Title :
ANN based load forecasting: a parallel structure
Author :
Hu, Chang ; Cao, Li
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Air-conditioning system plays an important role in modern architectures, whereas load forecasting provides a more efficient and accurate way to control air-conditioning systems. In this article, a parallel structure called 2-ANN for air-conditioner load forecasting is proposed. 2-ANN combines two independent predictors by a corrector. For forecasting, first the predictors make separate predictions, and then their predictions are compared and revised by the corrector to form a single output. 2-ANN structure is easy to analysis as well as easy to implement. In implementation, the predictors and corrector are back-propagation (BP) neural networks. The parallel structure, set up with three BP networks, is trained and tested by real-world data of air-conditioner load. In those tests, 2-ANN outperforms each one of the two predictors alone.
Keywords :
air conditioning; backpropagation; load forecasting; neural nets; power engineering computing; air-conditioning system; artificial neural networks; back-propagation neural networks; independent predictors; load forecasting; parallel structure; Artificial neural networks; Automation; Control systems; Feedback loop; Load forecasting; Modems; Neural networks; Predictive models; Recurrent neural networks; Testing;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1400900