Proven Data Validation and Reconciliation Techniques That Improve Performance
Series: Optimizing Plant Performance
Time: 12:30 PM – 1:15 PM CT
The measured process data from an operating power plant is used to make operational, maintenance, and business decisions. It is important that the information used for these decisions is accurate, however this measurement data can often contain significant bias error and can result in ambiguity. Traditional monitoring methods do not account for this error, and therefore new methods are being implemented to improve the quality of power plant data – Data Validation and Reconciliation, or DVR.
Data Validation and Reconciliation applies statistical and first-order principles, to:
- Identify Faulty Sensors – Reducing maintenance costs by only working components that need to be worked
- Optimize Output – By identifying error in existing instruments and correcting that indication
- Robust Analysis – Providing psudo measurements with the uncertainty of those measurements to compensate for missing instruments
- Recover Power – By identifying losses typically not found by component monitoring
The potential benefits of using DVR for performance monitoring extends across the entire power industry. DVR has been used in nuclear plants to implement power recovery efforts on units suffering from degraded feedwater flow measurements. Significant bias error has been identified in the coal flow measurement at a fossil plant through DVR modeling. All plants can benefit from the improved accuracy for calculated heat rates that DVR provides.
See how the utility industry is using the latest thermal system monitoring software and data reconciliation technology to provide powerful and unique analytics modules to simplify and provide timesaving, convenient methods of tracking thermal performance in nuclear, fossil and combined-cycle plant applications.
Greg Kanuckel, Thermal Performance Engineering Manager at GSE TrueNorth (A division of GSE Solutions)