JP2014181570A - Steam turbine control device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a steam turbine control device that can be started at a required time.SOLUTION: A control device 14 has: state quantity acquisition means 18 for acquiring a measurement value from a measuring instrument for a state quantity of a steam turbine as an actual state quantity value during starting, acquiring a state quantity planning value from a database, and calculating state quantity deviation as deviation based on the acquired state quantity planning value and the actual state quantity value; plant operation quantity determination means 19 for acquiring an operation quantity planning value from the database, acquiring the state quantity deviation from the state quantity acquisition means, calculating an operation correction quantity of an operation quantity associated with the state quantity based on the state quantity deviation and a pre-calculated conversion matrix A, and determining the operation quantity to an operation end based on the acquired operation quantity planning value and the calculated operation correction quantity; and master curve management means 20 for calculating the corrected conversion matrix A based on the operation correction amount calculated by the plant operation quantity determination means 19 and the state quantity deviation calculated by the state quantity acquisition means 18.

Description

  The present invention relates to a control device for starting a power plant (hereinafter referred to as a steam turbine plant) including a steam turbine.

  Conventionally, the start-up of a steam turbine plant has been often controlled mainly according to a predetermined schedule along a time axis. On the other hand, in recent years, start-up and load changes in a shorter time are required for steam turbine plants. While this is expected to increase global energy demand in the future, there are concerns about fossil fuels such as depletion and global warming. As a result, renewable energy system power represented by wind power generation and solar power generation This is because the connection to is increasing. The role of stabilizing the system power by absorbing fluctuations in the amount of power generated by these renewable energies is required for thermal power plants that include a steam turbine as a component. In addition, in a renewable energy plant that includes a steam turbine such as a steam Rankine cycle, the steam turbine can be started up at a high speed and the load can be changed for rapid start-up and load following operation in response to fluctuations in the amount of heat source of natural energy. Is required.

  The characteristics at the start of the steam turbine are that the heat transfer rate between the steam and the steam turbine rotor increases as the steam temperature increases or the steam flow rate increases. As a result, the surface temperature of the steam turbine rotor is faster than that inside the rotor. The temperature gradient in the rotor radial direction increases and thermal stress may increase. Excessive thermal stress shortens the life of the steam turbine rotor, so that thermal stress (hereinafter referred to as “thermal stress” refers to the thermal stress applied to the steam turbine rotor) falls within a predetermined limit value. It is necessary to start and control the steam turbine.

  Further, when the steam turbine is started, the steam turbine rotor and the casing that houses the steam turbine rotor are heated by being exposed to high-temperature steam, and are expanded particularly in the turbine axial direction by thermal expansion (this is called thermal expansion). ). At this time, since the steam turbine rotor and the casing have different structures and heat capacities, there is a difference between the thermal elongation of the steam turbine rotor and the casing. This is called a difference in thermal elongation. When the difference in thermal expansion becomes large, the rotating part of the steam turbine rotor and the stationary part of the casing come into contact with each other and are damaged. Therefore, it is necessary to start and control the steam turbine so that the difference in thermal expansion falls within a predetermined limit value.

  As a method of controlling so that such physical quantities as thermal stress and thermal expansion differences, or other physical quantities that serve as indices for limiting conditions during plant operation (hereinafter collectively referred to as state quantities) are within the limiting values. Various methods as shown in Patent Documents 1-5 have been proposed.

  In Patent Document 1, prediction means for predicting thermal stress in a predetermined prediction period, and an operation amount that suppresses the predicted thermal stress to a specified value or less, satisfies a part of the plant operation conditions, and minimizes the plant start-up time. An optimal pattern calculation means for calculating the optimal transition pattern, pattern correction means for correcting the optimal transition pattern so as to satisfy operational constraints other than those considered in the optimal transition pattern, and the current time value in the correction pattern An example is provided with an operation amount adjusting means which is set as a set value of a state quantity, and the operation value is adjusted so as to eliminate the deviation between the measured value corresponding to the set value and the turbine control device. It is disclosed. The operation amount adjusting means plays a role of adjusting the operation amount so that the deviation of the measured value at the time of actual plant start-up from the predicted value of the plant state quantity is eliminated. As a method for adjusting the operation amount, feedback control is used to adjust the rate of increase of the steam turbine and the rate of load increase, to directly control the steam flow rate, or to change the set value of the rotation speed and load. In this way, it is possible to improve the start-up control accuracy by reducing changes caused by the fact that the boiler conditions at the time of actual start-up of the plant are different from those at the time of prediction and the influence of uncertainty between the predicted value and the actual value. ing.

  Patent Document 2 discloses a specific calculation procedure for a control technique for predicting and calculating thermal stress in a prediction period extending from the current time to the future and starting the steam turbine at high speed while keeping the predicted thermal stress within a limit value. Yes.

  Patent Document 3 discloses a method of predicting thermal stress and thermal expansion difference over a predetermined prediction period, and controlling such values to be within a limit value based on the prediction result.

  In Patent Document 4, a process operation target setting means, a control means for receiving a signal from the target setting means and outputting a control amount, and the process operated based on a signal from the control means An evaluation unit that evaluates driving characteristics corresponding to the driving target; a correction unit that extracts a driving policy from a correction rule based on an evaluation value obtained by the evaluation unit and determines a correction amount of the control unit; A method comprising storage means for storing the relationship between the correction amount obtained by the correction means and the operation target is disclosed.

  In Patent Document 5, although a controlled object is a boiler instead of a steam turbine, a means for measuring / calculating or estimating state quantities such as steam temperature, steam pressure, and thermal stress, a difference between start characteristics and an operation restriction condition, and before starting A method is disclosed that includes a schedule error monitoring unit that monitors a difference from a created startup schedule, and a schedule optimization unit that corrects the startup schedule when the difference exceeds a predetermined value. As a startup schedule correction method, each margin value of schedule error, temperature increase rate, and thermal stress is evaluated, and the manipulated variable of the temperature increase rate and the pressure increase rate is corrected according to the combination of each margin value. The amount of correction is determined by fuzzy inference.

JP 09-317404 A JP 2006-257925 A JP 2009-281248 A Japanese Patent Laid-Open No. 03-164804 JP 02-272203 A

  Although these conventional methods can be expected to have a certain effect on shortening the start-up time of the plant, as a further problem, a solution method is not always clearly shown for the following points.

  In the method of Patent Document 1, the above-described manipulated variable adjusting means for eliminating the deviation between the predicted value of the plant state quantity and the measured value operates based on the current time. For this reason, during the plant start-up, there is an effect that the manipulated variable is adjusted based on the difference between the predicted value of the state quantity and the actually measured value (hereinafter referred to as state quantity deviation). However, in the case where the same tendency is deviated every time the plant is started, the adjustment of the plant operation amount repeats the same process every time it is started, and there is a certain limit to the improvement of the control accuracy. is there. The same applies to the method of Patent Document 2.

  The methods such as Patent Documents 2 and 3 together with the method of Patent Document 1 require a detailed prediction model in order to predict the plant state quantity. For this reason, as typically shown in Patent Document 2, it is necessary to construct in advance a complicated calculation procedure that often requires advanced knowledge. Similarly, as shown in Patent Document 2, in the process of adjusting the plant operation amount, it is necessary to repeat the optimization calculation in order to calculate the operation condition that does not exceed the constraint condition for plant operation. May increase.

  The method of Patent Document 4 does not require a detailed prediction model for predicting the plant state quantity as in Patent Documents 1-3 described above, and is a typical example that is substituted by an artificial intelligence method instead. In this example, the storage means has a back-propagation type neural circuit model, and the correction means determines the correction amount according to fuzzy theory. However, in order to actually apply these artificial intelligence methods, not only advanced technical knowledge and experience on the methods are required, but also knowledge and experience on the target area (plant-wide phenomena including control responses) and Furthermore, know-how and labor are required to generalize these and convert them into formal knowledge that can be processed.

