DECREASING NO_x EMISSIONS IN WALL-FIRED BOILERS THROUGH INTELLIGENT COMBUSTION OPTIMIZATION

摘要

In the current market conditions, steam power plants must always be run at the most profitable operating point. This primarily demands low emissions and the most cost efficient way to minimize emissions is to optimize the combustion process. The Siemens SPPA-P3000 process optimization solutions allow plant operators to achieve these objectives. This paper describes an online robust Combustion Optimization methodology used at LaCygne Unit 2 power plant of Kansas City Power and Light (KCPL) to significantly reduce NO_x emissions on a 30-plus-year-old 720 MW B & W wall-fired boiler firing 100 percent Powder River Basin coal. The Siemens SPPA-P3000 Combustion Optimization solutions were employed on the boiler without over-fired air by utilizing the existing combustion equipment, existing combustion controls system, and a new in-furnace laser based combustion monitoring system. The Combustion Optimizer provides closed-loop optimization of fuel and air combination by maneuvering the appropriate fuel and air flows in the furnace. This paper elaborates the hybrid of model based controls with neural network optimization technology, its implementation and operational results.