Lifetime Consumption Estimation Device

Abstract

A life consumption estimation device is used to estimate the life consumption of at least one component of a gas turbine, and includes: a predicted temperature information acquisition unit configured to acquire predicted temperature information related to future temperatures; a predicted load information acquisition unit configured to acquire predicted load information related to the future load of the gas turbine; a gas turbine state quantity estimation unit that estimates at least one future gas turbine state quantity based on the predicted temperature information acquired by the predicted temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and a life consumption estimation unit configured to estimate the life consumption of at least one component based on the estimated at least one gas turbine state quantity.

Description

Technical Field

[0001] The present disclosure relates to a device for estimating life consumption.

[0002] This application claims priority based on Japanese Patent Application No. 2020-104451 filed with the Japan Patent Office on June 17, 2020, and incorporates its content herein. Background Art

[0003] Patent Document 1 discloses a method for diagnosing the state of a gas turbine. By using the operating information of the gas turbine and the process information measured during the operation of the gas turbine, an equivalent operating time for evaluating the damage degree of the components constituting the gas turbine in terms of operating time is calculated during operation, and the state of the gas turbine is diagnosed based on the calculated equivalent operating time and a predetermined management standard.

[0004] In addition, when the calculated equivalent operating time is less than the management standard of each device, the remaining life is calculated. Here, in the calculation of the remaining life, methods are described such as a method based on regression analysis of the data so far; a method based on the operating mode of the design standard; and a method based on the change rate (differential value) at the evaluation time point.

[0005] Prior Art Documents

[0006] Patent Documents

[0007] Patent Document 1: JP Re-Published Patent No. 2002 / 103177 Summary of the Invention

[0008] Problems to be Solved by the Invention

[0009] For example, when calculating the remaining life of a component of a gas turbine by the method described in Patent Document 1, since parameters that affect the future life consumption of the component cannot be appropriately considered, the future life consumption of the component cannot be accurately estimated, and the accuracy of estimating the remaining life of the component is also likely to be limited.

[0010] In view of the above, an object of the present disclosure is to provide a life consumption estimation device that can accurately estimate the future life consumption of components of a gas turbine.

[0011] Means for Solving the Problems

[0012] To achieve the above object, the life consumption estimation device according to the present disclosure is used to estimate the life consumption of at least one component of a gas turbine, and includes: a predicted temperature information acquisition unit configured to acquire predicted temperature information related to future temperatures; a predicted load information acquisition unit configured to acquire predicted load information related to the future load of the gas turbine; a gas turbine state quantity estimation unit configured to estimate at least one gas turbine state quantity related to the future state quantity of the gas turbine based on the predicted temperature information acquired by the predicted temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and a life consumption estimation unit configured to estimate the life consumption of the at least one component based on the at least one gas turbine state quantity estimated by the gas turbine state quantity estimation unit.

[0013] Advantages of the Invention

[0014] According to the present disclosure, there is provided a life consumption estimation device capable of accurately estimating the future life consumption of components of a gas turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a block diagram showing a schematic hardware structure of the life consumption estimation device 2 according to an embodiment.

[0016] Figure 2 It shows Figure 1 a block diagram of the functional schematic structure of the life consumption estimation device 2 shown.

[0017] Figure 3 It is a flowchart showing an example of a method for estimating the life consumption of components of a gas turbine by the life consumption estimation device 2.

[0018] Figure 4 It is a diagram for explaining the information obtained by receiving an input by the predicted temperature input receiving unit 12.

[0019] Figure 5 It is a diagram for explaining a part of the information obtained by receiving an input by the predicted load input receiving unit 18.

[0020] Figure 6 It is a diagram for explaining a part of the information obtained by receiving an input by the predicted load input receiving unit 18.

[0021] Figure 7 It is a diagram for explaining the temperature frequency distribution information S.

[0022] Figure 8 It is a diagram for explaining a plurality of variation patterns representing the time variation pattern of the temperature during a day.

[0023] Figure 9 It is a graph showing the occurrence frequencies of multiple variation patterns of each minimum temperature zone to which the minimum temperature of a day belongs.

[0024] Figure 10 It is a graph for explaining the statistical data of the temperature at each past moment.

[0025] Figure 11 It is a graph for explaining the variation pattern information.

[0026] Figure 12 It is a flowchart showing an example of a method for generating the temperature frequency distribution information S.

[0027] Figure 13 It is a graph showing the standard deviation σ of the minimum temperature for each past month.

[0028] Figure 14 It is a graph showing the minimum temperature randomly simulated and generated for each future day.

[0029] Figure 15 It is a graph for explaining the method of allocating the temperature variation pattern to each future day.

[0030] Figure 16 It is a graph showing the temperature generated for each moment according to each future date.

[0031] Figure 17 It is a graph for explaining the future load frequency distribution information L.

[0032] Figure 18 It is a graph for explaining the past load frequency distribution information.

[0033] Figure 19 It is a graph showing the peak load for each future time zone, the turbine inlet temperature T1T for each temperature zone, etc.

[0034] Figure 20 It is a graph showing the life consumption amounts LFEOHv2, etc. of the components of the gas turbine for each time zone during the future evaluation period.

[0035] Figure 21 It is a graph showing the life consumption amounts LFEOHv3, etc. for each month during the future evaluation period.

[0036] Figure 22 It is a graph for explaining a modified example of life prediction based on the turbine inlet temperature T1T. Detailed implementation mode

[0037] Hereinafter, several embodiments of the present disclosure will be described with reference to the accompanying drawings. However, the dimensions, materials, shapes, relative configurations, etc. of the components described as embodiments or shown in the drawings are not intended to limit the scope of the invention thereto, but are merely illustrative examples.

