Short-term load forecasting of BP network based on bacterial foraging optimization

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Han, Yikan^1 ; Xiong, Hejin^1 ; Wei, Di^2

College of Automation, Wuhan University of Technology, Wuhan, Hubei

430070, China^1

State Grid Xiaogan Electric Power Supply Company, Xiaogan, Hubei

432000, China^2

关键词: Bacterial foraging optimization;    Bacterial foraging optimization algorithms;    BP neural networks;    Convergence process;    Global optimal solutions;    Gradient orientations;    Prediction accuracy;    Short term load forecasting;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/5/052082/pdf
DOI  :  10.1088/1757-899X/569/5/052082

来源: IOP

【 摘 要 】

The traditional BP neural network search algorithm based on gradient orientation is easy to fall into local minimum, the convergence process is slow, and it cannot guarantee the convergence to the global optimal solution. In order to improve the prediction accuracy of short-term load forecasting, this paper applies the bacterial foraging optimization algorithm to BP neural network, using its unique breeding and eviction operation, can improve the convergence speed of the algorithm, strengthen the ability to search the global optimal solution, and reduce the prediction error.