  For example, in this example, a knowledge base is used for the above-mentioned correction rule, but this knowledge base is constructed as a collection of fragmentary knowledge that expresses the qualitative knowledge possessed by the subject area expert so that it can be processed by a computer. This requires both know-how and effort in both knowledge processing and target areas.

  Neural network models used for evaluating plant behavior need to prepare a large amount of teacher data in advance to learn knowledge, which requires specialized knowledge, know-how, and labor. In addition, these artificial intelligence methods generally do not explicitly and statically specify the causal relationship of the output to the input in advance, and because they are dynamically learned by mechanical iterative processing, the difference between prediction and actual measurement is Regarding the various uncertain factors to be generated, it is difficult to preliminarily consider the controllability prior to actual operation, to what extent the factors are actually considered and calculated.

  The method of Patent Document 5 uses an artificial intelligence method as in Patent Document 4 described above, but the causal relationship between the output and the input when the manipulated variable is corrected is that the schedule error / temperature increase rate is as described above. The difference is that it is statically determined in advance such that the operating amount of the temperature rise rate and the step-up rate is corrected by inputting each margin value of the thermal stress. However, in this example as well, as shown in the example of Patent Document 1 described above, there is a limit to improvement in control accuracy with respect to a case where the same tendency is deviated every time the plant is started. The reason is that the control of this example dynamically operates during the startup of the boiler as in Patent Document 1, and the membership of the fuzzy inference unit in which the response characteristic of the correction amount with respect to the operation amount is predetermined. This is because there is no learning function that is determined by the function and is corrected according to the tendency of the measured data.

  As shown in these Patent Documents 4 and 5, when the artificial intelligence method takes an approach that does not explicitly or statically specify the causal relationship of the output with respect to the input in advance, there are various methods that produce the difference between the prediction and the actual measurement. As for uncertain factors, it becomes difficult to grasp what kind of factors can be calculated and calculated, and on the contrary, when taking the approach of prescribing causal relations statically in advance, the plant tends to be similar every time. It becomes difficult to learn from actual measurement data for such a situation.

  Furthermore, in the power plant fast start-up for system power stabilization as described in the background art, it is strongly required to reach the required power generation amount, that is, the load at the required time. However, a method for determining the time to reach the required power generation amount is not disclosed.

  The present invention is an invention for solving the above-mentioned problems, and in a high-speed start-up of a power plant having a steam turbine, by limiting a limiting factor such as a thermal stress or a thermal expansion difference within a limit value, When providing a steam turbine start-up control system that can reach the required load at the required time while maintaining safety, the plant does not require advanced knowledge of the phenomena inside the plant or complicated calculation models. It is an object of the present invention to provide a steam turbine control device that can effectively suppress a deviation between planning and actual start-up and can start up a plant at high speed.

  In order to achieve the above object, the steam turbine control device of the present invention has a manipulated variable planned value (for example, manipulated variable master curve 25) that is a planned value of change in the manipulated variable to the operating end for starting the steam turbine plant. And a state quantity plan value (for example, a state quantity master curve 21) that is a plan value of the state quantity for the operation state associated with the operation quantity, and a conversion value (for example, for calculating the operation quantity from the state quantity in advance) A conversion matrix A) and a database (for example, MCDB220), and when starting, a steam turbine state quantity measuring device (for example, a flow meter 3, a main steam pressure gauge 15, a main steam thermometer) every predetermined time 16, the measured value is obtained as a state quantity actual value (for example, the state quantity acquisition value 22) from the steam turbine thermal expansion difference meter 17), the state quantity plan value is obtained from the database, A state quantity obtaining unit (for example, state quantity obtaining unit 18) for calculating a state quantity deviation (for example, state quantity deviation 23), which is a deviation based on the state quantity planned value and the state quantity actual value, and a predetermined time interval. The operation amount plan value (for example, the operation amount master curve 25) is acquired from the database, the state amount deviation is acquired from the state amount acquisition means, and the operation amount associated with the state amount based on the state amount deviation and the converted value. Is calculated as an operation correction amount (for example, an operation correction amount 27b), and an operation amount determination means (for example, an operation amount to the operation end is determined based on the acquired operation amount plan value and the calculated operation correction amount). And an error for evaluating the converted value based on the operation correction amount calculated by the plant operation amount determination means 19) and the operation amount determination means at every predetermined time and the state amount deviation calculated by the state amount acquisition means. A database management unit (for example, master curve management unit 20) that calculates a corrected conversion value that is corrected and stores it in a database, and the manipulated variable determination unit next activates the corrected conversion value It is used when performing.

  According to the present invention, in the high-speed start-up of a power plant having a steam turbine, the required time while maintaining the safety of the equipment by suppressing the limiting factors such as thermal stress and thermal expansion difference within the limiting value. When providing a steam turbine start-up control system that can reach the required load, there is no need for advanced knowledge of the phenomena inside the plant or complicated calculation models. The plant can be started at high speed with effective suppression.

It is a lineblock diagram showing the steam turbine starting control system concerning the embodiment of the present invention. It is explanatory drawing which shows the relationship between the operation amount master curve and the state amount master curve. It is explanatory drawing which shows the conversion matrix used by a master curve management means. It is a processing flowchart which shows correction | amendment of the operation amount master curve by a master curve management means. It is explanatory drawing which shows the example of correction | amendment of the operation amount master curve. It is a block diagram which shows the access form to master curve DB in a master curve management means. It is explanatory drawing which shows the analysis result of the factor which produces the deviation with respect to the master curve of the operation amount and the state quantity.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
[Embodiment 1]
FIG. 1 is a configuration diagram showing a steam turbine start control system according to an embodiment of the present invention. The lower part of FIG. 1 shows a steam turbine 12 that is an object of start control. The heat medium 1 is put into the heat source device 4 for the purpose of generating steam that is a driving source of the steam turbine 12. The flow path of the heat medium 1 is provided with a flow rate adjusting valve 2 for the heat medium 1 and a flow meter 3 for measuring the flow rate. The heat medium 1 is put into the heat source device 4, and the heat source device 4 moves the amount of heat held in the heat medium 1 to the heat medium 5 by chemical or physical operation, and sends the heat medium 5 as a heat source for generating steam. To do. The heat medium 5 is put into the steam generation facility 6, and the retained heat amount is transmitted to the water supply 7 through the heat transfer pipe 8. The flow rate of the main steam 9 generated in the heat transfer tube 8 is adjusted by a main steam flow rate control valve 10. Surplus steam flows out to the main steam bypass valve 11. Downstream of the main steam flow control valve 10, the main steam is input to the steam turbine 12 to drive the turbine, and the generator 13 generates electricity.

  A control device 14 is installed to control these devices. The control device 14 includes a state quantity acquisition unit 18, a plant operation amount determination unit 19 (operation amount determination unit), a master curve management unit 20 (database management unit or management unit), functions or arithmetic circuits 31 and 32, a master curve DB ( MCDB) 220 (database). The master curve management means 20 has a state quantity deviation calculator 24 and an operation correction quantity calculator 28 which will be described later. DB is an abbreviation for database.

  The state quantity acquisition means 18 is measured by a measured value indicating the state of the steam turbine system, for example, a flow meter 3 of the heat medium 1, a main steam pressure gauge 15, a main steam thermometer 16, a steam turbine thermal expansion difference meter 17, and the like. The received value is received as the state quantity acquisition value. Here, the state acquisition value includes not only an actually measured value but also a value calculated based on the measured value and an estimated value. The measured values include those that can be measured and handled in addition to the examples of wiring shown in the figure, such as the metal temperature of the steam turbine casing, typically the inner and outer walls. In the case where the temperature difference or the heat source device 4 is a gas turbine, there are atmospheric temperature, pressure and humidity.

  The plant operation amount determination means 19 receives the state quantity acquisition value signal transmitted from the state quantity acquisition means 18. In the plant operation amount determination means 19, an arithmetic circuit for calculating various operation amounts necessary for operation control of the plant is mounted based on a known control method such as PID control, and the operation amount calculation result is expressed as a function. Alternatively, the data is output to the arithmetic circuits 31 and 32.

