JPS624526B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to performance monitoring techniques for steam-powered power plants.

First, an outline of a conventional performance monitoring device for a steam turbine plant will be explained.

In FIG. 1, the cycle configuration of the plant will first be explained. Steam generated in the boiler 7 passes through the main steam pipe and enters the high pressure turbine 1.

The steam that has completed its work in the high pressure turbine 1 is
It passes through the low-temperature reheat pipe and returns to the boiler 7 again. This steam is reheated in the boiler and enters the low pressure turbine 2 through a high temperature reheat pipe.

The work performed by the steam in the high-pressure and low-pressure turbines is converted into electrical energy in the generator 3. Exhaust steam from the low pressure turbine is transferred to condenser 4
The water is reduced to water by the water supply pump 5, and the boiler 7
is supplied with water. In order to improve plant efficiency, a feed water heater 6 is generally installed in this water supply system, and the feed water is heated by extraction air from the high pressure turbine 1.

Drain from the feed water heater 6 is collected into the condenser 4. The above is an example of a plant cycle configuration.

As shown in FIG. 1, the conventional performance monitoring device inputs each data signal from the pressure detection device 9, temperature detection device 10, output detection device 11, and flow rate detection device 12 to the heat rate calculation device 8. ,
This allows you to calculate the heat rate.

FIG. 2 shows a flowchart of a conventional performance monitoring device.

As shown in FIG. 2, in the data detection process 14, data is detected at fixed time intervals, and the detected data is sequentially processed in the data averaging and integration calculation process 15, and the calculation results are stored in a storage area 16 in the computer. be done. In addition, in the detection duration check step 17, the detection duration time is compared with the bogey value (set value), and if the detection duration time is less than the bogey value, the process returns to the initial data detection step 14 and the above-mentioned process is performed. Execute again.

If the detection duration satisfies the bogey value, the process proceeds to the next performance calculation step 18.

In a performance calculation step 18, performance calculation is performed based on the data in the storage area 16, and in a display step 19, the calculation results and detected data are displayed by printing out or the like.

After completing the display process 19, return to the detection process 14,
The steps from the detection process 14 to the display process 19 are repeatedly executed.

The above is an example of the configuration of a conventional performance monitoring device. Conventional performance monitoring devices input detected operating status values (pressure, temperature, flow rate, electrical output, etc.) into a computer regardless of the load fluctuation status of the plant. , perform performance calculations, and write daily power generation reports, etc. for 30 minutes or 1 hour.
Depending on the time interval or operator request, the simple average performance within that time period is printed out.

In this case, if the plant load is stable over a long period of time, accurate performance calculations can be expected, but if the load fluctuates rapidly, the performance calculation results printed out will vary widely and This has the disadvantage of being an unrealistic value, and the performance calculation results may be meaningless to the user.

In addition, performance data measured under stable load conditions
This will be mixed with the performance data of the load fluctuation state, and it will not be easy to distinguish this later, so the reliability of all the data will be weakened, and the performance monitoring device may not be able to fulfill its function.

In addition, if the detection device etc. operates normally and accurate operating state values are input into the computer, accurate performance calculations can be expected. If the input data is not checked constantly and abnormal values are included in the input data due to instrument failure, disconnection, aging of the detection device, etc., the performance calculation results printed out may be meaningless. are doing.

In addition, the detected operating status values, that is, the input data, change due to the aging of plant equipment over a long period of time, but in conventional turbine plant performance calculations, this aging of the plant is not taken into account at all. When a change occurs in the data, it is not possible to determine whether the change indicates an abnormal value due to equipment failure or a value based on aging of the plant, and therefore performance calculations are not performed based on these detected values. Therefore, it could not be said that it was fully functioning as a performance monitoring device. Furthermore, it has been impossible to establish guidelines for plant maintenance items and timing because the aging status of the plant is unknown.

The purpose of the present invention is to accurately calculate performance by distinguishing between a stable state and a fluctuating state of plant load, and to check the validity of detected plant operating state values (pressure, flow rate, temperature, electrical output, etc.). An object of the present invention is to provide a method for monitoring the performance of a steam power plant, which makes it possible to perform performance calculations and monitor changes in plant performance over time.

The feature of the present invention is to distinguish between a stable state and a fluctuating state of the plant load, and when the load fluctuation range is within a specified value and continues for more than a specified time,
The data of the operating status values measured within that time is judged to be effective for performance monitoring, and the performance is calculated.
In order to check the validity of detected operating status values (pressure, flow rate, temperature, electrical output, etc.), the operating status value is compared with the set value (bogie value), and the change rate (deviation) of the operating status value with respect to the bogie value is calculated. value) is within the specified value, the detected operating state value is judged to be effective for performance monitoring and the performance is calculated, and the operating state value of each part of the plant is further detected to calculate the plant heat consumption rate. The plant heat consumption rate, the influence of each plant equipment on the plant heat consumption rate, and the detected data are stored in a storage device at regular intervals, and the stored past data is stored periodically or upon operator request. The present invention provides a method for monitoring the performance of a steam power plant that enables monitoring and diagnosis of changes over time in the entire plant and plant equipment using a function that compares data with data (long-term data).

