Short-Term Load Forecasting of Pole-Transformer Using Artificial Neural Networks

신경회로망을 이용한 배전용 변압기의 단기부하예측

In this paper, the short-term load forecasting of pole-transformer is performed by artificial neural networks. Input parameters of the Nosed algorithm are peak loads of pole-transformer of previous days and their temperatures. The proposed algorithm is tested for ore of the pole-transformers in seoul, korea. Test results show that the proposed algorithm improves the accuracy of the load forecasting of pole-transformer compared with the conventional algorithm.