Under the background of “dual-carbon” strategy, this paper proposes a path planning method for lowcarbon transition of power system integrating dynamic carbon oriented mechanism and meta-heuristic algorithm. By constructing a dual low-carbon demand response model and a stepped carbon trading model, and combining with the refined simulation framework of EnergyPLAN platform, a multi-objective optimization model is established from the three dimensions of power supply, carbon emission and costing. Parameter planning and Nash negotiation game theory are introduced to generate the Pareto frontier equilibrium solution, and the cooperative scheduling optimization of microgrid cluster is realized based on CPLEX tool. The simulation results show that microgrids A and B realize the improvement of power flow efficiency within the system through the time-sharing tariff mechanism (peak tariff of 0.82 yuan/kWh and low valley tariff of 0.25 yuan/kWh), and the internal tariff is 12%-18% lower than that of the external grid, which promotes the consumption of renewable energy. The total power generation costs under low, medium and high risk scenarios are 47.68 trillion, 53.12 trillion and 58.45 trillion yuan respectively, and carbon emissions are reduced to 2,444.33Mt, 2,142.21Mt and 1,793.55Mt respectively at the end of the planning period, and the average annual emission reduction under the high-risk scenario reaches 648.84Mt, which improves the emission reduction efficiency by 37% compared with that of the low carbon price scenario. The sensitivity analysis shows that when the carbon price is raised from 30 yuan/ton to 100 yuan/ton, the medium-risk scenario reduces carbon emissions by 237 million tons, and the total cost is reduced by 0.81 trillion yuan. When the share of energy storage is increased from 5% to 15%, the unit generation cost of the high-risk scenario decreases by 0.039 yuan/kWh, saving 2.07 trillion yuan.