Next, a method for monitoring the performance of a steam turbine plant, which is an embodiment of the present invention, will be described with reference to the drawings. In Fig. 3, the cycle configuration of the plant is the same as that shown in Fig. 1, so the explanation will be omitted, and the equipment for performance monitoring will be explained as follows.
The plurality of pressure detection devices 9 detect main steam pressure P ₁ , high temperature reheat steam pressure P ₂ , low temperature reheat steam pressure P ₃ , feed water heater outlet pressure P ₄ , feed water heater inlet pressure P ₅ , and extraction pressure P ₆ and the feed water heater drain pressure P ₇ are detected and input to the determination device 21 . Further, the plurality of temperature detection devices 10 detect main steam temperatures T ₁ , T ₁ ′, high temperature reheat steam temperatures T ₂ , T ₂ ′, low temperature reheat steam temperatures T ₃ ,
T ₃ ′, bleed air temperature T ₆ , feed water heater inlet temperature T ₅ , feed water heater outlet temperature T ₄ , T ₄ ′, feed water heater drain temperature
T ₇ , condenser inlet seawater temperature T ₈ , and condenser outlet seawater temperature T ₉ are detected and input to the determination device 21 .

In addition, the output detection device 11 detects the generator output L.
, the water supply flow rate to the boiler 7 (main water supply flow rate F ₀ ) and the condenser inlet seawater flow rate Fc are detected by the plurality of flow rate detection devices 12, and the condenser inlet seawater flow rate Fc is detected by the vacuum degree detection device 9'. Detect the degree of vacuum V.

These detection data are input to a determination device 21 to determine the validity of the data. Furthermore, the detection data of the generator output L is also input to the load stable state and duration determination device 20, and if the determination result there is that the plant load is in a stable state, the above-mentioned detection data is input to the determination device 20. 21 will be input. The detection data determined to be valid by the determination device 21 is input to the heat rate calculation device 8 to calculate the heat rate, and is also input to the equipment performance calculation device 22, and then the calculated data is used to calculate the steam power. The information is input to a plant performance diagnosis device 23 and a steam power plant performance analysis device 24, where diagnosis and analysis are performed.

These processes will be explained with reference to FIG.

In FIG. 4, among the data of the operating state values detected by each of the detection devices 9 to 12, the output L and detection time M data detected by the output detection device 11 and the detection time detection device 25 are in the load stable state and It is input to the duration determination device 20. When the OK signal from the determination device 20, that is, the plant load is determined to be in a stable state, each detection data is input to the determination device 21. The detection data determined to be valid by the determination device 21 is processed by the next average value calculation device 2.
6, and the average value of each detected data is calculated.

Here, load stable state and load stable state duration determination device 20 and input data validity determination device 2
1 will be explained in detail.

FIG. 5 shows a detailed control block diagram of the load stable state and load stable state duration determination device 20. As shown in FIG.

In this figure, the first detection data L ₁ , M ₁ of the load and load stable state duration are the converter 31,
36, the initial setting values L ₀ and M ₀ are converted, and the setters 32 and 37 set the bogie values L ₀ and M ₀ .

The second and subsequent detection data L _{2 -N} , M _{2 -N} are input to the computing units 33 and 38, and the output data X _{2 -N}
performs the deviation calculation from the bogey value L ₀ . That is, L2 _~N - _L0 / _L0 =X2 _~N , and the plant load variation rate X2 _~N per unit time is calculated.

The fluctuation ratios X _{2 to N} are input to the comparator 35 and are the fluctuation ratio bogey values X ₀ stored in the setter 34.
The comparison result is input to the determiner 41.

On the other hand, the detection time data M _{2 to N} are bogey values M ₀
Accordingly, the calculation M2 _~N - _M0 =Y2 _~N is executed to obtain the detection duration Y2 _~N .

The duration Y _{2 to N} are the duration bogey values Y ₀ that are input to the comparator 40 and stored in the setter 39.
The comparison result is input to the determiner 41.

This _determiner 41 determines whether _the plant load _variation ratio (load variation _width ) It is something to do.

In other words, if the load fluctuation range X2 _~N is within the bogey value, an OK signal is output, each detected data is input to the input data validity determination device 21, and the process up to the next average calculation device 26 is monitored. possible.

However, the subsequent process, that is, performance calculation, is executed only when the detection duration Y2 _{to N} is greater than or equal to the bogey value _Y0 .

This is to determine that detection data when the plant load stable state continues to be equal to or greater than a specified value is valid for performance calculation.

FIG. 6 shows a detailed control block diagram of the input data validity determining device 21.

In this figure, input data validity determination device 21
The data of pressure P, temperature T, and flow rate F inputted to the classifier 43 are input, and the data of the output L is input to the calculators 44 and 61.

