Data collection

of periodic testing, a performance engineer can implement daily or weekly performance monitoring if the on-line thermal performance monitoring system is available. The continuous performance analysis starts with comparing current values with reference values of the plant’s thermal performance parameters.

3.2.3. Pre and post outage test

Typically, the performance test is implemented within 30 days before and after the outage of each cycle in order to overlook the change of thermal performance index and performance history at each component equipment in the turbine cycle. The TPE or a dedicated staff member in charge of plant’s efficiency analyses the test result and reports to the plant manager. Then it is registered to plant archives for the purpose of the plant’s thermal performance management.

3.2.4. Pre and post modification test

As a part of periodic test, the plant’s performance monitoring is conducted prior to and immediately following outages when key component equipment is repaired or modified. Such facilities are SG, HP, LP, MSR, and condenser, which directly affect the output of the turbine cycle. Particularly, this test results need to be reflected on the design factors of plant’s on-line thermal performance monitoring system.

3.3. INPUT DATA

3.3.1. Benchmarking (baselining data) acquisition

In order to know as much as possible about the thermal performance of an NPP at a given time, it is recommended to characterize the state of the plant. This data need to be acquired as close as possible to the moment at which one wishes to evaluate plant performance.

This data is used either to define the operating conditions of the plant at a given time (boundary conditions), or to compare with expected parameters at different points of the plant. The measured parameters are pressure (approx. between 0.02 bar and 95 bar), temperature (approx.

between 0 °C and 300 °C), flow rate (approx. between 0 and 33 000 kg/s) and electrical power.

The reliability of the data is very important to the process, performance monitoring is nearly impossible without reliable data. Inaccurate or unrepresentative data can lead to errors in diagnosis, discredit the process and undermine efforts made, including the development of reference models or the establishment of a specific organization. Therefore, substantial effort needs to be made regarding determining and acquiring input data.

3.3.2. Data collection

3.3.2.1. Instrumentation (location, type, etc.)

Although the more sensors one has, the more components that can be monitored, not all components have a significant impact on plant efficiency. For example, the performance of the first stage, low pressure secondary feed-water heaters (located after the condenser) has little impact on overall thermal efficiency.

A choice needs to be made to monitor only those components for which the instrumentation is a worthwhile investment. In some cases, instrumentation is based more on reliability than efficiency monitoring.

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A greater number of sensors allows for cross-checking between measurements, thereby increasing one’s confidence in the reliability of the measurements. Again, an optimum balance needs to be found between the reliability of the monitoring and the cost of installing the sensors.

The more reliable the sensors and acquisition systems are, the faster performance drifts can be identified. Thus, the accuracy of the selected sensors needs to be optimized according to the detection threshold needed.

A cost-effective approach is to focus on high energy components: the high-pressure stage of the turbine, the MSR, the condensers, the high-pressure heaters, and the cooling towers.

Following this approach, it is possible to achieve gains of 2 to 5 MWe for units producing approx. 1000 MWe.

For these systems, a second level of optimization is possible by reinforcing the instrumentation in order to concentrate on the largest performance losses and instrumenting less the parameters which have a smaller impact. For instance, for high pressure heaters, it is preferable to instrument the flow of each drain line, since the failure of a high-pressure heater can rapidly lead to a loss of several MWe.

Some power plants do not measure the steam pressure in each high-pressure heater. Instead they use the existing pressure gauge on each turbine bled steam line and estimate the shell pressure in the heater. This means, however, that the pressure drop between the measured pressure and the desired information becomes a fixed estimate. The true pressure in the shell may be different due to changes in the pressure drop related to flow and specific volume. There is therefore a risk that the estimated pressure in the heaters is incorrect and over time may lead to unreliability in the efficiency monitoring of the heaters.

With regards to the condenser, instrumentation is focused on the measurement of the vacuum.

Between four and six sensors are needed to ensure a good representation of the vacuum. In this case, cross-checking is enabled and ensures a reliable vacuum value.