[0038] For example, expressions indicating relative or absolute configurations such as "in a certain direction", "along a certain direction", "parallel", "orthogonal", "center", "concentric", or "coaxial" not only strictly represent such configurations, but also represent states of relative displacement with tolerances or angles and distances to the extent that the same functions can be obtained.

[0039] For example, expressions indicating states where things are equal such as "same", "equal", and "homogeneous" not only strictly represent equal states, but also represent states with tolerances or differences to the extent that the same functions can be obtained.

[0040] For example, expressions indicating shapes such as a quadrilateral shape and a cylindrical shape not only represent shapes in a strictly geometric sense such as a quadrilateral shape and a cylindrical shape, but also represent shapes including concave and convex portions, chamfered portions, etc. within the range where the same effects can be obtained.

[0041] On the other hand, expressions such as "mounted with", "provided with", "equipped with", "including", or "having" a component are not exclusive expressions that exclude the existence of other components.

[0042] Figure 1 It is a block diagram showing a schematic hardware configuration of the life consumption amount estimation device 2 according to one embodiment. Figure 2 It shows Figure 1 a block diagram of the functional schematic configuration of the life consumption amount estimation device 2 shown.

[0043] As Figure 1As shown, the life consumption estimation device 2 is configured using a computer that includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard Disk Drive), an input I / F 80, and an output I / F 82, which are interconnected via a bus 84. Additionally, the hardware structure of the life consumption estimation device 2 is not limited to the above and can also be configured by a combination of a control circuit and a storage device. Furthermore, the life consumption estimation device 2 is configured by a computer executing a program that implements each function of the life consumption estimation device 2. The functions of each part in the life consumption estimation device 2 described below are realized, for example, by the following processing: loading the program held in the ROM 76 into the RAM 74 and executing it on the CPU 72, and performing reading and writing of data in the RAM 74 and the ROM 76.

[0044] As Figure 2 shown, the life consumption estimation device 2 includes a predicted air temperature information acquisition unit 4, a predicted load information acquisition unit 6, a turbine inlet temperature estimation unit 8 (gas turbine state quantity estimation unit), a life consumption estimation unit 9, and a life consumption addition operation unit 10, and is configured to estimate the life consumption of at least one component of the gas turbine. Additionally, the component of the gas turbine is a high-temperature component whose life consumption changes according to the load of the gas turbine, such as a burner liner, a burner tail pipe, a turbine stator blade, or a turbine rotor blade of the gas turbine. Furthermore, hereinafter, the so-called "turbine inlet temperature" refers to the temperature of the combustion gas at the inlet of the turbine of the gas turbine.

[0045] The predicted air temperature information acquisition unit 4 includes a predicted air temperature input reception unit 12 and an air temperature frequency distribution generation unit 14. The predicted air temperature input reception unit 12 is configured to receive the input of predicted air temperature information P related to the predicted air temperature in the future, and the predicted air temperature information acquisition unit 4 acquires the predicted air temperature information P via the predicted air temperature input reception unit 12. The predicted air temperature information P can be, for example, information related to the minimum air temperature of a future day. In this case, for example, it can be the average value (average minimum air temperature of each month) obtained by averaging the minimum air temperature of a day for each month. Additionally, the predicted air temperature input reception unit 12 can receive the input of the predicted air temperature information P via an input device (not shown) provided outside the life consumption estimation device 2, or can receive the input of the predicted air temperature information P via an input device (e.g., the above input I / F 80) provided inside the life consumption estimation device 2.

[0046] The air temperature frequency distribution generation unit 14 is configured to generate air temperature frequency distribution information S indicating the frequency distribution of the air temperature for each future time zone (a frequency distribution indicating the relationship between the air temperature and the occurrence frequency of the air temperature for each future time zone) based on past air temperature information R related to past air temperatures and predicted air temperature information P obtained by receiving an input by the predicted air temperature input receiving unit 12. The past air temperature information R includes a plurality of variation patterns of the temporal variation of the air temperature during a day and the occurrence frequency of each of the plurality of variation patterns. The plurality of variation patterns and their occurrence frequencies are generated based on statistical information of past air temperatures. In the illustrated exemplary form, the past air temperature information R including the plurality of variation patterns and the occurrence frequency of each variation pattern is stored in the storage unit 16, and the air temperature frequency distribution generation unit 14 generates the air temperature frequency distribution information S based on the plurality of variation patterns read from the storage unit 16, the occurrence frequency of each variation pattern, and the predicted air temperature information P obtained by receiving an input by the predicted air temperature input receiving unit 12.

[0047] The predicted load information acquisition unit 6 includes a predicted load input receiving unit 18 and a peak load rate estimation unit 20. The predicted load input receiving unit 18 is configured to receive an input of predicted load information Q related to the future predicted load of a gas turbine (not shown), and the predicted load information acquisition unit 6 is configured to acquire the predicted load information Q via the predicted load input receiving unit 18.

[0048] The predicted load information Q includes, for example, the predicted value of the peak load for each future time zone (the predicted peak load for each future time zone), the predicted value of the average load for each future time zone (the predicted average load for each future time zone), the predicted value of the future operating rate of the gas turbine (the future predicted operating rate of the gas turbine), and the predicted value of the future number of start-ups of the gas turbine (the future predicted number of start-ups of the gas turbine). In addition, the predicted load input receiving unit 18 may receive an input of the predicted load information Q via an input device (not shown) provided outside the life consumption estimation device 2, or may receive an input of the predicted load information Q via an input device provided inside the life consumption estimation device 2 (for example, the above-described input I / F 80).

[0049] The peak load rate estimation unit 20 is configured to estimate, for each future time zone, the time ratio of the peak load (the time ratio of the time during which the load of the gas turbine is the peak load in that time zone), that is, the peak load rate, based on past load information V related to past loads and predicted load information Q obtained by receiving an input by the predicted load input receiving unit 18.