  The function or calculation circuit 31 that has received the operation amount calculation result generates and outputs a command signal for the flow rate control valve 2 of the heat medium 1, and the function or calculation circuit 32 outputs the command signal for the main steam flow rate control valve 10. In this way, the flow control valve 2 and the main steam flow control valve 10 of the heat medium 1 of the plant are operated.

  As a feature of the control device 14 of the present invention, an actual state quantity acquisition value at the time of starting the plant acquired by the state quantity acquisition unit 18 and an operation amount generated by the plant operation amount determination unit 19 at this time are received as inputs. A master curve management means 20 for correcting a planned value of the change over time of the operation amount for starting the plant is provided.

  In the MCDB 220, the state amount master curve 21 (state amount MC) (see FIG. 2), the operation amount master curve 25 (operation amount MC) (see FIG. 2), and the conversion matrix A (see FIG. 2) managed by the master curve management means 20 are stored. 3) is stored.

  The control device 14 of the steam turbine startup control system according to the present embodiment includes the master curve management means 20, so that the operation amount master curve of the plant (based on the actual operation difference with respect to the original plan at the time of startup) For example, it is possible to correct the operation amount master curve 25 (see FIGS. 2 and 5). Thereby, the precision of the starting control of a plant can be improved.

  The state quantity acquisition means 18, the plant operation amount determination means 19, the master curve management means 20, and the function or calculation circuits 31, 32 described as elements provided in the control device 14 function to explain the main flow of information. In the mounting, it is not necessary to be divided into separate circuit boards, and may be integrated.

  In the present embodiment, the contents of the master curve management means 20 will be described below. Prior to detailed description, the idea of the present invention and the calculation model that forms the core of the algorithm derived from the concept will be described.

  FIG. 2 is an explanatory diagram showing the relationship between the operation amount master curve and the state amount master curve. The concept of the present invention will be described with reference to FIG. FIG. 2 schematically shows changes over time in the operation amount (graph in FIG. 2A) and the state amount (graph in FIG. 2B) at the time of starting the plant. As shown in the graph of FIG. 2A, when the plant is started, generally, a change in the operation amount with time is planned or predicted in advance. In the present embodiment, this is called an operation amount master curve 25 (operation amount MC).

  On the other hand, in the actual start-up of the plant, the transition of the actual operation amount of the plant (referred to as the operation amount acquisition value 26) slightly differs from the planned value due to various factors. This difference is referred to as an operation amount deviation 27a or an operation correction amount 27b in this embodiment. These two names are used properly depending on the reason for the difference between the planned value and the actual value. When this difference is mainly due to fluctuations in operating conditions that do not depend on the control intention, the manipulated variable deviation 27a is used. On the other hand, when an active operation amount change caused based on the control operation is expressed, it is referred to as an operation correction amount 27b. Examples of the operation amount include the load factor of the heat source device 4 and the opening degree of the main steam flow control valve 10, but are not limited to these, and the operation amount at an arbitrary operation end for the plant corresponds to this. .

  As shown in the graph of FIG. 2 (b), similarly for the state quantity of the plant, when the plant is started up, a transition with time is predicted or planned in advance, or a change in limit value with time is set. Have been. The time change of the predicted value, the plan value, the set value, etc. of the state quantity at the time of start-up is the state quantity master curve 21 (state quantity MC), and the time change of the plant actual measurement value corresponding thereto is the state quantity acquisition value 22, In addition, the difference between the two is referred to as a state quantity deviation 23 in this embodiment.

  Examples of the state quantity include rotor thermal stress, thermal expansion difference between the passenger compartment and the rotor, and temperature difference between the outer walls of the passenger compartment, but are not limited to these, and the measured value at an arbitrary measurement point representing the operating state of the plant. (For example, steam pressure and steam temperature), an instruction value or estimated value (for example, a load factor of plant equipment) of the operating state, or an evaluation value calculated by combining these.

  The inventors obtained the following idea from the relationship between the master curve of the operation amount and the state amount and the plant data at the time of actual start-up. That is, if the operation amount is corrected so that the state amount deviation 23 is minimized and the operation amount master curve 25 for activation can be corrected, improvement in controllability at the time of activation can be expected.

  However, in order to realize this, it is necessary to be able to calculate the causal relationship of phenomena inside the plant from the opposite direction to the mathematical model of normal physical phenomena. In the example of this figure, in the forward calculation according to the physics side, a physical phenomenon inside the plant is modeled with an operation amount acquisition value 26 obtained by adding some correction or deviation to the operation amount master curve 25 as an input. As a result, a calculation output corresponding to the state quantity acquisition value 22 is obtained.

  On the other hand, in the reverse calculation, it is necessary to estimate the actual operation amount at that time based on the measured state quantity acquisition value 22. Such a problem is generally called an inverse problem. Especially when there are many inputs and outputs and the number of input and output items often do not match as in a plant, the solution cannot be uniquely determined mathematically. Advanced knowledge and experience are required to obtain reasonable solutions in numerical calculations.

  Therefore, the inventors examined the problem in more detail as (1) to (4) below, and devised a solution to this problem.

(1) Analysis on inverse problem In many cases, a multi-input multi-output system such as a plant is often difficult to convert so that the input response to the output can be calculated by reversing the relationship of the output response to the input. This is mainly because 1) there are many regions where the response of input / output is nonlinear, and 2) various physical quantities of different scales are mixed.

  On the other hand, the manipulated variable deviation 27a and the state quantity deviation 23 to be targeted by the present invention both represent deviations from the reference of the master curve, and the fluctuation range in the positive and negative directions centering on zero (0). Is limited to a certain range. For this reason, it is easy to align the scales of different variables by, for example, normalizing the range from the minimum value −1 to the maximum value +1. Considering such properties, there is room for the relationship between the manipulated variable deviation 27a and the state variable deviation 23 to be linear.

(2) Analysis of factor causing deviation FIG. 7 is an explanatory diagram showing an analysis result of a factor causing deviation of the manipulated variable / state quantity with respect to the master curve. As a result of analyzing the factors causing the deviation of the manipulated variable and the state quantity from the master curve, it is estimated that all the factors causing the deviation have the characteristics of addition or multiplication as shown in FIG. It was. Here, addition or multiplication means that if a deviation occurs between the planned value and the actual value due to a certain factor, if the planned value is corrected based on the actual value, either correction method of addition or multiplication is roughly used. Indicates whether it is suitable.

The contents of FIG. 7 will be described individually.
Reference number 1: “Error in characteristic model that is the basis for creating each master curve of manipulated variable / state variable” is a calculation model of the response relationship of state variable output with respect to the manipulated variable input of the plant, which is used in plant start-up planning (Physical formula, simulation, etc.) and the difference caused by the difference between the actual plant. This includes 1) when the responsiveness of the change in the state quantity output value corresponding to the change in the manipulated variable input value is shifted, and 2) regardless of the change in the manipulated variable input value, the state quantity output value is always It may be displaced in a certain direction. For the correction in the case of 1), multiplication such as multiplying the change width of the response by a certain coefficient is suitable, and in the case of 2), the addition such as adding a certain value is suitable.

Reference number 2: “Individual difference of plant / equipment” represents a case where the measured value of the obtained device is always shifted in a certain direction due to a manufacturing tolerance or a difference in sensor adjustment. For such a deviation, correction of addition is suitable.

Reference number 3: “Effect of maintenance / deterioration” represents a deviation due to factors such as deterioration in performance over time or performance recovery due to maintenance. Such deviations are suitable for correction of additivity, because when the difference in operating conditions is corrected to match standard operating conditions, the measured value tends to shift to a constant tendency.

Reference number 4: “Difference in initial warm-up state (when a certain tendency is always reproduced)” indicates how long the plant was warmed at the start of start-up, and persisted during the start-up process due to differences in heat insulation and warm-up state Represents a deviation that occurs with a certain width. In such a case, the initial temperature serving as a reference is often shifted, and correction of addition is suitable.

