Research on Optimization Method of Coal Blending for Carbon Emission Reduction Based on Bi-level Programming

Abstract

As the “dual carbon” goal has been upgraded to a national strategy, coal-fired power plants are the top priority for carbon reduction in the power generation industry, and coal-fired power plants are facing a huge challenge in limiting carbon emissions. Using the method of bi-level programming model, this paper established a low-carbon coal blending optimization model for thermal power units by considering the combination of carbon emission quotas for regulatory agencies and coal blending in power plants. The upper layer is the goal of the government management department, which seeks to minimize the cost of emission reduction of power plants under the given total carbon emissions. The lower layer is the goal of the power plant sector, pursuing the minimization of coal blending cost and carbon emission cost. The chaotic particle swarm optimization (CPSO) algorithm was used to solve the model. The calculation provides a certain reference for the allocation of carbon emission quotas for regulatory agencies and coal blending for power plant operators, and has good application value and guiding role.

Keywords

• carbon emission quota
• bi-level programming model
• coal blending optimization
• chaotic particle swarm optimization (cpso) algorithm