[0050] The past load information V includes load frequency distribution information representing the frequency distribution of the load of the gas turbine for each past time zone (the frequency distribution showing the relationship between the load of the gas turbine for each past time zone and the occurrence frequency of that load). In the illustrated exemplary form, the past load information V including the past load frequency distribution information is stored in the storage unit 16, and the peak load rate estimation unit 20 estimates the peak load rate for each future time zone based on the past load frequency distribution information read from the storage unit 16 and the predicted load information Q input and received by the predicted load input receiving unit 18.

[0051] For example, the peak load rate estimation unit 20 estimates the peak load rate for each future time zone based on the past load frequency distribution information read from the storage unit 16, the predicted peak load for each time zone input and received by the predicted load input receiving unit 18, and the predicted value of the average load for each time zone input and received by the predicted load input receiving unit 18. The peak load rate estimation unit 20 may also generate, based on the past load frequency distribution information, the predicted value of the peak load for each time zone, and the predicted value of the average load for each time zone, not only the peak load rate for each future time zone but also load frequency distribution information L representing the frequency distribution of the load for each future time zone (the frequency distribution showing the relationship between the load and the occurrence frequency of that load for each future time zone).

[0052] The turbine inlet temperature estimation unit 8 is configured to estimate the future turbine inlet temperature T1T, as a gas turbine state quantity related to the future state quantity of the gas turbine, based on the predicted temperature information P obtained by the predicted temperature information obtaining unit 4 and the predicted load information Q obtained by the predicted load information obtaining unit 6. For example, the turbine inlet temperature estimation unit 8 calculates the weighted average of the turbine inlet temperature T1T for each future time zone based on the temperature frequency distribution information S generated by the temperature frequency distribution generation unit 14 and the load frequency distribution information L representing the frequency distribution of the load for each future time zone estimated by the peak load rate estimation unit 20. In this case, the turbine inlet temperature estimation unit 8 may use only the predicted value of the peak load input and received by the predicted load input receiving unit 18 among the load frequency distributions in the load frequency distribution information L in the calculation of the above weighted average. In this case, the turbine inlet temperature estimation unit 8 estimates the turbine inlet temperature T1T for each future time zone based on the temperature frequency distribution information S generated by the temperature frequency distribution generation unit 14 and the predicted value of the peak load for each future time zone input and received by the predicted load input receiving unit 18.

[0053] The life consumption estimation unit 9 is configured to estimate the life consumption U of at least one component of the gas turbine based on the future turbine inlet temperature T1T for each time zone estimated by the turbine inlet temperature estimation unit 8, the future peak load rate for each time zone estimated by the peak load rate estimation unit 20, the expected value of the operating rate obtained by receiving an input from the expected load input receiving unit 18, and the expected value of the number of starts obtained by receiving an input from the expected load input receiving unit 18.

[0054] The life consumption addition operation unit 10 is configured to add the life consumption U of the component estimated by the life consumption estimation unit 9 to the past life consumption of the component.

[0055] Next, use Figure 3 to illustrate a specific example of the process of estimating the life consumption U of the components of the gas turbine by the above-described life consumption estimation device 2.

[0056] Figure 3 FIG. is an example of a diagram showing the process of estimating the life consumption U of the components of the gas turbine by the life consumption estimation device 2.

[0057] As Figure 3 shown, in S101, the expected temperature input receiving unit 12 receives an input of the expected temperature information P related to the future expected temperature. Here, as Figure 4 shown, the expected temperature input receiving unit 12 receives an input of the expected value of the average minimum temperature for each month as the expected temperature information P. The expected value of the average minimum temperature for each month is equivalent to the average value obtained by averaging the minimum temperature of one day for each month, and is information related to the minimum temperature of one day in the future.

[0058] Next, in S102, the expected load input receiving unit 18 receives an input of the expected load information Q related to the future expected load of the gas turbine. Here, as Figure 5 shown, the expected load input receiving unit 18 receives an input of the expected value of the peak load of the gas turbine for each future time zone and the expected value of the average load during operation of the gas turbine for each future time zone. In addition, as Figure 6 shown, the expected load input receiving unit 18 receives an input of the expected value of the operating rate of the gas turbine for each future month and the expected value of the number of starts of the gas turbine for each future month.

[0059] Next, in S103, the temperature frequency distribution generation unit 14 generates temperature frequency distribution information S indicating the frequency distribution of the temperature for each time zone for each future month as Figure 7 shown, based on the past temperature information R related to the past temperature and the expected temperature information P received by the expected temperature input receiving unit 12.Figure 7 The temperature frequency distribution information S shown divides a given temperature range into a plurality of temperature zones each delimited by a given temperature amplitude, and shows, for each future month and each time zone, the probability that the temperature belongs to each temperature zone. The exemplified temperature frequency distribution information S shown divides the temperature range from 0 degrees to 35 degrees into 7 temperature zones each delimited by 5 degrees, and shows, for each future month and each time zone, the probability that the temperature belongs to each temperature zone.

[0060] In S103, the past temperature information R related to the past temperature includes a plurality of variation patterns (refer to Figure 8 ) representing the pattern of the temporal variation of the temperature during a day, and the occurrence frequency of each of the plurality of variation patterns belonging to each minimum temperature zone of the minimum temperature of a day (refer to Figure 9 ).

[0061] Figure 8 Each of the plurality of variation patterns shown is a variation pattern of the difference between the temperature in each time zone during a day and the minimum temperature of the day. Figure 9 The occurrence frequency of the variation pattern shown divides a given temperature range into a plurality of minimum temperature zones each delimited by a given temperature amplitude, and shows the occurrence frequency (probability of occurrence) of each variation pattern for each minimum temperature zone to which the minimum temperature of a day belongs. In the example shown in Figure 9 , the temperature range from 0 degrees to 30 degrees is divided into 6 minimum temperature zones each delimited by 5 degrees, and the occurrence frequency of each variation pattern is shown for each minimum temperature zone to which the minimum temperature of a day belongs.