First, regarding the output data L, the arithmetic unit 44,
In step 61, a reference bogey value is calculated in order to determine the validity of the detected data. That is, as shown in FIG. 7, for each detected data, the relationship between the bogie value and the plant load is stored in advance, and by inputting the output data, an intersection point is found on this graph, and the bogey value at that time is set in the setting device 4.
5 and 62 as the reference bogey value.

On the other hand, the classifier 43 classifies each detected data based on the number of input points (multiple detections of the same type of data).

In the case of two input points, the detected data of the two points are used to calculate the deviation from the reference bogey value in the arithmetic unit 46. That is, if the detection data are A ₁ and A ₂ and the reference bogey value set in the setter 45 is A ₀ , |1-A ₁ /A ₀ |=x ₁ , |1-A ₂ /A ₀ | = x ₂ , and the calculation results x ₁ and x ₂ are the comparator 4
7, a comparison is made with the deviation bogey value x ₀ stored in the storage unit 49, and the process proceeds to the determiner 48.

In the determiner 48, if both the deviation values x ₁ and x ₂ are smaller than the deviation bogey value x ₀ , the detected data A ₁ and A ₂ are determined as valid data and are passed to the computing unit 51.
Otherwise, the process proceeds to comparator 50.

The calculator 51 calculates the average value of the detection data A ₁ and A ₂ , and the average value is inputted to the average value calculation device 26 by the setting device 52 as a representative value of the detection data A ₁ and A ₂ . .

Similar to the comparator 47, the comparator 50 performs a comparison with a reference bogey value and inputs the comparison result to the determiner 53. In the determiner 53, if either one of the deviation values x ₁ and x ₂ is smaller than the deviation bogey value x ₀ , one of the detected data A ₁ and A ₂ is determined as valid data and the setter 55 Otherwise, the process proceeds to the setting device 54.

The setter 55 sets the detection data smaller than the deviation bogey value x ₀ between the deviation values x ₁ and x ₂ as a representative value, and proceeds to the next step.

When proceeding to the setting device 54, the detection data
Both A ₁ and A ₂ are determined to be abnormal data, and both A ₁ and A ₂ are invalid for performance calculation. Therefore, the reference bogey value set by the setting device 45 is set as a representative value, and the process proceeds to the next step.

In the case of one input point, if the detection data is B ₁ and the reference bogey value set by the setting device 62 is B ₀ , the calculation unit 56 executes the calculation |1-B ₁ /B ₀ |=y _1. Then, find the deviation value y ₁ , and compare it with comparator 5.
Proceed to step 7.

The comparator 57 performs a comparison with the deviation bogey value y ₀ stored in the storage 63.

The comparison result is input to the determiner 58, and the deviation value y ₁
is smaller than the deviation bogey value y ₀ , the detection data B ₁
is input to the setting device 59 as valid data. Otherwise, the detection data _B1 is
This is input to the setting device 60 as abnormal data.

The setting device 59 sets the detection data _B1 as data valid for performance calculation, and proceeds to the next step.

The setting device 60 sets the reference bogey value B ₀ as valid data instead of the detection data B ₁ and proceeds to the next step.

In the setting devices 54, 55, 59, and 60, each set data is input to the average value calculation device 26, which calculates the average value and inputs an OK signal from the load stable state and duration determination device 20. Wait until. That is, the determination device 20 outputs a command to start performance calculation when the plant load stable state duration time exceeds a specified value. In this case, if the plant load fluctuates before the stable load state continues to exceed the specified value, all data collected during that period will be treated as invalid data.

In response to the OK signal from the determination device 20, the average value of each data in the average value calculation device 26 proceeds to the next process.

As shown in FIG. 8, the enthalpy calculating device 27 calculates a graph (Mollier diagram) in which the vertical axis is enthalpy and the horizontal axis is entropy, using the average value data of pressures P _{1 to 7} and temperatures T _{1 to 7} . Find the intersection and find the enthalpy H from the intersection. The enthalpy data H _{1 to H 7} are input to the flow rate calculation device 28 and the heat rate calculation device 8 .

The flow rate calculation device 28 is formed of flow rate calculation units 65, 66, and 67, as shown in FIG.
That is, when the plant cycle has the configuration shown in FIG. 3, the main steam flow rate F ₀ and the main steam flow rate F ₁ are equal in the main steam flow rate calculator 65, and the main steam flow rate F ₁ is calculated from F ₁ =F ₀ . Proceed to the next process.

The low-temperature reheat steam flow rate calculator 66 calculates the relationship between the main steam flow rate F ₁ and the extracted steam F ₄ , that is, F ₃ =F ₁ −F ₄ =F ₁ −F ₁ (H ₄ −H ₅ )/H ₆ − From _H7 , determine the low temperature reheat steam flow rate _F3 and proceed to the next step. In the high temperature reheat steam flow rate calculator 67, the high temperature reheat steam flow rate F ₂ is equal to the low temperature reheat steam flow rate F ₃ , and from F ₂ = F ₃ , the high temperature reheat steam flow rate F ₂ is calculated and used in the next process. move on. The above flow rate data F0 _{to F3} , output data L, and enthalpy data 64 are input to the heat rate calculation device 8, and the heat rate HR is determined by the following equation.

