Hybrid solar irradiance now-casting by fusing Kalman filter and regressor

Highlights

The proposed hybrid predictor fuses a Kalman filter predictor and a regressor predictor.

A time-varying adaptive system function for Kalman filter is designed.

Two fusion alternatives based on local root mean square error are proposed and compared.

When the local RMSE of Kalman filter is larger than a threshold, the prediction result from the regressor predictor is chosen.

Abstract

In this work, a hybrid solar irradiance now-casting mechanism is proposed. The proposed hybrid predictor fuses the results from both Kalman filter predictor and regressor predictor to benefit from the advantages of both techniques. A time-varying adaptive system function for Kalman filter is designed to deal with ramp-down events for more accurate prediction. Three fusion alternatives based on local root mean square error computation are proposed and compared. The experimental results have validated the effectiveness of the proposed method on a challenging dataset.

Keywords

  • Solar irradiance;
  • Prediction;
  • Kalman filter;
  • Regression

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