Low Carbon Scheduling of Thermal Power Unit Thermal Storage Capacity Based on Particle Swarm Optimization

A novel low carbon scheduling method for thermal power unit storage capacity is introduced to address the limitations of traditional approaches. By employing a particle swarm optimization algorithm, this method optimizes the scheduling of thermal storage capacity while considering the operational characteristics of the thermal power units. Through an analysis of the unit's pressure parameters, capacity level, and fuel type, different carbon emission allowances are allocated to each unit based on a baseline. The operation mechanism of the heat storage device is then optimized. The proposed low carbon scheduling model is effectively solved using the particle swarm optimization algorithm. Experimental analysis demonstrates the favorable scheduling performance of this method for thermal power units, highlighting its potential for reducing carbon emissions and achieving efficient operations.