Application of Ensemble Kalman Filter in Forecasting the Electricity Grid Carbon Factor

Abstract

Several publications have discussed the application of Ensemble Kalman Filter (EnKF) in history matching problems. The EnKF provides updated approximations based on the conditioned constraints to the historical data. In this paper we show how the EnKF is capable of forecasting/recovering the unpredictable trends of Electricity Grid Carbon Factor (EGCF). We adopt the EGCF scenario in the UK based on the available energy data provided by the Balancing Mechanism Reporting System (BMRS). We apply EnKF for forecasting the incomplete datasets in the UK EGCF in 2014. We present the ability of EnKF to recover the EGCF.