Title :
Short term load forecast using Burg autoregressive technique
Author :
Kamel, Nidal ; Baharudin, Zuhairi
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Teknol. Petronas, Tronoh
Abstract :
Short-term load forecasting plays an important role in planning and operation of power system. The accuracy of this forecasted value is necessary for economically efficient operation and also for effective control. This paper describes a method of autoregressive Burg in solving one week ahead of short term load forecasting. The proposed method is tested based from historical load data of Malaysia Grid system. The accuracy of proposed method, i.e., the forecast error, which is the difference between the forecast value and actual value of the load, is obtained and reported.
Keywords :
autoregressive moving average processes; load forecasting; power system economics; power system planning; Burg autoregressive technique; autoregressive moving average; power system economic; power system operation; power system planning; short term load forecasting; Artificial neural networks; Demand forecasting; Economic forecasting; Fuzzy logic; Intelligent systems; Load forecasting; Power generation economics; Power system economics; Power system planning; Predictive models; Autoregressive moving average (ARMA); Burg; MAPE; Short term load forecasting (STLF); autoregressive (AR);
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
DOI :
10.1109/ICIAS.2007.4658519