Combine Heat Balance with Data Analytics to Monitor and Detect Changes in Performance
Plant measured data is continuously monitored and evaluated using a combination of first-principles, heat-balance analysis and advanced data analytics. Monitoring output can be stored in plant historian and displayed graphically for operational review.
Heat balance analysis applies conservation of mass and energy plus combustion modeling to add information to the measured data. No assumptions about performance are needed. The heat balance outputs all temperatures and flows in the system from which equipment efficiencies and heat rates are calculated.
The most common problem in heat balance analysis is that plant data contains measurement and calibrations error. MapEx has the flexibility to use least-squared fitting to detect and resolve inconsistencies in the data and produce heat balance output (red line) that is more accurate than the individual measurements (blue dots).
Performance is evaluated by comparing expected performance current performance. Expected performance can be predicted using correction curves, correlations from regression fitting or advanced pattern recognition.
If a performance parameter is dependent upon several other variables, a correlation can predict it expected values. For example, gas turbine power at part-load may be a function of air temperature, inlet pressure, IGV, and turbine inlet temperature. Correlation accuracy ban be improved by using heat balance outputs as inputs.
Power plant performance monitoring continuously tracks the difference between observed (measured values or calculated values from heat balance) behavior and expected behavior. Advanced pattern recognition is the most flexible and accurate technology for prediction of the expected values of performance parameters.
New products are coming soon!