HR =F ₁・H ₁ −F ₀・H ₄ +F ₂・H ₂ −F ₃・H ₃
/L The determined heat rate 69 is input to the corrected heat rate calculation device 30.

In FIG. 10, the average values of pressure P, temperature T, and condenser vacuum degree V are determined by the computing unit 7 in the computing unit 30.
1, 72, and 74, respectively, and the storage unit 7
Find the rate of change from the planned values stored in 0, 73, and 75. Taking pressure P as an example, ΔP=P-P ₀ /P ₀ (%) ΔP: Rate of change in measured value P ₀ : Planned value is calculated.

The obtained measured value change is input to the correction value calculator 76, and a correction curve (CORRECTION) is created, where the vertical axis is the heat rate change and the horizontal axis is the measured value change.
CURVE) and find the heat rate change (correction value) C1 _~i from the intersection.

The correction values C _{1 to i} are calculated by the correction heat rate calculation device 3
It is input to 0.

As shown in FIG. 11, the correction values C1 _-i are input to the arithmetic unit 78 in the arithmetic unit 30, and the total correction value C is determined by the following equation.

C=(1+C ₁ /100)×(1+C ₂ /100)×
...×(1+Ci/100) The total correction value C and heat rate H.
R. is input to the corrected heat rate calculator 80, and the corrected heat rate HRc is determined from HRc=HR/C.

The corrected heat rate HRc is obtained by correcting the heat rate calculated from the actual measurement value (detection data) based on the planned value, and enables evaluation under the same conditions (same operating state value).

The equipment performance calculation device 22 determines the degree of influence that the performance of each plant equipment, such as the turbine body, boiler, feed water heater, boiler feed water pump, condenser, etc., has on the heat rate.

As an example, the condenser performance calculation device 82 is
As shown in the figure. In this figure, the average value of the condenser inlet/outlet seawater temperatures T ₉ , T ₈ and the condenser inlet seawater flow rate Fc is calculated from the average value calculation unit 26 by the exchange heat amount calculation unit 83
Q=Fc×C×(T ₉ −T ₈ ) C: Calculate the amount of exchanged heat Q from the seawater specific heat, and input this value to the exchanged heat amount ratio calculator 84.

The calculator 84 calculates the exchange heat amount ratio ΔQ, and ΔQ=(Q/Q ₀ )×100(%) Q ₀ :Exchange heat amount planned value. Obtained exchange heat ratio ΔQ
is input to the next estimated condenser vacuum calculator 85, and is calculated from the intersection on a diagram (condenser performance curve) consisting of the condenser vacuum degree on the vertical axis and the condenser exchange heat ratio on the horizontal axis. , the estimated degree of vacuum 86 is determined.

Estimated degree of vacuum V ₀ and average value of measured degree of vacuum ΣV/
By inputting N, the equipment performance correction value calculator 87 calculates heat rate changes ΔHR ₁ and ΔHR ₂ from the intersection on a diagram (correction curve) consisting of heat rate change on the vertical axis and condenser vacuum degree on the horizontal axis. seek.

These values are input to the device performance influence calculator 88, and the influence on the heat rate (device performance influence) ΔHR is determined by ΔHR=ΔHR ₁ −ΔHR ₂ .

Here, the estimated degree of vacuum V ₀ changes with changes in the plant operating state, and the measured degree of vacuum also includes changes in the performance of the condenser itself.

Therefore, the above equation calculates the effect of changes in the performance of the condenser itself on the heat rate.

Similarly for other plant equipment, for the turbine body, internal efficiency, for the boiler, boiler pressure loss, for the feed water heater (heater), terminal temperature difference and drain cooler temperature difference,
Regarding boiler feed pumps, like shaft power, etc.
By replacing the evaluation target of each device with the degree of vacuum described above, it is possible to determine the degree of influence of each device.

Next, the steam power plant performance diagnosis device 23 will be explained.

FIG. 13 shows a detailed control block diagram of the performance diagnostic device 23. In this figure, each input data
HRc, ΔHR, and ΣL/N are input to the classifier 90, and are classified for each plant load band, for example, 80% load or higher, 80% to 60% load, 60% to 40% load, and 40% load or lower. They are classified and stored in the storage 91, and proceed to the next step after a certain period of time or at the request of an operator.

The corrected heat rate HRc is sent to the arithmetic unit 94,
Average calculation of corrected heat rate for each load zone
Execute HRc′. At the same time, the computing unit 92 calculates the average of the plant load within each load zone for each load zone, and as shown in FIG. The intersection point on the diagram consisting of is determined, and the heat rate reference bogey value HR ₀ is set by the setter 93.

