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Application of ensemble Kalmen filter in forecasting the electricity grid carbon factor.

Eng Tseng Lau*,, ; Qingping Yang*,, ; Forbes, A B; Livina, V N (2015) Application of ensemble Kalmen filter in forecasting the electricity grid carbon factor. Int. J. Elect. Energy, 3 (4). pp. 209-212.

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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

Item Type: Article
Subjects: Mathematics and Scientific Computing
Mathematics and Scientific Computing > Modelling
Identification number/DOI: 10.18178/ijoee.3.4.209-212
Last Modified: 02 Feb 2018 13:13
URI: http://eprintspublications.npl.co.uk/id/eprint/7166

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