[0062] Here, an example of a method for generating a plurality of variation patterns and their occurrence frequencies will be described. First, the statistical data of the temperature at each past moment as exemplified in Figure 10 is transformed, as exemplified in Figure 11 , into variation pattern information associating the minimum temperature of each day and the difference between the temperature at each moment of each day and the minimum temperature, i.e., the variation pattern. The variation patterns of the variation pattern information are clustered into a plurality of variation patterns as shown in Figure 8 . In the example shown in Figure 8 , the variation patterns of the temperature are clustered into 12 variation patterns. And by sorting out the above variation pattern information for each of the clustered plurality of variation patterns, the occurrence frequency of each of the plurality of variation patterns is generated for each minimum temperature zone to which the minimum temperature of a day belongs, as shown in Figure 9 .

[0063] In addition, the past temperature information R can be stored in the storage unit 16 generated outside the life consumption estimation device 2, can be generated in the life consumption estimation device 2 and stored in the storage unit 16, or can be obtained from outside the life consumption estimation device 2 and used by the temperature frequency distribution generation unit 14 in the generation of the temperature frequency distribution information S without passing through the storage unit 16.

[0064] Next, use Figure 12 The flowchart shown below to illustrate an example of the method for generating the temperature frequency distribution information S in S103.

[0065] As Figure 12 shown, in S201, based on Figure 11 the daily minimum temperature in the variation pattern information shown, calculate the standard deviation σ of the minimum temperature for each past month as Figure 13 shown. Next, in S202, based on the standard deviation σ of the minimum temperature for each past month calculated in S201 and the predicted value of the average minimum temperature for each future month included in the predicted temperature information P obtained in S101, randomly and analogously generate, for each future day, the minimum temperature corresponding to a normal distribution having the above standard deviation σ and the above average minimum temperature as Figure 14 shown.

[0066] Then, in S203, based on the minimum temperature for each future day generated in S202, Figure 8 the multiple variation patterns shown, and Figure 9 the occurrence frequency of each variation pattern for each minimum temperature band shown, randomly and analogously generate, as Figure 15 shown, the variation pattern of the temperature based on the occurrence frequency of the minimum temperature band to which the minimum temperature for each future day belongs, and allocate it to each day.

[0067] Then, in S204, based on the minimum temperature for each future day generated in S202, the variation pattern of the temperature allocated to each future day in S203, and Figure 8 the temperature difference between the temperature at each time zone in each variation pattern of the temperature shown, generate, as Figure 16 shown, the predicted temperature for each moment for each future date.

[0068] Then, in S205, by organizing the predicted temperature for each moment for each future date generated in S204 for each time zone for each future month, generate Figure 7 the temperature frequency distribution information S shown.

[0069] Next, return to Figure 3, in S104, the peak load rate estimation unit 20 estimates the time ratio of the peak load, i.e., the peak load rate, for each future time zone based on the past load information V related to the past load and the predicted load information Q received and input by the predicted load input receiving unit 18 as Figure 17 shown. In the example shown in Figure 17 , the peak load rate estimation unit 20 generates a frequency distribution of the load of the gas turbine for each future time zone (a frequency distribution representing the relationship between the load and the predicted value of the occurrence frequency of the load for each future time zone), as the load frequency distribution information L including the peak load rate. Figure 17 The load frequency distribution information L shown is information that divides a given load range into a plurality of load bands and shows the probability that the load belongs to each load band for each future time zone.

[0070] In S104, the past load information V related to the past load is as shown in Figure 18 and includes past load frequency distribution information representing a frequency distribution of the load of the gas turbine for each past time zone (a frequency distribution representing the relationship between the load of the gas turbine for each past time zone and the occurrence frequency of the load). Figure 18 The past load frequency distribution information shown is information that divides a given load range into a plurality of load bands and shows the probability that the load belongs to each load band for each past time zone. The past load frequency distribution information in the past load information V can be obtained, for example, by extracting the loads at each past moment from the past operation data of the gas turbine and organizing them.

[0071] In S104, based on changing the peak load in the past load frequency distribution information shown in Figure 18 to the predicted value of the peak load in the predicted load information Q, the peak load rate estimation unit 20 adjusts the frequency of each load in the load frequency distribution information so that the average load in the load frequency distribution information is equal to the predicted value of the average load in the predicted load information Q, and thus generates the future load frequency distribution information L shown in Figure 17 .

[0072] In addition, the past load frequency distribution information in the past load information V can be generated and stored in the storage unit 16 outside the life consumption estimation device 2, can be generated and stored in the storage unit 16 in the life consumption estimation device 2, or can be obtained from outside the life consumption estimation device 2 and used by the peak load rate estimation unit 20 without passing through the storage unit 16 in the generation of the load frequency distribution information L including the peak load rate for each future time zone.

[0073] Next, in S105, the turbine inlet temperature estimation unit 8 estimates the future turbine inlet temperature T1T for each time zone based on the air temperature frequency distribution information S generated in S103 and the load frequency distribution information L generated in S104. Here, since the peak load of the gas turbine has a dominant influence on the turbine inlet temperature T1T compared to other loads, the turbine inlet temperature estimation unit 8 can calculate the turbine inlet temperature T1T for each time zone for each future month based on the peak load for each time zone in the load frequency distribution information L and the frequency distribution of the air temperature for each time zone for each future month in the air temperature frequency distribution information S. In this case, the weighted average of the turbine inlet temperature can also be calculated by weighting with the frequency of the air temperature (the probability that the air temperature in each future time zone belongs to each air temperature zone) in the air temperature frequency distribution information S.

