Intelligent Prediction and Experimental Study on Deep Peak-Regulation Capability of Thermal Power Units

Abstract

The rapid increase in renewable energy has put forward higher requirements for the peak-shaving capacity of coal-fired power plants. Intelligent prediction of the deep peak-regulating capacity of thermal power units can effectively explore the peak-regulating potential of the units. The ultra-low load steady combustion experiment is an effective verification of the minimum steady combustion load of the units, and also an important basis for evaluating the deep peak-regulating capacity. In this study, an intelligent prediction method combining numerical combustion simulation with hydrodynamic safety calculation is proposed to adapt to peak regulating requirements. The intelligent prediction method is used to predict that the 300MW boiler can be reduced to 25% turbine heat acceptance (THA) load and stable combustion in actual operation, the results are verified by the field low-load stable combustion experiment. The results show that: The method is used during the declining load include leveling deviation of primary air velocity and reducing the primary air velocity appropriately, commissioning adjacent burners, closing the perimeter air, reducing the operating oxygen volume while reducing the secondary air volume is beneficial to improve the low load stable combustion ability. At the same time, the main and auxiliary systems of the boiler are stable, safe, environmentally friendly, and have strong operation guarantee ability.