CN113591029A - Stator winding temperature on-line calculation method - Google Patents
Stator winding temperature on-line calculation method Download PDFInfo
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Abstract
The invention discloses an online calculation method for the temperature of a stator winding, which belongs to the technical field of generators and is characterized by comprising the following steps: a. identifying a coefficient vector required by the online calculation of the temperature of the stator winding, and setting a threshold value K; b. calculating a running predicted value theta 'of a stator winding temperature measuring point at time t't(ii) a c. If the deviation is within the threshold value K, theta't+1The calculation is determined by formula 2; d. if the deviation exceeds a threshold value K, determining theta't+1The calculation is determined by formula 3; e. and c, moving a moment backwards, jumping to the step b, and repeating the steps. The invention does not need to inject high-frequency signals, avoids the safe operation risk of the generator, is suitable for different load working conditions, has high adaptability to each temperature measuring point of the stator winding, can meet the individualized operation characteristics of each measuring point, obtains the local temperature of the stator winding by real-time online calculation, has high calculation precision, and greatly improves the effect of evaluating the health of the generator.
Description
Technical Field
The invention relates to the technical field of generators, in particular to an online calculation method for the temperature of a stator winding.
Background
The stator winding of the large-scale generator is placed in a slot of a stator core, and the straight line part is positioned in a rotating main magnetic field to induce high voltage and large current to be transmitted to a power grid. The stator winding is used as a key component for energy conversion and electric energy output of the generator, and the quality of the running state of the stator winding directly influences whether the whole unit can run safely and stably. Because the stator winding of a large generator has large current, the stator current of the steam turbine generator with the power of 300MW and 600MW respectively exceeds 10000A and 20000A, and therefore the stator winding is one of the parts with the largest loss and heat generation of the generator.
Statistical data show that the stator thermal fault is a common fault of the generator, and because the temperature of the stator winding is a key sign of the fault, each power plant pays extra attention to the temperature of the stator winding. At present, a fixed limit value alarm mechanism is generally adopted by a power plant, namely, a temperature limit value is set, once data of temperature measuring points arranged on a stator winding exceed the value, an alarm signal is sent out to remind monitoring personnel of the power plant to confirm and process, the temperature limit alarm value is generally set according to design or related standards, and for a large-sized internal water cooling steam turbine generator, the temperature alarm value of a water outlet end of the stator winding is 85 ℃, and the temperature alarm value in a tank is 90 ℃. The alarm mechanism alarms when the stator winding of the generator has obvious faults and reaches the limit, however, in order to meet the requirements of a power grid, the operation mode of a large-scale generator set is more flexible than the prior art, the peak regulation is frequently and deeply performed, the stator current is far lower than the rated current after long-time low-load operation, correspondingly, the temperature of the water outlet end of the stator winding and the temperature in the groove are much lower than the normal rated working condition, under the condition, when the early thermal fault occurs but does not exceed the limit, the monitoring function of fixed limit alarm is greatly weakened, and the early symptoms of the thermal fault of the stator cannot be effectively and timely found.
Chinese patent literature with publication number CN 108847799A and publication date of 2018, 11 and 20 discloses a PMSM stator winding temperature online detection method based on signal injection, which is characterized by comprising the following steps:
establishing a real-time temperature observation method for a stator winding of a permanent magnet synchronous motor;
and step two, adding an optimal injection signal strategy into the temperature observation method in the step one.
The PMSM stator winding temperature online detection method based on signal injection disclosed by the patent document can monitor the health condition of a motor and prevent over-temperature by estimating the stator winding temperature of a permanent magnet synchronous motor online, can also be used in the optimization control of an active heat management motor, and is beneficial to improving the performance of an electric drive system. However, a high-frequency signal needs to be injected, and the stator temperature is indirectly estimated by identifying the change of the stator resistance, so that the large-scale generator has the following problems: firstly, the online real-time injection of high-frequency signals has potential safety hazards to stator windings in high-current and high-voltage operation, and can cause power system faults; secondly, the temperature of the stator winding is estimated through the resistance change of the stator, the temperature value is the average temperature of the stator winding in operation, for a large-scale generator, the length of the stator winding is generally 4-8 m, obvious temperature gradient exists due to the difference of local heating and ventilation conditions, the outlet water temperature of cooling water of the stator winding can be higher than the inlet water temperature by more than 20 ℃, and therefore the actual utility of the average temperature on the estimation of the operation health state of the stator winding is poor.