[0074] For example, at a certain time zone t0, if the predicted value (MW) of the peak load is set to a0, the i-th air temperature in the air temperature frequency distribution information S is set to Ti (if the number of air temperature zones in the air temperature frequency distribution information S is set to n, it represents the temperature of the i-th air temperature zone among n air temperature zones), the turbine inlet temperature when the predicted value of the peak load is a0 and the air temperature is Ti is set to T1T(a0, Ti), and the frequency of occurrence of the air temperature Ti (the frequency that the air temperature belongs to the i-th air temperature zone) is set to pi, then the weighted average T1Tt0 of the turbine inlet temperature T1T(a0, Ti) in the time zone t0 weighted by the frequency pi can be represented by the following formula (1).

[0075] [Mathematical formula 1]

[0076]

[0077] That is, for example, as Figure 19 shown, for each time zone, the turbine inlet temperature T1T(a0, Ti) based on the predicted value of the peak load and each air temperature is calculated for each air temperature zone, and the results obtained by multiplying the turbine inlet temperature T1T(a0, Ti) in each air temperature zone by the frequency pi of that air temperature zone are added together for all air temperature zones, thereby calculating the weighted average of the turbine inlet temperature T1T. Here, the relationship between the peak load, the air temperature, and the turbine inlet temperature T1T can be obtained from the past operation data of the gas turbine, for example, read from the storage unit 16 and used in the estimation of the turbine inlet temperature. In several embodiments, the exhaust temperature of the gas turbine can also be calculated based on the peak load and the air temperature, the compression ratio of the gas turbine can be calculated based on the peak load, and the turbine inlet temperature can be calculated based on the exhaust temperature and the compression ratio of the gas turbine.

[0078] Next, in S106, the life consumption estimation unit 9 estimates the future life consumption of the components of the gas turbine based on the turbine inlet temperature T1T (the weighted average of the turbine inlet temperature T1T in the above example) for each future time zone estimated in S105.

[0079] Here, a method for estimating the future life consumption of the components of the gas turbine by the life consumption estimation unit 9 will be described. The life consumption during the future evaluation period of the components of the gas turbine can be estimated by the following method. The life consumption LF per unit time under a certain operating load can be estimated based on the state quantities of the gas turbine (such as turbine inlet temperature, pressure ratio, and / or exhaust gas temperature, etc.). By multiplying this LF by the operating time AOH of the gas turbine under this load, the life consumption LFEOH of the gas turbine during the evaluation period can be estimated. However, in the above, since only the influence of the operating time such as creep can be considered, for the calculation of the actual LFEOH, it is necessary to additionally incorporate the influence of the number of starts of the gas turbine.

[0080] In addition, Figure 20 The life consumption LFEOHv2 of the components of the gas turbine for each time zone (every 1 hour in the illustrated example) during the future evaluation period as shown can be calculated by multiplying LFEOHv1 by the peak load rate and the operation rate without considering the number of starts of the gas turbine. Here, LFEOHv1 is the assumed life consumption for each future time zone. LFEOHv1 has a positive correlation with the turbine inlet temperature T1T and is characterized as a function of the turbine inlet temperature T1T for each component of the gas turbine. Information indicating the correlation between the turbine inlet temperature T1T and LFEOHv1 is stored in the storage unit 16, for example, and is read out for the calculation of LFEOH.

[0081] Then, Figure 21 The life consumption LFEOHv3 of the components of the gas turbine for each month during the future evaluation period as shown can be calculated by incorporating the influence of the number of starts on the component life into LFEOHv2.

[0082] Furthermore, the life consumption LFEOH during the entire evaluation period from the current time to a certain future time point is equal to the cumulative value obtained by cumulatively continuing LFEOHv3 from the current time to the entire evaluation period of a certain future time point.

[0083] Next, in S107, the lifetime consumption LFEOH of the component from the present to a certain time point in the future is added to the lifetime consumption LFEOH of the component estimated in S106. Thus, the lifetime consumption LFEOH of the component from the beginning of use to a certain time point in the future can be calculated. In addition, the remaining life of the component can be obtained by subtracting the lifetime consumption LFEOH of the component from the beginning of use to a certain time point in the future calculated in S107 from the life of the component.

[0084] Next, a modification of the life prediction based on the turbine inlet temperature T1T described in the present embodiment will be described. In the above-described embodiment, the life consumption of the gas turbine may be estimated based on the turbine inlet temperature T1T as an example of the gas turbine state quantity, and the life consumption of the gas turbine may be estimated based on at least one gas turbine state quantity other than the turbine inlet temperature.

[0085] For example, since the temperature of the combustion gas at the turbine rear stage is lower than the turbine inlet temperature T1T, in order to accurately predict the life of the turbine rear stage, the combustion gas temperature at the target stage of the gas turbine is estimated and used. Specifically, the gas turbine state estimation unit estimates the combustion gas temperature of each stage of the gas turbine based on the estimated turbine inlet temperature T1T and the pressure ratio, taking into account the temperature drop caused by the expansion caused by the turbine and the mixing of the cooling air, and the life consumption estimation unit estimates the life consumption of the component of the target stage based on the estimated combustion gas temperature of the target stage. In addition, when low cycle fatigue (LCF) is more dominant than high temperature oxidation as a factor of the life consumption of the component, the life consumption based on the cumulative value of the load change rate (% load / min) expected in the future can be calculated, and compared with the life consumption estimated based on the turbine inlet temperature T1T, and the larger one can be adopted as the estimated value of the life consumption.

