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Optimization of carbon emissions in smart grids

In this paper the carbon emissions in smart grids are optimised. This is achieved by performing dynamical modelling with uncertainty analysis of smart grids using an Ensemble Based Closed-Loop Optimisation Scheme (EnOpt). Uncertainties include the fluctuations of consumer energy demand (behavioural) and generation fuel mix (green and non-green) are estimated using the Monte Carlo method. The UK electricity grid carbon factor is calculated based on the available energy data provided by the Balancing Mechanism Reporting System (BMRS). We apply the Ensemble Kalman Filter (EnKF) for the forecasting and prediction of the energy generation, consumption and resultant carbon emissions. Then we apply EnOpt to maximize the carbon savings in the system. Finally, we present results of EnOpt optimization of carbon emissions with estimated carbon savings.