Application of Neural Networks for Very Short-Term Load Forecasting in Power Systems

Load forecasting has become in recent years one of the major areas of research in electrical engineering. In a deregulated, competitive power market, utilities tend to maintain their generation reserve close to the minimum required by an independent system operator. This creates a need for an accurate instantaneous-load forecast for the next several minutes. An accurate forecast eases the problem of generation and load management to a great extent. This paper presents a novel artificial neural network (ANN) for very short-term load forecasting. The model with tapped delay line input is simple, fast, and accurate. Obtained results from extensive testing on Taipower System load data confirm the validity of the proposed approach.

• Type: Conference
• Year: 2005
• Where: ISNN
• Authors: Hungcheng Chen, Kuohua Huang, Lungyi Chang
• Keywords: Accurate Instantaneous-load Forecast, ISNN 2005, Load Forecasting, Short-term Load Forecasting