System 1 PEMS

Overview

The System 1® Predictive Emissions Monitoring System (PEMS) can predict the level of stack emissions generated by combustion equipment.

Predictive Emissions Monitoring System

System-1-PEMSThe System 1® Predictive Emissions Monitoring System (PEMS) offered as part of GE’s Bently Nevada product suite can predict the level of stack emissions generated by combustion equipment (typically gas turbines) based on ambient conditions, fuel composition and machine operating conditions while taking into account real time degradations.

Emissions models are developed using GE’s knowledge of aeroderivative and industrial gas turbines combining fundamental physics and real emissions test data. The resulting model can be tuned using periodic data from temporarily installed emissions monitoring system for continued or improved accuracy.

Features

PEMS Value

Lower Cost of Regulatory Compliance

PEMS reduces initial installation and operating costs compared to a CEMS solution. The installed cost of PEMS can be one third the cost of a permanently mounted CEMS emissions monitoring solution that achieves similar accuracy.

Local and Remote Access

The PEMS and System 1® Display client server can be installed anywhere (i.e. on or off platform) that has access to the required data. System maintenance, configuration and calibration updates do not require GE visits to site and help to keep PEMS annual costs low.

Emissions Credits Trading

Emissions’ trading is an administrative approach used to control pollution by providing economic incentives for achieving reductions in the emissions of pollutants. Companies are issued allocations for a specific amount of emissions per year. They are required to purchase additional allocation if their emissions exceed their limits. Likewise they can sell allocation if their emissions are lower than their allotment. Meaningful emission reductions within a trading system can only occur if they can be measured with sufficient accuracy based on live plant operational data. Therefore, emissions’ trading is predicted on accurate estimation of past and future emissions.