Disclosure of Invention
The invention provides the stator winding temperature on-line calculation method for overcoming the defects of the prior art, and the invention avoids the safe operation risk of the generator by introducing the normal operation value of the temperature at the previous moment without injecting high-frequency signals, is suitable for different load working conditions, has high adaptability to each temperature measuring point of the stator winding, can meet the individualized operation characteristic of each measuring point, obtains the local temperature of the stator winding by real-time on-line calculation, has high calculation precision, and greatly improves the effect of evaluating the health of the generator.
The invention is realized by the following technical scheme:
an online calculation method for the temperature of a stator winding is characterized by comprising the following steps:
a. setting an identification convergence error value and a ratio value, identifying a coefficient vector required by the on-line calculation of the temperature of the stator winding, and setting a threshold value K;
b. extracting n stator winding temperature continuous operation values, and calculating a stator winding temperature measuring point operation predicted value theta 'at t moment according to the coefficient vector through formula 1't；
In formula (II), theta'tFor the stator winding temperature measuring point operation predicted value at the time t, thetat-1,θt-2…θt-nFor measuring actual running value, alpha, of stator winding temperature before time t1,α2…αnIn order to weight the vector of coefficients,
is the disturbance quantity;
c. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation is within a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 2;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat+1-iIs the actual operation value of the stator winding temperature measuring point at the time t +1-i,
is the disturbance quantity;
d. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation exceeds a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 3;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat-iIs the actual operation value of the stator winding temperature measuring point at the time t-i,
is the disturbance quantity;
e. and c, moving a moment backwards, jumping to the step b, and repeating the steps.
In the step a, identifying the coefficient vector required by the stator winding temperature online calculation specifically refers to selecting a total n value of the coefficient vectors, selecting continuous operation data of stator winding temperature measuring points for a period of time, setting an iteration initial value of the coefficient vectors, identifying the coefficient vectors through a least square method or a neural network, judging whether a proportion value of the number of errors smaller than a convergence error value to the total reaches the standard or not after calculating the stable errors in the statistical identification process, if not, reselecting the total n value of the coefficient vectors, and adjusting parameters to continue identification; if yes, the coefficient vector [ alpha ] is output1,α2…αn]。
Running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (2) is absolute deviation sigma, and the absolute deviation sigma is calculated by formula 4;
σ＝|θt-θ'tequation 4
Where σ is the absolute deviation, θtIs at t timeMeasuring actual operating value theta of stator winding temperaturet' A predicted value is run for the stator winding temperature measurement point at time t.
Running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (a) is calculated by using a relative deviation lambda which is calculated by formula 5;
λ＝|θt-θ't|/θtformula 5
Wherein λ is a relative deviation, θtIs the actual operation value theta of the stator winding temperature measuring point at the time tt' A predicted value is run for the stator winding temperature measurement point at time t.
The basic principle of the invention is as follows:
the large-scale generator has large heat capacity, the unit power change rate is in a certain range, therefore, the temperature change of the components is relatively slow, the temperature sampling period of a general large-scale power plant is short and is about 1s, the temperature data are uploaded to a management information large area of the power plant, the time interval is within 10s, therefore, under normal conditions, the operation value of a stator winding temperature measuring point is greatly related to the temperature data operated by the measuring point in the previous period, the shorter the adjacent time is, the larger the correlation is, and the correlation is verified after long-term monitoring is carried out on the operation data of several large-scale thermal power plants.
