Virtual Instrumentation Monitors Arkansas Emissions

Arkansas Electric Cooperative Says Software Sensors Are Just as Good as Hardware Sensors, With Less Maintenance and Fewer Headaches

By Walt Boyes

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Arkansas Electric Cooperative Corp. (AECC), like most companies today, must meet stringent regulatory standards for environmental quality with a continuous emissions monitoring system (CEMS) that provides reliable and accurate data.

"Our Henry L. Oswald Generating Facility has hardware-based CEM monitors that are reaching their retirement time," says Tim Bivens, senior environmental analyst with AECC. "We had to consider doing a rip and replace, or do something else."

Bivens describes the facility: "The Oswald Generating Station is a 510-megawatt (MW), combined-cycle, natural gas combustion turbine plant located in Pulaski County, 0.5 miles south of Wrightsville, Ark. The plant (Figure 1) consists of six GE LM6000 aeroderivative combustion turbines, one GE Electric Frame 7EA combustion turbine, seven duct burners and two steam turbines. The plant configuration is commonly known as a 'Seven on Two.' "

"This means the seven combustion turbines (CTs), or fewer, provide steam to one or both steam turbines, depending on the current power demand. The plant is not configured for the CTs to operate in simple cycle mode," Bivens explained.

He continues, "The plant is designed to supply approximately 75 MW to 510 MW of power during high electrical demand hours of each day, usually between the hours of 7:00 a.m. and 11:00 p.m., and ramp down to approximately 75 MW during off-peak hours. This daily load cycling results in reduced power production each day during hours when there is less demand for the power."

The six LM combustion turbines are equipped with steam injection for emission control of oxides of nitrogen (NOx). The Title V Air Permit limits the six LMs to a three- hour rolling average of 25 ppm and a yearly average of 22 ppm NOx corrected to 15% oxygen (O2). The 7EA combustion turbine utilizes dry low NOX (DLN) burners for NOx control. The 7EA is limited to a three-hour rolling average of 9 ppm NOx corrected to 15% O2.

 The facility currently operates and maintains seven CEMS that are subject to the Acid Rain Program under 40 CFR Part 75 and the Clean Air Interstate Rule (CAIR) for the NOx ozone season trading program. Each system is comprised of an O2 monitor and a NOx monitor. The emissions are monitored every minute, and the data is passed to the existing, common data acquisition handling system (DAHS), which calculates the hourly emissions for each CT. Each calendar quarter the NOx (lbs/mmBtu) and other plant data are electronically reported to the U.S. Environmental Protection Agency (EPA). The CEMS undergo a calibration check each operating day, linearity checks each quality-assured (QA) quarter and an annual relative accuracy test audit (RATA).

Rip and Replace or Do Something Else

The CEM analyzers that monitor emissions on Oswald's seven multi-stage gas turbines needed replacement. They were elderly and obsolete. "Our options," Bivens says, "were to either replace the analyzers with new analyzers or replace the hardware-based CEMS with an alternate solution. Replacing the hardware-based system with new hardware was going to be very expensive."

Fortunately, Bivens says, one of his colleagues had worked with Pavilion's software-based CEMS at another facility, and knew about it. On his recommendation, AECC contacted Rockwell Automation, which had acquired Pavilion, and asked for a proposal.

"Software CEM is a model-based, predictive emissions monitoring system (PEMS) powered by the Pavilion8 software engine," says Joseph Miller, technical consultant with Rockwell Automation. "It uses powerful hybrid models of the process with real-time sensor validation to provide predictive emissions values."

Software CEM operates in real time using existing process sensor data. These process values enable the plant to monitor operating conditions that could affect final emissions output. Software CEM uses a patented sensor validation system as a qualifier to detect sensor failures and set appropriate alarms. The system uses existing sensors to generate a model of all sensors in the process. This allows data validation to continue accurate emissions predictions during a sensor failure, providing for near 100% uptime. This predictive methodology also gives AECC the ability to simultaneously incorporate process behavior and feedback into the control strategy of its gas turbines.

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