A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

Algorithm 1

Pseudocode of EEMD.

Input:

  —a sequence of sample data

Output:

  —a sequence of forecasting data

Parameters:

 —the number of ensemble for EEMD.

 —the amplitude of white noise.

 —the iterations of experiments.

 —the number of intrinsic mode function components.

(1) Initialize the number of IMF: ;

(2) Do EEMD, EEMD loop start;

(3) ;

(4) If  n <     do

(5)  Add white noise to the original data ;

(6)  Assign original data in the first column and start to find an IMF 10 times;

(7)  Decompose according to the EMD method;

(8) End if

(9) Calculate the mean: ;

(10) Return  .