The beneficial effects of the invention are mainly shown in the following aspects:
1. according to the invention, by introducing the normal operation value of the temperature at the previous moment, a high-frequency signal is not required to be injected, the safe operation risk of the generator is avoided, the method is suitable for different load working conditions, the adaptability to each temperature measuring point of the stator winding is high, the individualized operation characteristics of each measuring point can be met, the local temperature of the stator winding can be obtained through real-time online calculation, the calculation precision is high, and the effect of evaluating the health of the generator is greatly improved.
2. According to the invention, according to the running temperature characteristic of the stator winding, the local normal running characteristic of the stator winding temperature measuring point can be described only by introducing the recent temperature running value and a group of coefficient vectors, and the local temperature of the stator winding is obtained by real-time online calculation instead of the average temperature of the stator winding, so that the validity of the health evaluation of the generator is better.
3. The method is suitable for different load working conditions of flexible operation of the generator, can be used for respectively modeling each temperature measuring point of the stator winding, extracting coefficient vectors which accord with respective operation characteristics, and constructing a high-precision calculation model, wherein the relative calculation error can be controlled within 1 percent, and the calculation precision is ensured.
Drawings
The invention will be further described in detail with reference to the drawings and the detailed description, wherein:
FIG. 1 is a block flow diagram of the present invention;
FIG. 2 is a block diagram of a coefficient vector identification process according to the present invention;
FIG. 3 is a graph showing the effect of comparing the temperature of the stator winding calculated on-line with the actual operation value according to the embodiment of the present invention;
FIG. 4 is a graph showing the effect of the present invention on-line calculation of the relative error curve of the stator winding temperature;
FIG. 5 is a diagram illustrating the actual operation effect of the comparison curve between the on-line temperature calculation of the stator winding and the actual operation value according to the embodiment of the present invention;
FIG. 6 is a diagram illustrating the effect of the present invention on online calculation of the relative error curve of the stator winding temperature.
Detailed Description
Example 1
Referring to fig. 1 and 2, an online calculation method for stator winding temperature includes the following steps:
a. setting an identification convergence error value and a ratio value, identifying a coefficient vector required by the on-line calculation of the temperature of the stator winding, and setting a threshold value K;
b. extracting n stator winding temperature continuous operation values, and calculating a stator winding temperature measuring point operation predicted value theta 'at t moment according to the coefficient vector through formula 1't；
In formula (II), theta'tFor the stator winding temperature measuring point operation predicted value at the time t, thetat-1,θt-2…θt-nFor measuring actual running value, alpha, of stator winding temperature before time t1,α2…αnIn order to weight the vector of coefficients,
is the disturbance quantity;
c. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation is within a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 2;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat+1-iIs the actual operation value of the stator winding temperature measuring point at the time t +1-i,
is the disturbance quantity;
d. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation exceeds a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 3;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat-iIs the actual operation value of the stator winding temperature measuring point at the time t-i,
is the disturbance quantity;
e. and c, moving a moment backwards, jumping to the step b, and repeating the steps.
The embodiment is the most basic implementation mode, the normal operation value of the temperature at the previous moment is introduced, a high-frequency signal is not required to be injected, the safe operation risk of the generator is avoided, the method is suitable for different load working conditions, the adaptability to each temperature measuring point of the stator winding is high, the individualized operation characteristic of each measuring point can be met, the local temperature of the stator winding is obtained through real-time online calculation, the calculation precision is high, and the effect of evaluating the health of the generator is greatly improved.
Example 2
Referring to fig. 1 and 2, an online calculation method for stator winding temperature includes the following steps:
a. setting an identification convergence error value and a ratio value, identifying a coefficient vector required by the on-line calculation of the temperature of the stator winding, and setting a threshold value K;
b. extracting n stator winding temperature continuous operation values, and calculating a stator winding temperature measuring point operation predicted value theta 'at t moment according to the coefficient vector through formula 1't；
In formula (II), theta'tFor the stator winding temperature measuring point operation predicted value at the time t, thetat-1,θt-2...θt-nFor measuring actual running value, alpha, of stator winding temperature before time t1,α2…αnIn order to weight the vector of coefficients,
is the disturbance quantity;
c. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tStator winding temperature measurement at time tPoint actual operation value thetatWhen the deviation is within a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 2;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat+1-iIs the actual operation value of the stator winding temperature measuring point at the time t +1-i,
is the disturbance quantity;
d. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation exceeds a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 3;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat-iIs the actual operation value of the stator winding temperature measuring point at the time t-i,
is the disturbance quantity;
e. and c, moving a moment backwards, jumping to the step b, and repeating the steps.
