21 / 2023-09-17 18:48:38
Considering the optimal input for global horizontal irradiance forecasting based on Informer
Global horizontal irradiance (GHI); forecasting; Inforemer; Optimal input; Long series
Final Paper
Chengcheng Jiang / Shanghai University of Electric Power
Qunzhi Zhu / Shanghai University of Electric Power
Accurate global horizontal irradiance (GHI) prediction is significant for the stability and economy of power system operation. This paper proposes an advanced model Informer to predict GHI and selects Root Mean Square Error (RMSE) as the primary evaluation metric to calculate the error. Through discussing the Pearson correlation coefficient, chooses five strong correlation parameters and selects the optimal input through the experiments of 2 and 3 inputs. The Informer model is compared with five reference machine learning (ML) models, and the performance improvement is over 99% under optimal input, which proves the proposed model's superiority. Finally, the Informer's long series prediction ability is verified, and the results showed that Inforemer can efficiently complete long series prediction tasks without losing accuracy, which has high practical value.

 
Important Date
  • Conference Date

    Dec 08

    2023

    to

    Dec 10

    2023

  • Nov 01 2023

    Draft paper submission deadline

  • Dec 10 2023

    Registration deadline

Sponsored By
IEEE IAS
Organized By
Southwest Jiaotong University (SWJTU)