Creating an Advanced Sensor Network to calculate real-time, mass-weighted flue gas composition and air heater leakage of a coal-fired utility boiler under dynamic operating conditions

Utilization of renewable energy sources to minimize the environmental impact of energy production has changed the way utility boilers operate, requiring frequent load cycling between full load and partial loads as low as 30%. Dynamic operation of coal-fired utility boilers significantly reduces boiler efficiency when compared to steady state at full load. Data-driven plant optimization has shown success with coal-fired utility boilers under dynamic operating conditions. The purpose of this work was to create an Advanced Sensor Network (ASN) to provide more extensive real-time data to inform dynamic plant optimization of Net Unit Heat Rate (NUHR). The ASN consists of gas sampling grids in the convective pass of the boiler and downstream of the air heater. These sampling grids allow for quantification of spatial variation of flue gas within the boiler and calculation of massweighted composition of flue gas through the combination of composition, velocity, and temperature measurements. The comparison of O2 between the inlet and outlet of the air heater is used to calculate air leakage in real time. Flue gas composition and air heater leakage are both important factors in boiler efficiency and NUHR. The results of this work support the value of mass-weighted averages for determining flue gas composition accurately. The measurements from the ASN show increased composition stratification during dynamic operation, with an average standard deviation 38% higher than observed during steadystate operation. Air heater leakage was also observed to increase from 2.8% to 5.1% following a load change. Prior to the installation of the ASN, these data would not have been available for dynamic control. These real-time data will be leveraged to calculate and optimize for NUHR during dynamic operation in future work.

Automated summary

The study focuses on creating an Advanced Sensor Network (ASN) to optimize the dynamic operation of coal-fired utility boilers, aiming to improve boiler efficiency and minimize environmental impact. The ASN provides real-time data on flue gas composition and air leakage, which are crucial for boiler optimization during dynamic operation.