In the calculator 95, the corrected heat rate average value
Calculate the deviation between HRc′ and the reference bogey value HR ₀ .

In other words, HRc (%) = 1-HRc'/HR ₀ , and the heat rate deviation value HRc
(%) is set for each plant load zone using the setting device. On the other hand, like the corrected heat rate HRc, the device performance impact degree ΔHR goes through the classifier 90 and the storage device 91 to the calculator 97, where the average calculation of the impact degree is performed for each load zone and for each device. Then, the process proceeds to the arithmetic unit 98. In the calculator 98, the setting device 96
By inputting the heat rate deviation value HRc (%) of It is something.

If the average value of device performance impact is ΔHR′, ΔHR (%) = ΔHR'/HRc (%) × 100 That's what it means.

In addition, the diagnostic device 23 has a function of detecting abnormalities in device performance. The functions will be explained below.

The device performance influence degree ΔHR is averaged in the computing unit 100 for each load zone and for each device, and
The average value is input to comparator 101.

In the comparator 101, a comparison is made with a reference bogey value stored in the storage unit 104a.

Based on the signal from the comparator 101, the determiner 102
If the reference bogey value is exceeded, that is, if the deterioration of equipment performance is recognized to be significant, the output device 103 outputs an alarm, etc.
Provide guidelines for equipment inspection, etc. to operators, etc.

The above is an explanation of device abnormality detection.

Heat rate deviation HRc in setting devices 96 and 99
(%) and device performance influence degree deviation ΔHR (%),
It is stored in the storage 105 for each period.

Next, the steam power plant performance analyzer 24 will be explained.

FIG. 15 shows a detailed control block diagram of the analyzer 24.

The corrected heat rate deviation value HRc (%) and device performance influence degree deviation value ΔHR (%) are input to the calculators 107 and 110 in the analyzer 24 after a certain period of time or at the operator's request, and are calculated for each period and , for each plant load zone, the difference from the data stored in the bogie value storage units 106, 110 at the beginning of plant operation or immediately after periodic inspection is determined. That is, convert these data into HRc (%)
BASE, ΔHR (%) BASE, then ΔHRc (%) = HRc (%) - HRc (%) BASE ΔHR' (%) = ΔHR (%) - ΔHR (%) BASE, and ΔHRc (%) represents the aging rate of the heat rate, and ΔHR′ (%) represents the aging rate of each device.

ΔHRc (%) and ΔHR' (%) are set by setting device 10.
8, 112, output devices 109, 11
3, it will be printed out or displayed on a display.

Next, the details of the performance monitoring technology for a steam-powered power generation plant according to the present invention will be explained using a flowchart.

FIG. 16 is a flowchart showing an overview of the performance monitoring technology of the present invention, and the details of the performance monitoring of the present invention will be explained below.

FIG. 17 shows a detailed flowchart of the load fluctuation range and load stable state duration check function 115 shown in FIG.

In this figure, each detection data, which is the operating state value of the plant, is input to the check function 115 in the data input process 124, and in the detection time and load data selection process 125, the detection time and load (output) in the detection data are inputted into the check function 115. Detection time initial setting check step 126 (this step 12)
6 indicates the transducers 31, 36 of FIG.

Step 126 is to check whether or not an initial value of the detection time has been set, and it is necessary to set the initial value at the time of the first detection. Therefore, the first detection data (time, load) is obtained through the initial value setting process 131 (this process 131 shows the setting devices 32 and 37 in FIG. 5).
Accordingly, the value is set as the initial value and the process returns to step 124.

The data from the second time onward is the load fluctuation range calculation process 1.
34 (this step 134 shows the arithmetic unit 33 in FIG. 5), and the calculation result is transferred to the next load fluctuation range check step 127 (this step 127 shows the comparator 35 and the determiner 41 in FIG. 5). ) is entered. Step 127 is to compare the calculation result (load fluctuation width) with the bogie value, and if the load fluctuation width is within the bogie value, that is, if it can be determined that the plant load is stable, the following The process proceeds to step 135, and if the value is equal to or greater than the bogey value, the process proceeds to step 133. The case of proceeding to step 133 will be described later.

Detection duration calculation process 135 (this process 135
5) is for calculating the time that has passed since the first detection, and after the calculation, the next measurement start check step 128 (this step 128 is performed by the comparator 38 in FIG. 5). 40, which shows the determiner 41).

Step 128 is to compare the plant load stable state duration time and the bogie value, and is shown in FIG. As shown, this is to secure the time from when the plant load stabilizes until the load stabilizes.

That is, only the data indicated by the performance calculation data measurement unit 154 after the settling time has elapsed is valid for performance calculation.

If the settling time is not reached, the process returns to step 124, and after the settling time has elapsed, the process proceeds to step 129.

Measurement start message output check process 129
This ensures a settling time, makes the subsequent data valid for performance calculations, and notifies the operator of the start of detection. A message is output only if starting from step 128 and proceeding to step 129.

