Short-Term System Imbalance Forecast Using Autoregressive Distributed Lag Method

The imbalance between supply and demand is a crucial factor in the operation of the power system therefore, it is essential to be able to predict its value from historical, measured, and prediction data. This work proposes a multistep version of the autoregressive distributed lag model for the short-term forecast of imbalance. The proposed forecast model has been compared to a Long Short-Term Memory network-based procedure using real data. The results show that the proposed multistep autoregressive forecast model outperforms the others in all three evaluation metrics. Since, in many cases, it is sufficient to specify the sign of the imbalance, this paper introduces the concept of sign accuracy as a function of the forecasted imbalance and evaluates it for the investigated solutions.