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International Journal of Information Technology & Computer Science ( IJITCS )

Abstract :

The key condition for reliable work of electric  power systems is the presence of efficient system forecasting of state variables (load flows, power flow,  voltage magnitude, etc.). Development of the state-of-theart  technique for robust forecasting of behavior of  nonlinear and non-stationary power systems is one of the  challenges in energetics. This paper aims to evaluate Data  mining type of models for short-term forecasting of power  system operating condition. Models that are examined  include artificial neural networks, support vector  machines; autoregressive integrated moving average and  exponential smoothing. Evaluation results are presented  for voltage magnitude forecasts.

Keywords :

: power system; data mining; forecasting; data  analysis, model, state variables

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