A final example can be given concerning the monitoring of cooling towers. The air temperature is a key parameter of the tower’s performance. EDF test standards prescribe the use of precise instrumentation in the air intake (about 20 sensors). For reliable monitoring, three or four sensors are enough to allow cross-checks of measurements. In Figure 12 below, a thermal model with sensors is shown. This figure serves only illustrative purposes (indicating the level of detail related to data collection).

The sensors and acquisition systems to be used for performance monitoring need to have a reliability comparable to the one required by international standards dedicated to thermal performance. Some examples of these standards are as follow:

NF-EN-60953-2 (Turbine) [6];

NF E38-350 (Condensers) [7];

ISO 16345 (Cooling towers) [8];

ASME Performance Test Code series for all turbine cycle equipment.

35 FIG. 12. Thermal model (with sensors)

3.3.2.2. Measurement (calibration, uncertainty, alternate measurement etc.)

As mentioned above, the reliability required is the one defined in international standards dedicated to thermal performance acceptance tests. Since thermal performance needs to be monitored over time, regular calibration is required. Suggested calibration frequencies are provided below:

 Vacuum sensors – yearly;

 Differential pressure sensors for flow – yearly;

 Pressure sensors – two years;

 Temperature sensors – could be as much as three or four years;

Plant installation guidelines for these sensors need to be respected. Special attention needs to be paid to the installation of instrument lines on let-down lines.

3.3.2.3. Data acquisition system (Computer, PI, etc.)

The acquisition system’s accuracy is again based on international standards. For each measured parameter, the overall uncertainty (consider the uncertainty of the sensors) and that of the acquisition system need to remain within the limits imposed by the standards.

Since we need to monitor thermal performance over time, it is necessary to guarantee the reliability of the data acquisition system in the long term. Various interventions are expected in time, for instance:

 Modification of calibration coefficients of sensors;

 Replacement of a faulty sensor;

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 Repair of degraded wiring.

In addition, long term performance monitoring requires the ability to guarantee consistent data over time.

For all these reasons, it is best to focus on a permanent acquisition system, connected to a dedicated computer whose reference configuration can only be modified by certain users. This methodology will help guarantee the quality of the input data over time.

In some cases, it may be useful to have a modular acquisition system to which you can easily add new sensors. This makes it possible to progressively complete the instrumentation in place with special instrumentation.

3.3.2.4. Special instrument (ultrasonic, infrared, etc.) Additional special instrumentation can be put in place to:

 Provide complementary measurements to cross-check existing measurements and improve the precision of measurements.

 Confirm a diagnosis performed with the existing instrumentation.

 Validate hypothetical models used in the performance monitoring tool.

 Carry out hard-to-implement monitoring dedicated to specific components (e.g. valves) and encourage the involvement of operators in performance monitoring.

This special instrumentation is generally set up for a limited period only. Various types of complementary instrumentation are used (sometimes it is the same kind of instrumentation as the permanent instrumentation):

 Ultrasonic flow measurement devices (for instance to check the division of flow between parallel heaters);

 Infrared (IR) thermometers (for instance to monitor valve leaks);

 Flow measurement via dilution rates (for an accurate, independent flow measure).

3.3.2.5. Manual reading (heater level, cooling water pressure drop, etc.)

The instrumentation proposed above is the basis for performance monitoring. When performance drifts are detected from these measurements, it may be useful to have additional information to confirm the diagnosis. This additional information comes from manual records made by an operator in the field.

This information can be:

 The water level in the heaters;

 The temperature of the pipes downstream of the floodgates (obtained via an IR thermometer).

For maximum reliability, it is very important that these manual records be made the same way, week after week. It is recommended, that the manual records are not dependant on the operator who performs them; only then can the records be used to complete the other measures already available.

37 In order to ensure the best possible reproducibility of these manual records, a procedure describing in detail each step of the ‘performance sweep’ is to be followed by the operator. It describes all the measures that are to be manually recorded, the exact location of the measurement points, and how to correctly perform the measurement.