Power Forecast of Renewable Energy Power Plant Based on Kalman Filter Method

Authors

  • Shuang Li School of Information Engineering, Xi'an Mingde Institute of Technology, Xi’an (China) Author
  • Zhannan Yin Research and Development Department(R&D), Xian Shaangu Intelligent Information Technology Co, Xi’an (China) Author

DOI:

https://doi.org/10.52152/

Keywords:

Kalman Filter, Renewable Energy, Power Generation by Power Plant, Power Prediction

Abstract

At present, the prediction accuracy of water power plant is poor. In order to improve the prediction accuracy of water power plant. Firstly, the regression sliding model is obtained by analyzing the power sequence of the water power plant, and the regression sliding model is regarded as Kalman filter method. Then, the equation value is obtained by the state equation of Kalman filter method, and the power generation is predicted by Kalman filter method. In the follow-up case analysis, the evaluation index of the China Energy Bureau is used to evaluate the prediction accuracy of power generation. The MATLAB prediction results show that the proposed method in this paper can get better results and higher prediction accuracy.

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Published

2024-08-12

Issue

Vol. 22 No. 6 (2024)

Section

Articles