Thoroughly studying the emission reduction responsibilities, potential, and pathways of the power industry is an important reference for promoting the green and low-carbon transformation of energy, as well as a key support for achieving the goal of peak carbon emissions and carbon neutrality for the whole society. The analysis of carbon emission reduction in the power industry needs to consider external factors such as economy, society, resources, and environment, as well as the constraints of power system operation such as electricity balance and unit output limitations. It is a complex nonlinear problem with multiple objectives, constraints, and parameters. Firstly, factors such as economic growth, industrial restructuring, and energy substitution are analyzed. The variables included electricity load, installed capacity of various power sources, energy storage capacity, carbon capture scale, and cross regional power transmission capacity. The objective function is the transformation cost of the power industry, and the constraints include electricity balance, carbon emissions, new energy utilization, hydrogen production demand, and the development of low-carbon, zero carbon, and negative carbon key technologies. A carbon reduction analysis model for the power industry is constructed, and an OpenMP multi-core parallel particle swarm optimization algorithm and a dual layer solution algorithm for multi solution tasks are proposed. Finally, based on the constructed model and algorithm, calculations and analyses are conducted on the long-term power structure, electricity balance, new energy consumption, energy storage configuration, etc., and a path for achieving carbon neutrality in China′s power industry is proposed.