New Combination Approach to Predict Daily Electric Load Based on Artificial Neural Networks

  • Enduardo The University of São Paulo São Carlos, Brazil
  • Hugo Ribeiro The University of São Paulo São Carlos, Brazil
Keywords: Artificial Neural Network, Optimization Algorithm, Short-Term Load Forecasting, Intelligent Systems

Abstract

In this paper, new methods combined based on Modified Bat Algorithms (MBA) and Artificial Neural Network algorithms have been proposed to estimate the peak power load of electricity. In the proposed method, Bat Algorithm is used as a popular optimization method and Artificial Neural Networks are also used as a mathematical method that is strong in mapping nonlinear relationships between model variables for the purpose of predicting daily electrical loads. In addition, to improve the performance of bat algorithms with respect to avoiding local optimal utilization and increasing the speed of convergence, several modifications have been made in the bat algorithm called SAMBA. The experimental results show that the proposed method has superior performance compared to other traditional machine learning algorithms.

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Published
2018-08-31
Section
Articles