In the step a, the step of identifying the coefficient vector required by the on-line calculation of the stator winding temperature specifically refers to selecting the total number n of the coefficient vectors, selecting continuous operation data of the stator winding temperature measuring points for a period of time, setting an iteration initial value of the coefficient vectors, identifying the coefficient vectors through a least square method or a neural network, and counting the calculation errors in the identification processAfter stabilization, judging whether the proportion value of the number of the errors smaller than the convergence error value in the total number reaches the standard, if not, reselecting the value of the total number n of the coefficient vectors, and continuously identifying the adjustment parameters; if yes, the coefficient vector [ alpha ] is output1,α2…αn]。
According to the operation temperature characteristics of the stator winding, the local normal operation characteristics of the stator winding temperature measuring point can be described only by introducing the recent temperature operation value and a group of coefficient vectors, and the local temperature of the stator winding is obtained through real-time online calculation instead of the average temperature of the stator winding, so that the effectiveness of the health evaluation of the generator is better.
Example 3
Referring to fig. 1 and 2, an online calculation method for stator winding temperature includes the following steps:
a. setting an identification convergence error value and a ratio value, identifying a coefficient vector required by the on-line calculation of the temperature of the stator winding, and setting a threshold value K;
b. extracting n stator winding temperature continuous operation values, and calculating a stator winding temperature measuring point operation predicted value theta 'at t moment according to the coefficient vector through formula 1't；
In formula (II), theta'tFor the stator winding temperature measuring point operation predicted value at the time t, thetat-1,θt-2...θt-nFor measuring actual running value, alpha, of stator winding temperature before time t1,α2…αnIn order to weight the vector of coefficients,
is the disturbance quantity;
c. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation is within a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 2;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat+1-iIs the actual operation value of the stator winding temperature measuring point at the time t +1-i,
is the disturbance quantity;
d. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation exceeds a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 3;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat-iIs the actual operation value of the stator winding temperature measuring point at the time t-i,
is the disturbance quantity;
e. and c, moving a moment backwards, jumping to the step b, and repeating the steps.
In the step a, identifying the coefficient vector required by the on-line calculation of the stator winding temperature specifically refers to selecting the total n value of the coefficient vectors, selecting continuous operation data of the stator winding temperature measuring points for a period of time, setting an iteration initial value of the coefficient vectors, identifying the coefficient vectors through a least square method or a neural network, judging whether the proportion value of the number of errors smaller than the convergence error value to the total reaches the standard or not after the calculation errors are stable in the statistical identification process, and if not, reselecting the coefficient vectorsThe total number n is the value, and the parameters are adjusted to be continuously identified; if yes, the coefficient vector [ alpha ] is output1,α2…αn]。
Running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (2) is absolute deviation sigma, and the absolute deviation sigma is calculated by formula 4;
σ＝|θt-θ'tequation 4
Where σ is the absolute deviation, θtIs the actual operation value theta of the stator winding temperature measuring point at the time tt' A predicted value is run for the stator winding temperature measurement point at time t.
Running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (a) is calculated by using a relative deviation lambda which is calculated by formula 5;
λ＝|θt-θ't|/θtformula 5
Wherein λ is a relative deviation, θtIs the actual operation value theta of the stator winding temperature measuring point at the time tt' A predicted value is run for the stator winding temperature measurement point at time t.
The embodiment is an optimal implementation mode, is suitable for different load working conditions of flexible operation of the generator, can be used for respectively modeling each temperature measuring point of the stator winding, extracting coefficient vectors which accord with respective operation characteristics, and accordingly constructing a high-precision calculation model, and can ensure the calculation precision by controlling the relative calculation error within 1%.
