Title :
Short-term power load forecasting based on autocorrelation function optimization
Author :
Paarmann, Larry D. ; Najar, Mohamed D.
Author_Institution :
Dept. of Electr. Eng., Wichita State Univ., KS, USA
Abstract :
Reliable, short-term load forecasting by computer has been a topic of considerable interest. In this paper, a method to accomplish this that automatically adapts to changing conditions, requiring very little human intervention, is on-line, and is reliable, Is presented. It makes use of time-series models, automatically adjusting the model parameters, to forecast the load. One thing that is unique in this method is the autocorrelation optimization used for incorporating daily and weekly periodicities
Keywords :
correlation methods; electric power generation; load forecasting; optimisation; power system analysis computing; power system planning; time series; autocorrelation function optimization; daily periodicities; model parameters; power generation; short-term power load forecasting; time-series models; weekly periodicities; Autocorrelation; Energy management; Filters; Humans; Load forecasting; Optimization methods; Power generation; Power system management; Predictive models; Weather forecasting;
Conference_Titel :
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location :
Lafayette, LA
Print_ISBN :
0-7803-2428-5
DOI :
10.1109/MWSCAS.1994.519085
