Optimal Carbon Flow and Sensitivity Analysis under New Energy Integration Based on MVO Algorithm

With the continuous increase in carbon emissions from the power system, low-carbon transformation of the power system is imperative. An optimal carbon flow calculation method under the integration of new energy sources is proposed. By adjusting the power generation output, the carbon emissions on the generation side are reasonably allocated based on load nodes and branch network losses. A mathematical model for carbon reduction of new energy sources is established to quantitatively evaluate the specific contributions of energy-saving and emission reduction by new energy units. First, the impacts of photovoltaic and wind power grid integration are analyzed, and the carbon flow calculation model is optimized. Then, a mathematical model is established with the optimization objective of power grid generation cost, and the results are used as constraints for the optimal carbon flow. Subsequently, the power generation output is mapped to the carbon flow rate using node admittance matrix, and an optimal carbon flow calculation model is established. The multi-verse optimization(MVO), a multi-objective optimization algorithm, is used for optimization and sensitivity analysis to evaluate the stability and feasibility of the optimal solution. Finally, the simulation analysis of the IEEE 30-node system shows that the MVO algorithm can achieve convergence on the large-scale optimal carbon flow calculation model faster than the traditional optimization algorithm, with better speed and accuracy, and the proposed optimal carbon flow model can quantify the contribution of new energy units in the carbon reduction process and reduce carbon emissions by about 23.41% while taking into account the economy.