That is, the measurement start message output step 130 outputs a message based on the output signal from step 129, and the process returns to step 124, where the above steps are executed again by data input.

Here, in step 127, the process that proceeds when the load fluctuation range is equal to or greater than the bogey value will be described.

Start measurement here Message output check process 1
There are three possible cases in which the process proceeds to step 33, with different progression routes.

In the case where detection data is input at a time when the plant load is not in a stable state (plant load variation unit 151 shown in Fig. 19), the load is in a stable state but the settling time is short and the measurement start message is not output. There are three cases: a case where the load is disturbed, and a case where the load is in a stable state, a settling time is secured, and a measurement start message is output.

In the two cases described above, it is determined in step 133 that no data valid for performance calculation is held in the storage device because no message has been output, and all stored data is cleared in data clear step 132. , return to step 124.

In the remaining case, that is, if a message has been output, the process proceeds to step 136.

The detection duration check process 136 is to determine the length of the performance calculation data measuring section 154 shown in FIG. 19, and is to check whether the storage device stores more than the required number of data used for performance calculation. be. If the detection duration is less than the bogey value, step 132 clears all data in the storage area and returns to step 124.

If the value is greater than or equal to the bogey value, the process proceeds to the input data validity check function 116.

The function 116 will be explained with reference to FIG.

In this figure, all the data in the storage process 136 are stored in the data classification process 137 according to the number of input points in the function 116 (this process 137
is input to the classifier 43 shown in FIG.

In this step 137, important detection data is classified based on the number of input points since a plurality of measurement points are set for the same detection value. For data with two input points, process 138
Proceed to step 139 for data with 1 input point.
Proceed to.

Deviation calculation process 138, 139 (this process 13
8 and 139 indicate the computing units 46 and 56 in FIG.
0 is the calculator 44, 61, setting device 45,
62) is used to calculate the deviation between the reference bogey value calculated in 62 and the detected data.

The deviation values are input into steps 140 and 142.

The detected data validity check process 140 (this process 140 shows the comparator 47 and the determiner 48 in FIG. 6) detects 2 if the deviation values of the 2 input points are both within the reference bogey value. Assuming that both point data are normal data, average value calculation solution 14
3 (this process 143 shows the arithmetic unit 51 in FIG. 6), and the average value is used as the detection data in the detection data setting process 144 (this process 144
is set by the setting device 52 shown in FIG. In other cases, the process proceeds to the detected data validity check process 141 (this process 141 shows the comparator 50 and the determiner 53 in FIG. 6), and one of the deviation values is within the reference bogey value. In the case of,
The data that satisfies the reference bogey value is used as the detection data, and the detection data setting process 145 (this process 1
45 indicates a setting device 55 in FIG. 6).

Otherwise, proceed to step 146.

On the other hand, in the case of one input point, as in the case of two detected data points, the reference bogey value is If it is within the standard bogey value, set process 1.
47 (this step 147 shows the setter 59 in FIG.
6 shows the setters 54, 60 of FIG.

When proceeding to step 146, the data is determined to be abnormal data regardless of the number of detection points, and using it for performance calculations may lead to loss of reliability of performance calculation results (heat rate, etc.). It is something that connects.

Therefore, instead of these data, the reference bogey value is set as the detection data. At this time, the message output process 148 notifies the operator or the like of the detected data abnormality.

As described above, the setting process 144, 145, 14
The data set in any one of 6 and 147 is input to the data averaging and integrating function 117, and is averaged and integrated.

These processes are executed for all stored data, and the following performance calculation functions 118, 119,
Proceed to 120.

The performance calculation results are input to a data classification process 156 (this process 156 represents the classifier 90 in FIG. 13) in the plant performance diagnosis function 121 shown in FIG.

A process 156 is for classifying data for each plant load zone, and a data storage process 157
(This process 157 shows the storage 91 in FIG. 13), which is stored for each load zone.

Storage continues until it is determined in the diagnosis start time check step 158 that a certain period of time has elapsed or that a command has been issued by an operator request.

The signal of step 158 causes data selection step 15
9, the data in the storage area is advanced to the next process for a certain load band of each load band.

The process is divided into three types.

The first path is the corrected heat rate average calculation process 1
60 (This process 160 is performed by the arithmetic unit 94 in FIG.
), and the average value of the corrected heat rate is calculated for each load zone.

The average value is the heat rate deviation calculation process 162
(This process 162 is inputted to the calculator 95 in FIG. 13), and calculates the deviation from the heat rate reference bogey value for each load zone.

The second route is the device performance impact average calculation process 16
1 (this process 161 shows the arithmetic unit 97 in FIG. 13), and is to obtain the average value of the device performance influence degree for each load band.

The average value is the device performance influence degree deviation calculation process 163
(This process 163 shows the calculating unit 98 in FIG. 13), calculates the heat rate deviation value, that is, determines the rate of influence of each device on the heat rate change.

Processes 161 and 163 are device check process 17.
1a is repeatedly executed for each plant device.