[0086] Furthermore, whenever the life of a component is expected to reach its end, the estimated life consumption is compared with the remaining life of the component. The remaining life can also be replaced by a value calculated based on the repair history of the component (inspection records of crack occurrence, TBC peeling, etc.) instead of the nominal value.

[0087] For example, in Figure 22In the example shown, based on the above temperature frequency distribution information S and load frequency distribution information L, the pressure ratio, turbine inlet temperature T1T, and exhaust gas temperature are calculated for each time zone, and based on these, the inlet temperature of the nth-stage stationary blade (n is an integer of 1 or more) of the gas turbine is calculated. Then, based on the calculated inlet temperature of the nth-stage stationary blade and the information on the correlation between the inlet temperature of the nth-stage stationary blade and the life consumption amount of the nth-stage stationary blade, the life consumption amount of the nth-stage stationary blade for each time zone is calculated, and the cumulative value obtained by cumulatively adding up the life consumption amounts of the nth-stage stationary blade calculated for each time zone over the entire evaluation period is calculated. Furthermore, based on the latest life evaluation of the gas turbine and the inspection record of the nth-stage stationary blade, the remaining life of the nth-stage stationary blade is calculated, and by comparing this remaining life with the above cumulative value obtained by cumulatively adding up the life consumption amounts of the nth-stage stationary blade over the entire evaluation period, the life reaching time of the nth-stage stationary blade can be predicted. In addition, in Figure 22 the example shown, the pressure ratio, turbine inlet temperature T1T, exhaust gas temperature, and inlet temperature of the nth-stage stationary blade each correspond to a gas turbine state quantity related to a future state quantity of the gas turbine.

[0088] All of the above-described modified examples can also be used in combination with each other.

[0089] The present disclosure is not limited to the above-described embodiments, and also includes forms in which modifications are added to the above-described embodiments and forms in which these forms are appropriately combined.

[0090] The content described in each of the above embodiments can be grasped as follows, for example.

[0091] (1) The life consumption amount estimation device according to the present disclosure (for example, the above-described life consumption amount estimation device 2) is used to estimate the life consumption amount of at least one component of a gas turbine, and includes: a predicted temperature information acquisition unit (for example, the above-described predicted temperature information acquisition unit 4) configured to acquire predicted temperature information related to a future temperature; a predicted load information acquisition unit (for example, the above-described predicted load information acquisition unit 6) configured to acquire predicted load information related to the future load of the gas turbine; a gas turbine state quantity estimation unit (for example, the above-described turbine inlet temperature estimation unit 8) configured to estimate at least one gas turbine state quantity related to the future state quantity of the gas turbine based on the predicted temperature information acquired by the predicted temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and a life consumption amount estimation unit (for example, the above-described life consumption amount estimation unit 9) configured to estimate the life consumption amount of the at least one component based on the at least one gas turbine state quantity estimated by the gas turbine state quantity estimation unit.

[0092] The life consumption of a large number of components used in a gas turbine is related to the state quantity of the gas turbine. In addition, the state quantity of the gas turbine is sometimes related to the load of the gas turbine and the air temperature.

[0093] Therefore, in the life consumption estimation device described in (1) above, at least one gas turbine state quantity related to the future state quantity of the gas turbine is estimated based on the predicted air temperature information and the predicted load information, and the life consumption of the components of the gas turbine is estimated based on the estimated gas turbine state quantity. Therefore, the life consumption of the components of the gas turbine can be accurately estimated based on the gas turbine state quantity estimated considering the future load and air temperature of the gas turbine.

[0094] (2) In several embodiments, based on the life consumption estimation device described in (1) above, the gas turbine state quantity estimation unit is configured to estimate the future turbine inlet temperature as the gas turbine state quantity, and the life consumption estimation unit is configured to estimate the life consumption of the at least one component based on the future turbine inlet temperature estimated by the gas turbine state quantity estimation unit.

[0095] The life consumption of a large number of components used in a gas turbine is related to the turbine inlet temperature. In addition, the turbine inlet temperature is related to the load of the gas turbine and the air temperature.

[0096] Therefore, based on the life consumption estimation device described in (1) above, the future turbine inlet temperature of the gas turbine is estimated based on the predicted air temperature information and the predicted load information, and the life consumption of the components of the gas turbine is estimated based on the estimated turbine inlet temperature. Therefore, the life consumption of the components of the gas turbine can be accurately estimated based on the turbine inlet temperature estimated considering the future load and air temperature of the gas turbine.

[0097] (3) In several embodiments, based on the life consumption estimation device described in (1) or (2) above, the predicted air temperature information acquisition unit includes: a predicted air temperature input receiving unit (such as the predicted air temperature input receiving unit 12 described above), which is configured to receive the input of the predicted air temperature information; and an air temperature frequency distribution generation unit (such as the air temperature frequency distribution generation unit 14 described above), which is configured to generate air temperature frequency distribution information representing the frequency distribution of the air temperature in each future time zone based on the past air temperature information related to the past air temperature and the predicted air temperature information received by the predicted air temperature input receiving unit, and the gas turbine state quantity estimation unit is configured to estimate the gas turbine state quantity for each future time zone based on the air temperature frequency distribution information generated by the air temperature frequency distribution generation unit and the predicted load information acquired by the predicted load information acquisition unit.

[0098] Since the temperature varies according to time, in order to accurately estimate the gas turbine state quantity for each future time zone, it is desirable to estimate the gas turbine state quantity based on the predicted temperature for each future time zone.

[0099] Therefore, according to the life consumption estimation device described in (3) above, considering the past temperature information and the predicted temperature information, temperature frequency distribution information representing the frequency distribution of the temperature for each future time zone is generated, and based on this temperature frequency distribution information, the gas turbine state quantity is estimated for each future time zone. Therefore, it is possible to accurately estimate the gas turbine state quantity and the life consumption of components while considering the temporal variation of temperature.