Reference number 5: “Difference in initial warm-up state (when the tendency of deviation is different every time)” represents a case where the degree of warming of the plant at the start of the start is similarly different but this deviation is different every time. In such a case, it is often caused by variations in operating conditions (in a broad sense) such as an elapsed time after the plant is shut down, a warming state before startup, and a degree of warm-up. As a correction method, since there is no fixed tendency, correction of addition is not appropriate. For example, correction of multiplication is suitable, for example, correction is performed by applying a constant according to the deviation from the standard value of the warm-up time.

Reference number 6: “Fluctuation of environmental conditions such as atmospheric temperature (if it changes every time the engine is started)” is typically related to the intake temperature of the gas turbine in a combined cycle thermal power plant having the steam turbine 12 as a component. Applicable. The output and efficiency of the gas turbine have characteristics that vary greatly depending on the atmospheric temperature. As a result, the condition of the steam supplied to the steam turbine 12 of the combined cycle plant changes. For such a deviation, it is suitable to correct for multiplication such as multiplying a certain number according to the deviation of the atmospheric temperature from a predetermined standard value.

Reference number 7: “Changes in environmental conditions such as atmospheric temperature (large change during start-up)” corresponds to the intake temperature of the gas turbine of the combined cycle plant, as in reference number 6. The difference is that the deviation is dynamically caused by the change in the intake air temperature even during the starting process. For such a deviation, as in the case of reference numeral 6, it is suitable to correct the multiplication property by applying a constant according to the deviation with respect to a predetermined standard temperature. In order to carry out the correction with higher accuracy, it is effective to set a standard temperature rise pattern or the like and correct it accordingly.

  The analysis results of these reference numbers 1-7 are summarized as follows. The item of reference numbers 1-4 is mainly due to the difference from the actual model of the characteristic model, and the addition method is suitable for the correction method. The item of reference number 5-7 is mainly centered on the deviation due to the difference in operating conditions, and the correction method is suitably multiplicative.

(3) Modeling policy based on deviation factor analysis From the analysis result of (1) described above, the relationship between the manipulated variable deviation 27a and the state quantity deviation 23 has room to be regarded as linear, and further from the analysis result of (2) The correction method for each factor causing a deviation is expected to be realized to some extent by a combination of multiplication for fluctuations in operating conditions and addition for differences between the characteristic model and the actual machine.

  However, in a multi-input multi-output response system, the number of input items is not always the same as the number of output items. In such a case, the output response to the input is mathematically calculated using a matrix. Even if it can be expressed as possible, since there is no inverse matrix for the matrix representing the response, the response relationship cannot be converted to an input relationship with respect to the output in the reverse direction. For example, although it is possible to obtain a pseudo inverse matrix by a technique such as singular value decomposition, specialized knowledge and experience are required to guarantee the accuracy and stability of the model thus calculated.

  In order to avoid such difficulties, the algorithm of the present invention represents the input / output response relationship of the process in the reverse direction from the beginning, as an input / output relationship. That is, for example, the response coefficient of the output Y with respect to the input X is expressed as Y / X in a simplified manner in the conventional general method, whereas in the method of the present invention, the coefficient is referred to as X / Y. It represents as follows.

  When expressing such a response relationship, the operation amount deviation 27a is assumed to be a scalar Δx and the state amount deviation 23 is assumed to be a scalar Δy. The response coefficient (scalar a) is expressed as a = Δx / Δy. The coefficient a can be used to obtain an operation amount deviation Δx (or operation correction amount Δx) corresponding to the coefficient a by multiplying the state amount deviation Δy. In this respect, the coefficient “a” corresponds to the correction of the multiplication property corresponding to the variation of the operating condition described above. On the other hand, the correction of the addability corresponding to the difference between the characteristic model and the actual machine described above can be expressed as adding a certain constant (for example, scalar c).

  Therefore, an equation for calculating the operation correction amount Δx corresponding to the state amount deviation Δy by combining these two corrections can be approximately expressed as Δx = aΔy + c. This equation can also be used to obtain a coefficient a and an intercept c that specify the relationship between the manipulated variable deviation Δx and the state quantity deviation Δy based on actual operation data of the plant.

(4) Calculation Modeling The policy of (3) above is generalized, and the response relationship of the operation amount deviation 27a (or operation correction amount 27b) corresponding to the state amount deviation 23 is expressed by the following equations (1a) and (1b). A calculation model was created as shown in FIG. The expression (1a) is expanded when there are a plurality of these items for the state quantity deviation Δy and the operation quantity deviation (or operation correction quantity) Δx, and the state quantity deviation vector ΔY and the operation quantity deviation (or operation quantity respectively). This represents a model formula when expressed as a correction amount) vector ΔX. (Note that in the description of the invention, lowercase variables represent scalars and uppercase variables represent vectors).

  Corresponding to the fact that the number of items of the state quantity deviation 23 and the operation quantity deviation 27a (or the operation correction quantity 27b) is expanded to a plurality, the coefficient of multiplication correction shown as the scalar a in the above (3) is stored in the matrix A. Has been extended. This is hereinafter referred to as a transformation matrix. Similarly, the constant for addition correction shown as scalar c in (3) above is extended to vector C. This is hereinafter referred to as an offset vector. The relationship between the row and column elements of the transformation matrix A will be described with reference to FIG.

FIG. 3 is an explanatory diagram showing a conversion matrix used in the master curve management means. In the transformation matrix A, the number of rows is the number of elements of the operation correction amount 27b, and the number of columns is the number of elements of the state quantity deviation 23. For example, the element a_ij in the i-th row and j-th column (the symbol _ indicates that the subsequent symbol is a subscript) is the operation correction amount 27b (operation) for the j-th element Δy_j of the state quantity deviation 23. It represents the coefficient of the response relationship of the i-th element Δx_i of the quantity deviation 27a), and these relationships are
Δx_i = Σ_j (a_ij Δy_j) + c_i
It has become. Note that i is the item number of the operation correction amount 27 b, and j is the item number of the state amount deviation 23.

  Here, a feature of the present invention is that a_ij is regarded as constant regardless of the plant operation time. This is because even if the i-th element Δx_i of the operation correction amount 27b and the j-th element Δy_j of the state quantity deviation 23 change according to the step size Δt of time progress, the ratio a_ij between them is substantially constant. This is due to the fact that Δx_i and Δy_j are assumed to be linear based on the operating characteristics of the steam turbine 12.

  In this calculation model, elements included in the state quantity deviation vector ΔY are desirably combined with variables having high independence and low dependency. As a simple example of a suitable combination, a rotor thermal stress, a difference in thermal expansion between the vehicle interior and the rotor, a temperature difference in the exterior wall of the vehicle interior, or a combination of only the former two of these can be considered. It is necessary to combine variables that are independent of each other in this way. If a variable with high interdependency is included in the combination, the multicollinearity in the matrix calculation becomes strong, and the accuracy and stability of the calculation of the model formula This is because of a decrease.

  By expanding the system to handle multiple items at the same time, this model formula incorporates the effects of various factors that cause the plant behavior to deviate from the planned values, that is, the various factors listed in FIG. Thus, it is possible to calculate the correction amount of the plant operation amount so as to reduce the deviation of the plant state amount.

  Further, in this calculation model, as described in (3) above, the input / output response relationship is deliberately defined from the reverse direction and expressed as a conversion coefficient, thereby enabling the operation amount correction vector element, that is, for operating the plant. The degree of freedom in selecting a combination of variables is improved as compared with the case where the response is modeled in the forward direction. As a result, it becomes possible to perform control by combining more operation amounts, and it can be expected that controllability is improved.

The reason why the degree of freedom of variable combination is improved is that when the relationship between the manipulated variable correction vector ΔX and the state variable deviation vector ΔY is modeled using a conventional general input / output forward response relationship,
ΔY = PΔX + Q
Where Δ is a vertical vector, P is a matrix representing a response, and Q is an offset. In this matrix operation, ΔX is multiplied by a matrix on the right side. This is because a combination of elements that are highly independent from each other is required, and if elements having high obeying attributes are included, a problem of multicollinearity occurs.