The invention is described below with reference to specific application examples:
in order to verify the calculation accuracy of the method, the actual operation data of the temperature of the stator winding of a No. 2 1000MW generator of a certain power plant for a period of time is selected for testing and verification.
The total number n of coefficient vector elements is selected to be 3 and the convergence relative error value is 1%. The coefficient vectors identified by the least square method are [0.5243, 0.2246, 0.2511], and the identification effect is shown in fig. 3 and 4. The relative error range is (-0.6%, 0.6%), which meets the established requirements, and the coefficient vector is available.
The coefficient vector is applied to the stator winding temperature calculation in the subsequent period, and the practical application effect is shown in fig. 5 and fig. 6. In order to show visually and conveniently, the test only uses actual data of the power plant for a little time, and the calculation precision and the effect of the method are good for long-time real-time online stator winding temperature calculation.
Claims (4)
1. An online calculation method for the temperature of a stator winding is characterized by comprising the following steps:
a. setting an identification convergence error value and a ratio value, identifying a coefficient vector required by the on-line calculation of the temperature of the stator winding, and setting a threshold value K;
b. extracting n stator winding temperature continuous operation values, and calculating a stator winding temperature measuring point operation predicted value theta 'at t moment according to the coefficient vector through formula 1't；
In formula (II), theta'tFor the stator winding temperature measuring point operation predicted value at the time t, thetat-1,θt-2 … θt-nFor measuring actual running value, alpha, of stator winding temperature before time t1,α2 … αnIn order to weight the vector of coefficients,
is the disturbance quantity;
c. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation is within a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 2;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat+1-iIs the actual operation value of the stator winding temperature measuring point at the time t +1-i,
is the disturbance quantity;
d. if the operation predicted value theta 'of the stator winding temperature measuring point at the moment t'tActual operation value theta of stator winding temperature measuring point at t momenttWhen the deviation exceeds a threshold value K, the operation predicted value theta 'of the stator winding temperature measuring point at the moment t + 1't+1The calculation is determined by formula 3;
in formula (II), theta't+1The predicted value alpha of the operation of the stator winding temperature measuring point at the moment t +1iAs a vector of weighting coefficients, thetat-iIs the actual operation value of the stator winding temperature measuring point at the time t-i,
is the disturbance quantity;
e. and c, moving a moment backwards, jumping to the step b, and repeating the steps.
2. The on-line calculation method of the stator winding temperature according to claim 1, characterized in that: in the step a, identifying the coefficient vector required by the on-line calculation of the stator winding temperature specifically refers to selecting the total n value of the coefficient vectors, selecting continuous operation data of the stator winding temperature measuring points for a period of time, setting an iteration initial value of the coefficient vectors, identifying the coefficient vectors by a least square method or a neural network, and judging that the proportion value of the number of errors smaller than the convergence error value to the total number isIf not, reselecting the value of the total number n of the coefficient vectors, and adjusting the parameters to continue to identify; if yes, the coefficient vector [ alpha ] is output1,α2 … αn]。
3. The on-line calculation method of the stator winding temperature according to claim 1, characterized in that: running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (2) is absolute deviation sigma, and the absolute deviation sigma is calculated by formula 4;
σ＝|θt-θ’tequation 4
Where σ is the absolute deviation, θtIs the actual operation value theta of the stator winding temperature measuring point at the time tt' A predicted value is run for the stator winding temperature measurement point at time t.
4. The on-line calculation method of the stator winding temperature according to claim 1, characterized in that: running predicted value theta 'of stator winding temperature measuring point at moment t'tActual operation value theta of stator winding temperature measuring point at t momenttThe deviation of (a) is calculated by using a relative deviation lambda which is calculated by formula 5;
λ＝|θt-θ’t|/θtformula 5
Wherein λ is a relative deviation, θtIs an actual operation value theta of a stator winding temperature measuring point at the time t'tAnd (5) running a predicted value for the temperature measuring point of the stator winding at the time t.
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