The third route is a correction value printing process 155, which prints correction values for changes in operating state values in order to return the heat rate based on the actual measurement value to the planned value base.

This correction value makes it possible to grasp the plant operating state and provide guidelines for actual operation.

The deviation values obtained in processes 162 and 163 are sequentially stored in a storage area for each load and each period by a calculated value storage process 165 (this process 165 shows the storage 105 in FIG. 13), and at the same time , the calculated value is printed out or displayed on a display in the calculated value printing step 166.

Anomaly detection, which is another function of the diagnostic function 121, will be explained.

The average value obtained in the process 161 is calculated in the device performance deviation calculation process 164 (this process 164 is the first
3) performs calculations with the past device performance influence degree average value.

The calculation result is compared with the bogey value set for each device in the device performance check step 167 (this step 167 shows the comparator 101 and judger 102 in FIG. 13), and only when the bogey value is exceeded. Assuming that the device performance is abnormal, a message is output in an abnormality message printing process 168 (this process 168 shows the output device 103 in FIG. 13) to prompt an operator or the like to check the device performance.

This process is performed for each piece of plant equipment by the equipment check process 1716.

The steps after step 159 are as follows for all load bands:
After execution, proceed to the plant performance analysis function 122.

FIG. 21 shows a flowchart of the plant performance analysis function 122.

In the analysis start time check step 177, the data stored in the storage area is input to the data classification step 172 after a certain period of time has elapsed or in response to an operator request.

The classified data is sequentially entered in the plant performance degradation calculation process 17 in order of oldest storage date within one load band.
3 (this process 173 shows the calculator 107 in FIG. 15) and the equipment performance deterioration calculation process 174 (this process 173 shows the calculator 110 in FIG. It executes calculations with the data immediately after completion,
The calculation results are displayed by the following display steps 175 and 176 (showing the output devices 109 and 113 in FIG. 15).
Printed for each period and load band.

This makes it possible to know the transition of performance changes immediately after the start of operation or immediately after periodic inspections.

Plant performance diagnosis function 121, analysis function 122
By comparing the planned base heat rate deviation calculation value for each load zone with past data (chronological data) stored in the storage area,
It becomes possible to understand deterioration of plant performance over time. or,
Upon operator request, it is possible to understand aging deterioration only in the necessary load range.

In addition, it is possible to determine the tendency of changes in plant equipment performance over time by comparing past data (annual data) with the equipment performance influence degree ΔHR on turbine heat rate. It becomes possible to understand the inferiority.

In other words, by comparing trends in plant equipment over time (performance, pressure, temperature, flow rate, etc.) with past data, it is possible to not only understand the current operational status of plant equipment, but also estimate the future status of plant equipment. It also becomes possible to provide guidelines for items to be modified during plant shutdowns such as periodic inspections.

Therefore, by modifying plant equipment according to this guideline, highly efficient plant operation becomes possible.

As described above, when the load fluctuation width of the plant is within a specified value and continues for a specified period of time, there is a function that determines that data detected within that period is valid for performance monitoring, and an input operating status value. If the deviation of It is equipped with a steam power plant performance diagnosis and analysis function that is extremely effective for monitoring.Furthermore, in the steam power plant performance diagnosis and analysis function, by comparing with past data (annual data), it is possible to detect deterioration of plant performance over time. It is also possible to understand the trends in secular changes in the performance of plant equipment (turbines, condensers, boilers, heaters, pumps, etc.) using past data (annual data) and the degree of influence of equipment performance on the turbine heat rate. It is possible to realize a steam power plant performance monitoring method that makes it possible to understand the aging deterioration of current and future equipment performance by determining through comparison.

As is clear from the above description, according to the present invention, it is possible to accurately calculate performance by distinguishing between a stable state and a fluctuating state of the plant load, and to check the validity of the detected plant operating state value. The present invention has the effect of realizing a method for monitoring the performance of a steam power plant that enables performance calculations and monitoring of changes in plant performance over time.

[Brief explanation of the drawing]