The calculation model of this embodiment is shown in the following equation.

  In contrast to the above problem, in the calculation model shown in Equation (1a), the manipulated variable correction vector ΔX is on the output side of the left side and does not become the input side of the matrix operation (need to be an independent variable). There is no problem and the restriction of variable combinations can be eliminated.

  It should be noted that equation (1a) of the calculation model of the present embodiment may be simplified and replaced with equation (1b) except for the offset vector C. By doing so, it is possible to effectively correct the correction of the multiplicity as previously indicated by reference numerals 5-7 in FIG. 7, that is, the correction of the responsiveness of the deviation caused by the fluctuation of the operating condition. .

  In the master curve management means 20 (see FIG. 1) provided in the steam turbine start control system, the operation amount master is actually calculated using the equation (1a) or (1b) of the calculation model derived as described above. Whether to correct the curve will be described with reference to FIG.

  FIG. 4 is a processing flowchart showing the correction of the operation amount master curve by the master curve management means. With reference to FIG. 4, the process flow in which the operation amount master curve is corrected inside the master curve management means 20 (FIG. 1) will be described.

  Here, the correction of the operation amount master curve (operation amount MC) is, as shown in FIG. 5, corrected operation amount master curve based on the actual operation result with respect to a predetermined operation amount master curve 25. A curve 25m is generated. This procedure will be described below.

  The process indicating the correction of the manipulated variable master curve is divided into step S40A for acquiring plant characteristic data and step S40B for correcting the manipulated variable master curve. Step S40A is composed of steps S41 to S45, and step S40B is composed of steps S46 to S49.

  When the master curve management means 20 detects the start of the start of the steam turbine 12 by the start signal of the control device 14 or the like (step S41, True), the master curve management means 20 proceeds to step S42. When the master curve management means 20 cannot detect the start of the start of the steam turbine 12 (step S41, False), the process returns to step S41. The master curve management means 20 reads the conversion matrix A and the offset vector C from the MCDB 220 (step S42), and acquires the operation correction amount ΔX and the state amount deviation ΔY from the plant startup actual measurement data (step S43). Specifically, the change along the time of the operation correction amount ΔX at the time of starting the plant and the change along the time of the state amount deviation ΔY corresponding thereto are acquired.

  The data of the operation correction amount ΔX is acquired based on information received from the plant operation amount determining means 19 (see FIG. 1). As the procedure, the information received from the plant operation amount determination means 19 includes an operation amount master curve and a correction amount corresponding thereto or a value of an actual operation amount during plant operation (collectively referred to as an operation amount actual value). The difference between the operation amount master curve and the actual value is calculated and acquired by the operation correction amount calculator 28 (see FIG. 1) provided in the master curve management means 20.

  The data of the state quantity deviation ΔY is acquired based on information received from the state quantity acquisition unit 18 (see FIG. 1). As the procedure, the information received from the state quantity acquisition means 18 includes a state quantity master curve and an actual measurement value or a calculated value or an estimated value (collectively referred to as a state quantity actual value) during actual plant operation. The difference between the state quantity master curve and the actual value is calculated and acquired by the state quantity deviation calculator 24 (see FIG. 1) provided in the master curve management means 20.

  The operation correction amount calculator 28 and the state amount deviation calculator 24 have been described as being in the master curve management means 20, but are not necessarily limited thereto. For example, the operation correction amount calculator 28 may be in the plant operation amount determination unit 19, and the state amount deviation calculator 24 may be in the state amount acquisition unit 18.

  Specifically, with reference to FIG. 1, an operation amount plan value that is a planned value of a change in the operation amount to the operation end for starting the steam turbine plant is stored in the database (MCDB 220) of the control device 14. (For example, the operation amount master curve 25) and the state amount plan value (for example, the state amount master curve 21) that is the planned value of the state amount for the operation state associated with the operation amount, and the operation amount are calculated in advance from the state amount. The conversion value (for example, conversion matrix A) used for performing is stored.

  When starting, the state quantity acquisition means 18 measures a state quantity of the steam turbine 12 every predetermined time (for example, a flow meter 3, a main steam pressure gauge 15, a main steam thermometer 16, a steam turbine thermal expansion difference meter). 17), a measured value is acquired as a state quantity actual value (for example, state quantity acquisition value 22), and a state quantity plan value (for example, state quantity master curve 21) is acquired from the database. The state quantity deviation calculator 24 calculates a state quantity deviation (for example, a state quantity deviation 23), which is the deviation, based on the acquired state quantity planned value and state quantity actual value.

  The plant operation amount determination means 19 acquires an operation amount plan value (for example, the operation amount master curve 25) from the database every predetermined time, and acquires a state amount deviation from the state amount acquisition means. The operation correction amount calculator 28 calculates the operation amount correction amount associated with the state amount as the operation correction amount (for example, the operation correction amount 27b) based on the state amount deviation and the conversion value (for example, the conversion matrix A). To do. The plant operation amount determination means 19 determines the operation amount to the operation end based on the acquired operation amount plan value and the calculated operation correction amount.

  Returning to FIG. 4, in step S43, the operation correction amount ΔX and the state amount deviation ΔY are vectors having the number of items (for example, the operation correction amount ΔX is the M item, and the state amount deviation ΔY is the N item). Assuming that the number of time divisions is τ, the operation correction amount ΔX is M × τ, and the state amount deviation ΔY is N × τ. Specifically, if the time from the start to the start completion time is 60 minutes and the predetermined time is every minute, the operation correction amount ΔX is M × 60 pieces and the state amount deviation ΔY is N × 60 piece of element data. Is acquired.

  When the master curve management means 20 detects the start end of the steam turbine 12 based on the start end signal of the control device 14 or the like (step S44, True), the master curve management means 20 proceeds to step S45. When the master curve management unit 20 cannot detect the end of the start of the steam turbine 12 (step S44, False), the process returns to step S43.

  Subsequently, in step S45, based on the values of the operation correction amount ΔX and the state amount deviation ΔY acquired in step S43, the values of the transformation matrix A and the offset vector C in the calculation model equation (1a) are calculated.

Specifically, with respect to the operation amount deviation Δx_i, an evaluation formula of the error Err when modeled by the above-described formula (1a) is defined as, for example, the sum of squared errors shown in the following formula.

  As shown in equation (2a), error Err is evaluated by integrating along the time during startup, and the evaluation value is minimized, that is, the calculated value on the left side of equation (3a) is near zero. The values of each element a_ij of the transformation matrix A and each element c_i of the offset vector are obtained. This calculation can be performed by various known optimization calculation algorithms such as a least square method and a gradient method. The above is step S40A which acquires plant characteristic data.

  In addition, when the equation (1a) of the calculation model of the present embodiment is simplified and expressed as the equation (1b) except for the offset vector C, the error Err is expressed by the equation (2b) as follows: Integrating and evaluating along the time during startup, that is, a condition that minimizes the evaluation value, that is, each element a_ij of the transformation matrix A such that the calculated value on the left side of the expression (3b) is near zero A value is determined.

  Next, in step S40B for correcting the manipulated variable master curve, the manipulated variable master curve is corrected based on the values of the conversion matrix A and the offset vector C obtained in step S45 and the data during actual plant operation. . The procedure will be described.

  The master curve management means 20 acquires the state quantity deviation ΔY along the startup process from the plant actual measurement data (step S46). Specifically, in step S46, based on the state quantity information acquired by the state quantity acquisition unit 18 (see FIG. 1) at the time of plant startup, the state quantity deviation along the startup time is determined as the master curve management unit 20. Is calculated by the state quantity deviation calculator 24 (see FIG. 1). The state quantity deviation ΔY here includes a deviation from the planned value of the operating condition such as the atmospheric temperature.

