Low-carbon Optimal Scheduling of Power System Based on Shapley Value Carbon Responsibility Allocation Theory

With the progress of global low-carbon, reducing carbon dioxide from the grid not only requires the macro-control on the source side, but also the optimization treatment on the demand side can reduce the carbon emissions of the network. On this basis, carbon emission theory and carbon price are taken as pricing signals to build a low-carbon optimized emission model in power system on account of demand response. Firstly, on account of carbon date, carbon emission stream and Shapley carbon responsibility allocation means, carbon emission responsibility values corresponding to carbon emissions on different demand sides are obtained. Secondly, according to different liability values, a reasonable carbon price ladder model is proposed. Then, the demand response based on carbon price is established, so as to lessen the carbon date in the Power stream network by optimizing the consumption behavior of users and utilizing the adjustment behavior on the demand side. Finally, based on IEEE-14 nodes, the network of wind-bearing motors is simulated and analyzed. Through comparing carbon date in systems, the conclusion can be reached that the optimization treatment decrease carbon date in the network and achieve the purpose of power source saving and consumption reduction.