A Prediction-Correction Based Method for Calculating the Affine Carbon Flow in Power Systems

Carbon flow calculation methods, which can allocate the direct carbon emissions generated during unit power generation to the load side in the form of indirect carbon emissions, have become an important means of driving consumers to reduce carbon emissions. However, due to the fluctuation of loads and renewable energy sources, the system carbon emission intensity cannot be fully predicted in advance. Therefore, this paper proposes an affine carbon emission flow calculation method for measuring the trend and interval of the system carbon emission flow under a certain level of uncertainty effect. First, for the discontinuity of the carbon emission flow model, the carbon modes are divided according to the branch power flow direction of the whole network, and all possible carbon modes are identified based on Kirchhoff’s law and the analytical nature of the affine noise elements. Second, for the nonlinearity of carbon emission flow, new noise elements are constructed in the calculation of each carbon mode based on the idea of prediction-correction to ensure the completeness of the calculation. IEEE14 simulations show that the method proposed in this paper takes less than 7% of the time of the Monte Carlo method and has an average conservatism of less than 6%.