  In subsequent step S47, the master curve management means 20 calculates ΔX, which is the operation correction amount, using the above-described model calculation formula (1a) or formula (1b) based on the state quantity deviation ΔY obtained in step S46. calculate. Since ΔX in this case is different from the operation amount deviation 27a shown in FIG. 2, the operation correction amount is 27m (see FIG. 5). Subsequently, at step S48, the master curve management means 20 adds the value along the time of the operation correction amount 27m obtained at step S47 along the time to the existing operation amount master curve to be corrected this time, The operation amount master curve (X_mc) is corrected. Finally, in step S49, the master curve management means 20 writes the corrected manipulated variable master curve 25m (see FIG. 5) in the MCDB 220.

  Note that step S40B is not always executed as a set with step S40A, and may be performed at any timing as long as the transformation matrix A and the offset vector C obtained by step S40A are present. Typically, in the initial period after the start-up of a new plant, if the plant is started at the timing after the startup is completed, the difference between the planned time of the plant and the actual equipment is effectively corrected. can do. Alternatively, in a situation where a certain period of time has elapsed after the start of plant operation and the values of the conversion matrix A and the offset vector C obtained each time the plant is started up are small and the necessity for change is low, the number of executions can be reduced by reducing the number of executions. Start-up can be stably optimized according to the actual operating environment.

Furthermore, in the step S45 of FIG. 4, the following equation considering the load characteristics can be used. Instead of using Formula (2a) and Formula (3a), Formula (4a) and Formula (5a) may be used.

In the equation (4a), the value of the element a_ij of the conversion matrix A is dynamically calculated in consideration of the influence of the heat source device 4 (see FIG. 1) or the load factor (represented as λ) of the plant. ing. That is, correction according to the load factor λ is introduced in the form of a Kth order polynomial using the correction coefficient b_ijk, and the value of the element a_ij of the transformation matrix A is
a_ij = Σ_k (b_ijk * λ ^ k)
Is calculated as

  Equation (5a) represents a condition that minimizes the sum of squared errors of Equation (4a), and the values of the elements of constants b_ijk and c_i such that the calculation result on the left side is close to zero are known. What is necessary is just to be solved by an optimization method. In this way, in the calculation method using the equations (4a) and (5a), a phenomenon having a dependency such that the characteristics change depending on the load factor can be modeled with higher accuracy by incorporating the load characteristics. As a result, the calculation of the deviation of the actual value can be calculated more precisely, and the accuracy of the start control is improved.

  In particular, when the steam turbine 12 is started, the response characteristics of the equipment may be load-dependent when the load is low at the initial stage of the start and near the rated load near the start of the start. By correcting the difference in response due to such a load, the controllability (accuracy) at the time of reaching the rated load and completing the start-up can be improved.

  In addition, when the equation (1a) of the calculation model of the present embodiment is simplified and expressed as the equation (1b) except for the offset vector C, the error Err is expressed by the equation (4b) as follows: It is evaluated by integrating along the running time. A condition that minimizes the evaluation value, that is, the value of the element of the constant b_ijk so that the calculated value on the left side of Equation (5b) is close to zero may be obtained by a known optimization method.

  In the method of Formula (2b) and Formula (3b) according to Formula (1b), the method of Formula (4b) and Formula (5b), the method of Formula (2a) and Formula (3a) according to Formula (1a), Formula (4a) ) And formula (5a), the calculation amount can be reduced and the calculation can be efficiently performed at high speed. In addition, since the offset vector C is not included in the equations of the entire system when performing the numerical calculation for obtaining the transformation matrix A, the number of unknowns is small, and a more stable and robust value (the value of the transformation matrix A, and consequently It can be expected that the operation amount master curve correction result) will be obtained.

  FIG. 6 is a configuration diagram showing an access form to the master curve DB by the master curve management means. This will be described with reference to FIG. With reference to FIG. 6, a mechanism for registering and using a master curve inside the master curve management means 20 will be described. The master curve is registered as follows. When the process shown in FIG. 4 is executed when the plant is activated, a corrected master curve 211 (corrected MC), which is a corrected master curve, is newly acquired. The information of the correction master curve 211 is transferred to the MCDB 220, which is also the database of the master curve management means 20, via the registered I / F (interface) 221 provided in the master curve management means 20, and stored. The

  The master curve is used as follows. When the plant is about to be started up or when the start-up of the plant is planned, information on the start-up condition 231 of the plant is acquired in the master curve management means 20 (FIG. 1). Received at (interface) 222.

  The information of the start condition 231 includes, for example, an initial metal temperature (a temperature at a measurement point of a steam turbine casing or a measurement temperature as an index of a rotor temperature), an elapsed time after a stop, a steam temperature, a schedule, or a target There are length of start-up time, atmospheric temperature, fuel properties etc

  Information on these activation conditions 231 is acquired by various input means provided in the control device 14. For example, information such as initial metal temperature, steam temperature, and atmospheric temperature is acquired from the state quantity acquisition unit 18 that receives measurement information of the plant. The elapsed time after the stop is acquired based on time information by a clock or timer (not shown in the figure) provided in the control device 14. The length of the scheduled or target start-up time is a value specified by an operation plan setting circuit (not shown in the figure, implemented based on a known operation plan control technique) provided in the control device 14. To be acquired.

  In the acquisition I / F 222, a master curve having a high similarity to the information of the activation condition 231 is extracted from the MCDB 220 and output as information of the activation master curve 232. Here, the master curve extraction from the MCDB 220 is performed by calculating the similarity between the start condition 231 and the similar start condition information included in the master curve information stored in the MCDB 220 (for example, the small temperature difference and the elapsed time after the stop). The closest case is extracted based on the difference). Alternatively, the values of the master curve according to the activation time may be weighted and averaged from a plurality of cases having similar degrees of similarity and output as extraction results. Such extraction based on similarity can be implemented using known multivariate analysis or signal processing techniques.

  By correcting or registering or using the master curve in this way, in the steam turbine start control system of the present invention, the difference between the plant start plan and the actual plant start-up behavior as the plant repeats start-up. And the accuracy of start control is improved. As a result, the accuracy of starting in a specified time is improved while satisfying the constraints on the plant operation.

[Embodiment 2]
Embodiment 2 demonstrates the example which applied the steam turbine starting control system of this invention to the gas turbine combined cycle. The heat source device 4 in FIG. 1 indicates a gas turbine, the heat medium 1 indicates fuel, the valve 2 indicates a fuel control valve or an operation end of a compressor inlet guide vane, the heat medium 5 indicates a gas turbine exhaust gas, steam The generating facility 6 indicates an exhaust heat recovery boiler. Description of other parts having the same configuration and function as those already described with reference to FIG. 1 will be omitted.

  As shown in this embodiment, the steam turbine start-up control system of the present invention not only controls the operation amount of the equipment directly related to the steam turbine 12, but also the operation amount of the equipment of the heat source, that is, the gas turbine fuel flow rate of this embodiment. It can also be used to correct the operation amount of the engine, enables more accurate and flexible control, reaches the required power generation amount at the required time, and limits the state quantities related to equipment safety such as thermal stress and thermal expansion difference of the steam turbine 12. The effect suppressed within the value is obtained.

[Embodiment 3]
Embodiment 3 demonstrates the example which applied the steam turbine starting control system of this invention to the boiler. In FIG. 1, a heat source device 4 indicates a boiler furnace, a heat medium 1 indicates a fuel, a valve 2 indicates a fuel control valve or further an air port, a heat medium 5 indicates a combustion gas, and a steam generation facility 6 has a boiler rear heat transfer. Refers to the face. Description of other parts having the same configuration and function as those already described with reference to FIG. 1 will be omitted.

  As shown in the second embodiment and the third embodiment, the steam turbine start control system of the present invention can be applied to any apparatus using the steam turbine 12, and the original heat medium 1 and the heat medium 5 are used. Although the types of the heat source device 4 and the steam generation facility 6 for conversion into the above are changed depending on the heat source and the system, the present invention can be applied as long as they are applicable to the configuration of FIG. Examples applicable in this way include a solar thermal Rankine cycle plant and a geothermal binary power plant.