[0100] (4) In several embodiments, based on the life consumption estimation device described in (3) above, the predicted temperature input receiving unit is configured to receive the input of information related to the minimum temperature of a day as the predicted temperature information.

[0101] The temporal variation pattern of the temperature during a day is related to the minimum temperature of the day. Therefore, as described in (4) above, by receiving the input of information related to the minimum temperature of a day, it is possible to accurately estimate the temperature for each future time zone while considering this minimum temperature. Therefore, it is possible to accurately estimate the gas turbine state quantity and the life consumption of components.

[0102] (5) In several embodiments, based on the life consumption estimation device described in (3) or (4) above, the past temperature information includes a plurality of variation patterns of the temporal variation of the temperature during a day and the occurrence frequency of each of the plurality of variation patterns.

[0103] According to the life consumption estimation device described in (5) above, it is possible to accurately estimate the temperature for each future time zone while considering a plurality of variation patterns of the past temperature and their occurrence frequencies. Thus, it is possible to accurately estimate the future gas turbine state quantity and the life consumption of components.

[0104] (6) In several embodiments, based on the life consumption estimation device described in (5) above, it further includes: a storage unit (such as the above-mentioned storage unit 16) that stores the plurality of variation patterns and the occurrence frequency of each of the variation patterns.

[0105] According to the life consumption estimation device described in (6) above, it is possible to accurately estimate the temperature for each future time zone based on the plurality of variation patterns stored in the storage unit and their occurrence frequencies.

[0106] (7) In several embodiments, based on the life consumption amount estimation device described in any one of the above (1) to (6), the predicted load information acquisition unit includes: a predicted load input receiving unit (such as the predicted load input receiving unit 18 described above), which is configured to receive the input of the predicted load information; and a peak load rate estimation unit (such as the peak load rate estimation unit 20 described above), which is configured to estimate the time ratio of the peak load, i.e., the peak load rate, for each future time zone based on the past load information related to the past load of the gas turbine and the predicted load information received by the predicted load input receiving unit.

[0107] The peak load of the gas turbine has a dominant influence on the gas turbine state quantity (especially the turbine inlet temperature) compared with other loads. Therefore, by estimating the peak load rate for each future time zone based on the past load information and the predicted load information as described in the above (7), it is possible to accurately calculate the gas turbine state quantity (especially the turbine inlet temperature) and the life consumption amount of the components for each future time zone while considering the peak load rate.

[0108] (8) In several embodiments, based on the life consumption amount estimation device described in the above (7), the predicted load input receiving unit is configured to receive the predicted value of the peak load for each future time zone and the predicted value of the average load for each future time zone as the predicted load information.

[0109] According to the life consumption amount estimation device described in the above (8), it is possible to accurately estimate the peak load rate while considering the predicted value of the peak load and the predicted value of the average load. As a result, it is possible to accurately calculate the gas turbine state quantity and the life consumption amount of the components for each future time zone.

[0110] (9) In several embodiments, based on the life consumption amount estimation device described in any one of the above (1) to (8), the predicted load information includes the predicted value of the future operating rate of the gas turbine, and the life consumption amount estimation unit estimates the future life consumption amount based on the gas turbine state quantity estimated by the gas turbine state quantity estimation unit and the predicted value of the operating rate obtained by the predicted load information acquisition unit.

[0111] According to the life consumption amount estimation device described in the above (9), it is possible to accurately estimate the life consumption amount of the components while considering the predicted gas turbine state quantity and the predicted value of the operating rate in the future.

[0112] (10) In several embodiments, based on the life consumption amount estimation device described in any one of the above (1) to (9), the predicted load information includes a predicted value of the future number of startups of the gas turbine, and based on the gas turbine state quantity estimated by the gas turbine state quantity estimation unit and the predicted value of the number of startups obtained by the predicted load information acquisition unit, the life consumption amount is estimated.

[0113] According to the life consumption amount estimation device described in the above (10), it is possible to accurately estimate the life consumption amount of components by considering the predicted gas turbine state quantity and the predicted value of the number of startups in the future.

[0114] (11) In several embodiments, based on the life consumption amount estimation device described in any one of the above (1) to (10), the gas turbine state quantity estimation unit is configured to calculate the weighted average of the gas turbine state quantity for each future time zone based on the temperature frequency distribution information indicating the frequency distribution of the temperature for each future time zone and the load frequency distribution information indicating the frequency distribution of the load for each future time zone.

[0115] According to the life consumption amount estimation device described in the above (11), it is possible to accurately estimate the future gas turbine state quantity and the life consumption amount by considering the frequency distribution of the temperature and the frequency distribution of the load for each future time zone.

[0116] (12) In several embodiments, based on the life consumption amount estimation device described in the above (11), the gas turbine state quantity estimation unit is configured to use only the peak load in the load distribution of the load frequency distribution information in the calculation of the weighted average.

[0117] The peak load of the gas turbine has a dominant influence on the gas turbine state quantity estimation unit (especially the turbine inlet temperature) compared to other loads. Therefore, by using only the peak load in the load distribution in the calculation of the weighted average as described in the above (12), it is possible to accurately calculate the gas turbine state quantity and the life consumption amount of components for each future time zone by means of a simple calculation based on the peak load.

[0118] (13) In several embodiments, based on the life consumption amount estimation device described in any one of the above (1) to (12), it further includes: a life consumption amount addition operation unit configured to add the life consumption amount of the component estimated by the life consumption amount estimation unit to the past life consumption amount of the component.

[0119] According to the life consumption amount estimation device described in the above (13), it is possible to calculate the life consumption amount of the component consumed from the past to a certain point in the future.

