The Autoregressive Moving Average Model for Separation of The Additional Noise

This paper provides main modeling approaches for the prediction of electricity prices. It presents actual global problem of RES (= Renuable Energy Sources) and their influences on hourly prices on wholesale markets. The strong weather dependence of RES causes that RES are bilanced maily on the short term markets as close to physical delivery as it is possible. The most appropriate markets for selling and maximalization of RES production is necesssary to choose. For this type of consideration the high quality and massive prediction model of electricity prices is required. More kind of prediction models have already exist, but still there exists systematic errors, which brings unrealibility to the price prediction. The autoregressive moving average models are proposed for separation of the addtional noise and their calibration is shown.