  As shown in each of the above embodiments, in the present invention, simple calculations such as model calculation formulas (1a) to (1b) based only on the deviation information between the operation amount at the time of starting the plant and the master curve related to the state quantity. Using the formula, it is possible to improve the startup accuracy of the model. At this time, the advanced predictive model of the plant behavior required by typical conventional technology is unnecessary, and the controllability for shortening the startup time can be improved efficiently with a small calculation load. A state quantity can be suppressed below this with respect to various restrictions in plant operation.

  In each embodiment of the present invention, as the configuration of the control device 14, the master curve management unit 20 is combined with the state quantity acquisition unit 18 and the plant operation amount determination unit 19. For this reason, the control system of the present invention is mainly obtained by adding a calculation circuit corresponding to the master curve management means 20 to the control device installed in the existing power plant without adding a new sensor or the like. Is applicable. In this way, it is possible to reduce the start-up time while minimizing the modification to the existing control system, and to increase the accuracy of reaching the required power generation amount at the required time. State quantities relating to equipment safety, such as thermal stress of the steam turbine 12 and thermal expansion difference, can be suppressed within the limit values.

  Each embodiment of the present invention has shown an example in which the operation amount master curve is corrected collectively after the plant is started, but the operation amount is corrected in real time during the start-up process based on the measured plant values. Needless to say, it may be. In this way, there are two advantages as described below.

  First, in response to a change in environmental conditions during startup (reference numeral 7 in FIG. 7 described above), that is, in response to a change in the state of steam supplied to the steam turbine 12 due to, for example, a change in the atmospheric temperature of the gas turbine, Since it becomes possible to dynamically modify the operation amount master curve, the accuracy of the start control can be improved.

  Second, under conditions where the number of start-ups is limited, such as the trial run period of the plant, the values of the conversion matrix A and the offset vector C can be quickly and accurately identified from actual plant data. The labor and time required for trial run adjustment and evaluation can be reduced.

The characteristics of this embodiment will be described again as follows.
(1) The management means (for example, master curve management means 20) of the steam turbine control device determines a predetermined specified value or a predetermined value for the operation amount to the operation end for starting the steam turbine 12 or the steam turbine plant. The planned value (hereinafter, manipulated variable planned value (for example, manipulated variable master curve 25)) calculated by the determined procedure is acquired, and the actual value during activation (hereinafter, the manipulated variable actual value) is acquired or predetermined. The deviation between the planned value and actual value of the operation amount at the time of starting the plant acquired by the operation amount determination means (for example, the plant operation amount determination means 19) calculated in accordance with the determined procedure (hereinafter, the operation amount deviation 27a or the operation correction amount 27b). ) And a measured value or an estimated value (hereinafter referred to as a state quantity actual value) of the operation state of the steam turbine 12 or the steam turbine plant. In addition, a deviation between the planned value and actual value of the state quantity at the time of starting the plant acquired by the state quantity acquisition means 18 for acquiring a predetermined specified value or predicted value (hereinafter referred to as a state quantity planned value). Based on the above, the manipulated variable planned value is corrected.

(2) The management means of (1) includes a j-th element Δy_j of the state quantity deviation vector ΔY composed of at least one element (the symbol _ is a symbol arranged on the right side of the symbol below) The coefficient of the response of the i-th element Δx_i of the operation correction amount vector ΔX consisting of at least one element corresponding to the subscript)
a_ij = Δx_i / Δy_j
The following calculation model shown in the equation (1a) using the transformation matrix A constituted by the elements: ΔX˜t = AΔY˜t
(The symbol ~ t represents the transposition of the matrix or vector on the left side of the symbol.)
A circuit for calculating the operation correction amount is provided.

(3) In the management means of (1), the j-th element Δy_j of the state quantity deviation vector ΔY consisting of at least one element (the symbol _ is a symbol arranged on the right side of the symbol below) The response coefficient of the i-th element Δx_i of the operation correction amount vector ΔX consisting of at least one element corresponding to the subscript)
a_ij = Δx_i / Δy_j
The following calculation model ΔX ~ t = AΔY ~ t + C ~ t shown in Expression (1a) using the transformation matrix A composed of the elements and the offset vector C composed of at least one element c_i
(The symbol ~ t represents the transposition of the matrix or vector on the left side of the symbol.)
A circuit for calculating the operation correction amount is provided.

(4) The management means of (2) includes an element Δx_i of the operation amount deviation vector ΔX acquired by the operation amount determination means, an element Δy_j of the state amount deviation vector ΔY acquired by the state amount acquisition means, Based on the value of, the calculation model of equation (2b) Err = ∫_t [Δx_i-Σ_j (a_ijΔyj)] ^ 2 dt
(Integration along the symbol ∫_t time, dt is a minute time, Σ_j is addition along the subscript j, and ^ indicates that the right symbol is a right shoulder subscript.)
A circuit for specifying the value of each element a_ij of the transformation matrix A that minimizes the value of Err represented by

(5) The management means of (3) includes an element Δx_i of the operation amount deviation vector ΔX acquired by the operation amount determination means, and an element Δy_j of the state amount deviation vector ΔY acquired by the state amount acquisition means, Based on the value of, the calculation model shown in equation (2a) Err = ∫_t [Δx_i-Σ_j (a_ijΔyj)-c_i] ^ 2 dt
(Integration along the symbol ∫_t time, dt is a minute time, Σ_j is addition along the subscript j, and ^ indicates that the right symbol is a right shoulder subscript.)
A circuit for specifying the values of each element a_ij of the transformation matrix A and each element c_i of the offset vector C so that the value of Err represented by

(6) The management unit of (2) includes an element Δx_i of the operation amount deviation vector ΔX acquired by the operation amount determination unit, an element Δy_j of the state amount deviation vector ΔY acquired by the state amount acquisition unit, Based on the value of, the calculation model Err = ∫_t [Δx_i-Σ_j ((Σ_k (b_ijk * λ ^ k)) Δy_j)] ^ 2 dt
(Integration along symbol ∫_t time, dt is minute time, Σ_j is addition along subscript j, Σ_k is addition up to k = 1, 2,... K along subscript k, b_ijk is subscript i, (scalar constant with j, k, λ is the load factor of the steam turbine 12 or the plant equipped with the steam turbine 12, and ^ indicates that the symbol on the right is a right shoulder subscript.)
A circuit for specifying a value corresponding to each subscript of the constant b_ijk that minimizes the value of Err represented by

(7) The management means in (3) includes an element Δx_i of the operation amount deviation vector ΔX acquired by the operation amount determination means, and an element Δy_j of the state amount deviation vector ΔY acquired by the state amount acquisition means, Is calculated based on the value of Err = _t [Δx_i-Σ_j ((Σ_k (b_ijk * λ ^ k)) Δy_j)-c_i] ^ 2 dt
(Integration along symbol ∫_t time, dt is minute time, Σ_j is addition along subscript j, Σ_k is addition up to k = 1, 2,... K along subscript k, b_ijk is subscript i, (scalar constant with j, k, λ is the load factor of the steam turbine 12 or the plant equipped with the steam turbine 12, and ^ indicates that the symbol on the right is a right shoulder subscript.)
And a circuit for specifying a value corresponding to each subscript of the constant b_ijk and a value of each element c_i of the offset vector C so that the value of Err represented by

  According to the steam turbine start control system of the present embodiment, the change in the state quantity of the plant along the time can be controlled in a range close to the state quantity master curve. Therefore, operating limiting factors such as thermal stress and differential thermal expansion of the steam turbine 12 during startup are suppressed within the limiting values. In addition, since the time-series state quantity of the steam turbine 12 follows the planned line, the load, that is, the power generation amount increases in a state close to the plan, and can follow the target value with high accuracy.

  In addition, if the steam turbine start-up control system of the present embodiment is used in place of a predictive control system that is required in many conventional methods, it is not necessary to use a complicated predictive calculation logic sequentially, so that the control device It is also possible to reduce the 14 computational load.

  In addition, by having multiple state quantity master curves and manipulated variable master curves, the flexibility of control is expanded, and even when other limiting factors are added, the planned power generation is achieved in the planned time while ensuring the safety of the equipment. Can be easily obtained.

