PEMS solution for offshore platforms

Emerging legislation will soon require European offshore operators to monitor and report gas turbine emissions, with numerous other countries expected to follow suit. In the past, offshore platforms relied primarily on tem¬porary instrumentation to perform as-needed emissions estimates. However, this approach lacks the necessary models to extend results to other operating regimes and ambient conditions. As such, there are today only two viable options for compliance with regulations requiring higher accuracy: a Continuous Emissions Monitoring System (CEMS) or a Predictive Emissions Monitoring System (PEMS).
While a CEMS affords many advantages, including continuous and direct measurement of emissions, its capabilities may exceed the requirements of offshore operators.
A PEMS approach, in contrast, can approach the accuracy of a CEMS for as little as one-third the cost while adequately meeting the specific needs of offshore operators. Fortunately, such a PEMS solution is now available for the large installed base of GE LM2500 SAC aeroderivative gas turbines used in offshore service, and is easily extensible to LM6000 SAC units.
GE’s PEMS solution is implemented in System 1 software and requires the following: System 1 software, version 5.x or later; Bently PERFORMANCE System Extender module; PEMS configuration, tuning, and installation services.
The PEMS module employs a GE-developed “first principles” emissions model for the LM2500 SAC gas turbine. This physics-based model uses fundamental engine parameters and conditions known to correlate to emissions output, drawing on extensive test results from the large installed base of LM2500 SAC units. It uses ambient conditions, various turbine operating param¬eters, and fuel properties as inputs and is valid for both gas and diesel fuels. The model computes emissions estimates for NOX, CO, and unburned hydrocarbons, while providing calculated values for CO2 and SO2. A calibration feature allows customization to a specific installation along with post-installation refinement of model outputs based on tuning adjustments derived from temporary CEMS and corresponding turbine data sets.