Title :
Gauss-Markov models for forecasting and risk evaluation
Author :
Wong, Y.K. ; Rad, A.B.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech., Hung Hom, Hong Kong
Abstract :
In power systems, expansion of generating and transmission facilities, day-to-day operation are dependent on the future loading demands. Load uncertainty can be modeled using the Gauss-Markov properties for a random process. Sharing the Gauss-Markov characteristics, Box-Jenkins (ARIMA) forecast procedure is described. Then, electricity consumption data is simulated as an application of ARIMA models. Finally, a risk evaluation study using a Gauss-Markov load model is also demonstrated
Keywords :
Markov processes; autoregressive moving average processes; load forecasting; power consumption; power systems; risk management; time series; ARIMA model; ARIMA models; Box-Jenkins forecast procedure; Gauss-Markov load model; Gauss-Markov models; autoregressive integrated moving average model; day-to-day operation; electricity consumption; future loading demands; generating facilities expansion; load forecasting; load uncertainty modelling; power systems; random process; risk evaluation; time series models; transmission facilities expansion; Autocorrelation; Gaussian processes; Load forecasting; Load modeling; Power generation; Power system modeling; Power system simulation; Predictive models; Random processes; Uncertainty;
Conference_Titel :
Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on
Print_ISBN :
0-7803-4495-2
DOI :
10.1109/EMPD.1998.705539
