

Akzeptiert: 26. Mai 2020

DOI: https://doi.org/10.2478/amns.2020.2.00032

SchlüsselwörterBayesian Learning, Power Output Forecasting, Data-based Regression, Probabilistic Model

© 2020 Wengen Gao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Bayesian Learning, Power Output Forecasting, Data-based Regression, Probabilistic Model