FIG. 1 is a schematic diagram of a conventional performance monitoring device for a steam turbine plant, FIG. 2 is a flowchart showing a method for monitoring the performance of the device shown in FIG. 1, and FIG. 3 is a steam turbine according to an embodiment of the present invention. A schematic diagram of a plant performance monitoring device, FIG. 4 is a block diagram showing details of the performance monitoring device shown in FIG. 3, and FIG. 5 is a diagram of the load stable state and load stable state duration determination device shown in FIG. Detailed block diagram. Figure 6 is a detailed block diagram of the input data validity determination device shown in Figure 4. Figure 7 is a diagram of the relationship between plant load and bogie value. Figure 8 is the enthalpy calculation shown in Figure 4. 9 is a detailed block diagram of the flow rate calculation device and heat rate calculation device shown in FIG. 4, FIG. 10 is a detailed block diagram of the correction value calculation device shown in FIG. 4, and FIG. 11 is a detailed block diagram of the device. The figure is a detailed block diagram of the corrected heat rate calculation device shown in Figure 4.
Figure 2 is a detailed block diagram of the equipment performance calculation device shown in Figure 4, Figure 13 is a detailed block diagram of the steam power plant performance diagnostic equipment shown in Figure 4, and Figure 14 is a diagram showing the plant load and heat rate reference bogie. Figure 15 is a detailed block diagram of the steam power plant performance analyzer shown in Figure 4, and Figure 16 is a flowchart outlining the performance monitoring method of the performance monitoring equipment shown in Figure 4. Figure 17 is a detailed flowchart for checking the plant load fluctuation range and load stable state duration time shown in Figure 16, Figure 18 is a detailed flowchart for checking the validity of input data shown in Figure 16, and Figure 19 is a detailed flowchart for checking the plant load fluctuation range and load stable state duration time shown in Figure 16. Explanatory diagram showing the situation of fluctuation range and load stable state duration time, No. 20
This figure is a detailed flowchart of the performance diagnosis method shown in FIG. 16, FIG. 21 is a detailed flowchart of the performance analysis method shown in FIG. 16, and FIG. 22 is an explanatory diagram showing the plant load fluctuation state. 1...High pressure turbine, 2...Low pressure turbine, 3
... Generator, 4 ... Condenser, 5 ... Water pump,
6... Feed water heater (heater), 7... Boiler, 8
... Heat rate calculation device, 9 ... Pressure detection device, 10 ... Temperature detection device, 11 ... Output detection device, 12 ... Flow rate detection device, 14 ... Data detection process, 15 ... Data average, integration calculation process, 16
...Data storage process, 17...Detection duration check process, 18...Performance calculation process, 19...Display process, 20...Load stable state and duration determination device, 21...Input data validity determination device, 22...
... Equipment performance calculation device, 23 ... Steam power plant performance diagnosis device, 24 ... Steam power plant performance analysis device, 25 ... Detection time detection device, 26 ... Average value calculation device, 27 ... Enthalpy calculation device, 2
8...Flow rate calculation device, 29...Correction value calculation device,
30...Correction heat rate calculation device, 31, 36
...Converter, 32, 34, 37, 39... Setting device, 33, 38... Calculator, 35, 40... Comparator, 41... Judgment device, 42... Output signal, 43...
...Classifier, 44, 46, 51, 56, 61... Arithmetic unit, 45, 52, 54, 55, 59, 60, 6
2... Setting device, 47, 50, 57... Comparator, 4
8,53,58...determiner, 49,63...container, 64...enthalpy data, 65...main steam flow rate calculator, 66...low temperature reheat steam flow rate calculator,
67... High temperature reheat steam flow rate calculator, 68... Flow rate data, 69... Heat rate, 70, 73, 7
5...Bogie value storage unit, 71, 72, 74... Rate of change calculator, 76... Correction value calculator, 77... Correction value, 78... Correction value total calculator, 79... Correction value total, 80...Correction heat rate calculator, 81
... Corrected heat rate, 82 ... Condenser performance calculation device, 83 ... Condenser exchange heat amount calculation device, 84 ...
Condenser exchange heat amount ratio calculator, 85...Estimated condenser vacuum degree calculator, 86...Estimated vacuum degree, 87...Equipment performance correction value calculator, 88...Equipment performance influence degree calculator, 89... ...Equipment performance impact level, 90...Classifier,
91,105...Container, 92,94,95,9
7,98,100...Arithmetic unit, 93,96,99
... Setting device, 101 ... Comparator, 102 ... Judgment device, 103 ... Output device, 104a ... Bogie value storage device, 104b ... Correction heat rate deviation value, 1
05...Equipment performance influence degree deviation value, 106,110
...Bogie value storage, 107, 111 ... Arithmetic unit, 108, 112 ... Setting device, 109, 113
...Output device.

Claims (1)

[Scope of Claims] 1. A method for monitoring the performance of a steam power plant by detecting operating status values of each part of a steam power plant and performing various arithmetic operations on a computer based on the detected values. If the width is within the specified value and continues for more than the specified time, the data detected within that period is judged to be effective for performance monitoring, and the data of the detected operating status value is compared with its reference value. The validity of the measurement equipment is checked, the data determined to be valid is determined to be valid for performance monitoring, and these detected data are converted into steam power plant heat consumption rates and steam power plant heat consumption rates by plant equipment. The performance of the steam power plant is monitored by calculating the degree of influence, and furthermore, these calculated values are stored in the computer at regular intervals, and compared with past historical data that is stored periodically or arbitrarily. A method for monitoring the performance of a steam power plant, characterized in that it is possible to diagnose changes in plant performance over time. 2. The calculated values of the steam power plant heat consumption rate and the degree of influence on the steam power plant heat consumption rate by plant equipment are classified by plant load zone and stored in the computer, and the past years for the required load zone are stored. 2. A method for monitoring performance of a steam power plant according to claim 1, characterized in that a comparison is made with historical data.