[0120] (14) In several embodiments, based on the life consumption estimation device described in any one of the above (1) to (13), the gas turbine state quantity estimation unit is configured to estimate the combustion gas temperature of each stage of the gas turbine, and as the gas turbine state quantity, the life consumption estimation unit is configured to estimate the life consumption of the component of the target stage based on the combustion gas temperature of the target stage estimated by the gas turbine state quantity estimation unit.

[0121] In a gas turbine, since the temperature of the combustion gas decreases as it goes downstream (the rear stage side) in the flow direction of the combustion gas, by estimating the temperature of the combustion gas for each stage of the gas turbine as described in the above (14) and estimating the life consumption of the component of the target stage based on the temperature of the combustion gas of the target stage, the life consumption of the component can be calculated with good accuracy.

[0122] -Symbol Explanation-

[0123] 2 Life consumption estimation device

[0124] 4 Predicted air temperature information acquisition unit

[0125] 6 Predicted load information acquisition unit

[0126] 8 Turbine inlet temperature estimation unit

[0127] 9 Life consumption estimation unit

[0128] 10 Life consumption addition operation unit

[0129] 12 Predicted air temperature input receiving unit

[0130] 14 Air temperature frequency distribution generation unit

[0131] 16 Storage unit

[0132] 18 Predicted load input receiving unit

[0133] 20 Peak load rate estimation unit

[0134] 72 CPU

[0135] 84 Bus.

Claims

1. A life consumption estimation device for estimating the life consumption of at least one component of a gas turbine, characterized in that Comprising: A predicted temperature information acquisition unit configured to acquire predicted temperature information related to future temperatures; A predicted load information acquisition unit configured to acquire predicted load information related to the future load of the gas turbine; A gas turbine state quantity estimation unit configured to estimate at least one gas turbine state quantity related to the future state quantity of the gas turbine based on the predicted temperature information acquired by the predicted temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and A life consumption estimation unit configured to estimate the life consumption of the at least one component based on the at least one gas turbine state quantity estimated by the gas turbine state quantity estimation unit, The predicted temperature information acquisition unit includes: A predicted temperature input reception unit configured to receive the input of the predicted temperature information; and A temperature frequency distribution generation unit configured to generate temperature frequency distribution information representing the frequency distribution of temperatures in each future time zone based on past temperature information related to past temperatures and the predicted temperature information input and received by the predicted temperature input reception unit, The gas turbine state quantity estimation unit is configured to estimate the gas turbine state quantity for each future time zone based on the temperature frequency distribution information generated by the temperature frequency distribution generation unit and the predicted load information acquired by the predicted load information acquisition unit.

2. The life consumption estimation device according to claim 1, wherein: The gas turbine state quantity estimation unit is configured to estimate the future turbine inlet temperature as the gas turbine state quantity, The life consumption estimation unit is configured to estimate the life consumption of the at least one component based on the future turbine inlet temperature estimated by the gas turbine state quantity estimation unit.

3. The life consumption estimation device according to claim 1, wherein: The predicted temperature input reception unit is configured to receive the input of information related to the minimum temperature of a day as the predicted temperature information.

4. The life consumption estimation device according to claim 1, wherein: The past temperature information includes a plurality of variation patterns of the temporal variation of the temperature during a day and the occurrence frequency of each of the plurality of variation patterns.

5. The life consumption estimation device according to claim 4, wherein: The life consumption estimation device further includes: A storage unit that stores the plurality of variation patterns and the occurrence frequency of each of the variation patterns.

6. The life consumption estimation device according to claim 1, wherein: The predicted load information acquisition unit includes: A predicted load input reception unit configured to receive the input of the predicted load information; and A peak load rate estimation unit configured to estimate the time ratio of the peak load, i.e., the peak load rate, for each future time zone based on past load information related to the past load of the gas turbine and the predicted load information input and received by the predicted load input reception unit.

7. The life consumption estimation device according to claim 6, wherein: The predicted load input receiving unit is configured to receive, as the predicted load information, the predicted value of the peak load for each future time band and the predicted value of the average load for each future time band.

8. The life consumption estimation device according to claim 1, wherein: The predicted load information includes the predicted value of the future operating rate of the gas turbine. The life consumption estimation unit is configured to estimate the life consumption based on the gas turbine state quantity estimated by the gas turbine state quantity estimation unit and the predicted value of the operating rate obtained by the predicted load information acquisition unit.

9. The life consumption estimation device according to claim 1, wherein: The predicted load information includes the predicted value of the future number of starts of the gas turbine. The life consumption estimation unit is configured to estimate the life consumption based on the gas turbine state quantity estimated by the gas turbine state quantity estimation unit and the predicted value of the number of starts obtained by the predicted load information acquisition unit.

10. The life consumption estimation device according to claim 1, wherein: The gas turbine state quantity estimation unit is configured to calculate the weighted average of the gas turbine state quantity for each future time band based on the temperature frequency distribution information indicating the frequency distribution of the temperature for each future time band and the load frequency distribution information indicating the frequency distribution of the load for each future time band.

11. The life consumption estimation device according to claim 10, wherein: The gas turbine state quantity estimation unit is configured to use only the peak load among the loads in the load frequency distribution information for calculating the weighted average.

12. The life consumption estimation device according to claim 1, wherein: The life consumption estimation device further includes: A life consumption addition operation unit configured to add the life consumption of the component estimated by the life consumption estimation unit to the past life consumption of the component.

13. The life consumption estimation device according to claim 1, wherein: The gas turbine state quantity estimation unit is configured to estimate the combustion gas temperature of each stage of the gas turbine as the gas turbine state quantity. The life consumption estimation unit is configured to estimate the life consumption of the component of the target stage based on the combustion gas temperature of the target stage estimated by the gas turbine state quantity estimation unit.

Images