A real-time phase transition modeling of supercritical steam cycle and load variation rate enhancement of thermal power plants under deep peak shaving

The ambitious green revolution to renewable energy sources in global power grids necessitates massive integration of solar and wind energy, which involves intermittent and unpredictable challenges. Thermal power plants are crucial in stabilizing the grid and addressing these challenges through flexibility reformation including deep peak shaving and frequent load variations since the unsteady state energy transfer and thermal dynamics during combustion and heat transformation in thermodynamic processes vary significantly. These conditions lead to issues such as furnace instability and latent heat of phase transition. This study introduces a novel approach to modeling phase transitions of supercritical steam cycle, and investigatesthe length, position, temperature, and energy transfer of the working medium and components under normal and low operational states. Conducting and analyzing the thermal feasible region associating the security of components and working medium this study establishes a control strategy for dynamic heat transfer to reduce component degradation effects andenhance load variation rate under flexible operations. Simulation model of a supercritical power unit based on the proposed method demonstrates an accuracy of 97.94%. Results from the optimal approach in maximizing load variation rate show the effectiveness and achieve 1.2%p.e./min most under transition process.