  In addition, since the operation amount master curve at the next and subsequent startups can be corrected based on the operation correction amount and state amount deviation at the time of startup, the state that occurs due to the operation amount planned value and the operation conditions The deviation from the planned value of the quantity, and the deviation from the planned value due to individual differences in the plant and changes over time of the characteristics are reduced, and the planned power generation amount can be obtained in the planned time while ensuring the safety of the equipment more accurately. Can do.

  Therefore, when this embodiment is applied, the required power generation amount is reached at the required time by more accurate control, and the state quantities related to equipment safety such as the thermal stress of the steam turbine 12 and the difference in thermal expansion are within the limit values. The effect to be suppressed is obtained.

DESCRIPTION OF SYMBOLS 1,5 Heat medium 2 Flow control valve 3 Flowmeter 4 Heat source device 6 Steam generating equipment 7 Water supply 8 Heat transfer pipe 9 Main steam 10 Main steam flow control valve 11 Main steam bypass valve 12 Steam turbine 13 Generator 14 Control device 15 Main steam Pressure gauge 16 Main steam thermometer 17 Steam turbine thermal expansion difference meter 18 State quantity acquisition means 19 Plant operation amount determination means (operation amount determination means)
20 Master curve management means (database management means, management means)
21 State quantity master curve (state quantity MC)
22 State quantity acquisition value 23 State quantity deviation 24 State quantity deviation calculator 25, 25m Manipulation variable master curve (manipulation variable MC)
26 Operation amount acquisition value 27a Operation amount deviation 27b Operation correction amount 28 Operation correction amount calculator 31, 32 Function or arithmetic circuit 211 Correction master curve (correction MC)
220 Master curve DB (database)
221 Registration I / F
222 Acquisition I / F
231 Startup condition 232 Startup MC
A transformation matrix

Claims (7)

A manipulated variable planned value that is a planned value of a change in the manipulated variable to the operating end for starting the steam turbine plant, and a state quantity planned value that is a planned value of the state quantity for the operating state associated with the manipulated variable; A database for storing in advance conversion values used for calculating the manipulated variable from the state quantity;
When the start is started, the measured value is obtained as a state quantity actual value from the state quantity measuring instrument of the steam turbine every predetermined time, the state quantity planned value is obtained from the database, and the obtained state quantity is obtained. A state quantity obtaining means for calculating a state quantity deviation which is a deviation based on the plan value and the state quantity actual value;
The manipulated variable plan value is acquired from the database at each predetermined time, the state variable deviation is acquired from the state variable acquisition means, and is associated with the state variable based on the state variable deviation and the converted value. An operation amount determination means for calculating a correction amount of the operation amount as an operation correction amount, and determining an operation amount to the operation end based on the acquired operation amount plan value and the calculated operation correction amount;
Based on the operation correction amount calculated by the operation amount determination unit and the state amount deviation calculated by the state amount acquisition unit every predetermined time, correction for reducing the error for evaluating the conversion value is performed. Database conversion means for calculating the conversion value and storing it in the database,
The said operation amount determination means uses the corrected conversion value when starting next time. The steam turbine control apparatus characterized by the above-mentioned. In the steam turbine control device according to claim 1,
In the database, as the conversion value,
At least corresponding to the j-th element Δy_j of the state quantity deviation vector ΔY composed of at least one element (the symbol _ indicates that the symbol arranged on the right side of the symbol is a subscript). Response coefficient of the i-th element Δx_i of the operation correction amount vector ΔX including one or more elements
a_ij = Δx_i / Δy_j
Is stored as an element, and
The database management unit is based on the operation correction amount vector ΔX calculated by the operation amount determination unit and the state amount deviation vector ΔY calculated by the state amount acquisition unit,
ΔX ~ t = AΔY ~ t
(The symbol ~ t represents the transposition of the matrix or vector on the left side of the symbol.)
The steam matrix control device characterized in that the transformation matrix A shown by (2) is calculated and stored in the database. The steam turbine control device according to claim 1,
In the database, as the conversion value,
At least one corresponding to the j-th element Δy_j of the state quantity deviation vector ΔY composed of at least one element (the symbol _ indicates that the symbol arranged on the right side of the symbol is a subscript) Coefficient of response of the i-th element Δx_i of the operation correction amount vector ΔX comprising two or more elements
a_ij = Δx_i / Δy_j
Is stored, and an offset vector C composed of at least one element c_i is stored.
The database management unit is based on the operation correction amount vector ΔX calculated by the operation amount determination unit and the state amount deviation vector ΔY calculated by the state amount acquisition unit,
ΔX ~ t = AΔY ~ t + C ~ t
(The symbol ~ t represents the transposition of the matrix or vector on the left side of the symbol.)
The conversion matrix A and the offset vector C shown in FIG. 6 are calculated and stored in the database. The steam turbine control device according to claim 2, wherein
The database management means includes:
Based on the values of the element Δx_i of the operation correction amount vector ΔX calculated by the operation amount determination unit and the element Δy_j of the state amount deviation vector ΔY calculated by the state amount acquisition unit,
Err = ∫_t [Δx_i-Σ_j (a_ijΔy_j)] ^ 2 dt
(Integration along the symbol ∫_t time, dt is a minute time, Σ_j is addition along the subscript j, and ^ indicates that the right symbol is a right shoulder subscript.)
The steam turbine control device, wherein the value of each element a_ij of the transformation matrix A that minimizes the value of the Err indicated by (2) is calculated and stored in the database. The steam turbine control device according to claim 3,
The database management means includes:
Based on the values of the element Δx_i of the operation correction amount vector ΔX calculated by the operation amount determination unit and the element Δy_j of the state amount deviation vector ΔY calculated by the state amount acquisition unit,
Err = ∫_t [Δx_i-Σ_j (a_ijΔy_j)-c_i] ^ 2 dt
(Integration along the symbol ∫_t time, dt is a minute time, Σ_j is addition along the subscript j, and ^ indicates that the right symbol is a right shoulder subscript.)
A steam turbine control device that calculates values of each element a_ij of the transformation matrix A and each element c_i of the offset vector C so that the value of the Err shown in FIG. The steam turbine control device according to claim 2, wherein
The database management means includes:
Based on the values of the element Δx_i of the operation correction amount vector ΔX calculated by the operation amount determination unit and the element Δy_j of the state amount deviation vector ΔY calculated by the state amount acquisition unit,
Err = ∫_t [Δx_i-Σ_j ((Σ_k (b_ijk * λ ^ k)) Δy_j)] ^ 2 dt
(Integration along symbol ∫_t time, dt is minute time, Σ_j is addition along subscript j, Σ_k is addition up to k = 1, 2,... K along subscript k, b_ijk is subscript i, (scalar constant with j, k, λ is the load factor of the steam turbine or the plant with the steam turbine, ^ indicates that the symbol on the right is the right subscript.)
A steam turbine control device that calculates and stores in the database a value corresponding to each subscript of the scalar constant b_ijk that minimizes the value of the Err shown in FIG. The steam turbine control device according to claim 3,
The database management means includes:
Based on the values of the element Δx_i of the operation correction amount vector ΔX calculated by the operation amount determination unit and the element Δy_j of the state amount deviation vector ΔY calculated by the state amount acquisition unit,
Err = ∫_t [Δx_i-Σ_j ((Σ_k (b_ijk * λ ^ k)) Δy_j)-c_i] ^ 2 dt
(Integration along symbol ∫_t time, dt is minute time, Σ_j is addition along subscript j, Σ_k is addition up to k = 1, 2,... K along subscript k, b_ijk is subscript i, (scalar constant with j, k, λ is the load factor of the steam turbine or the plant with the steam turbine, ^ indicates that the symbol on the right is the right subscript.)
A value corresponding to each subscript of the scalar constant b_ijk and a value of each element c_i of the offset vector C are calculated and stored in the database so that the value of the Err shown in FIG. Control device.

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