CN113586323A - Method and device for determining starting sequence of unsteady-state water turbine generator set and storage medium - Google Patents
Method and device for determining starting sequence of unsteady-state water turbine generator set and storage medium Download PDFInfo
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Abstract
The disclosure provides a method and a device for determining a starting sequence of an unsteady-state water turbine generator set and a storage medium, wherein the method comprises the following steps: determining a first starting sequence of the plurality of water-turbine generator sets according to the health degrees corresponding to the plurality of water-turbine generator sets respectively, determining a second starting sequence of the plurality of water-turbine generator sets according to the running states corresponding to the plurality of water-turbine generator sets respectively, determining the accumulated running time of the plurality of water-turbine generator sets deviating from the optimal working condition respectively, and determining a target starting sequence of the plurality of water-turbine generator sets under the unsteady working condition according to the first starting sequence, the second starting sequence and the accumulated running time. The water turbine generator set can be guaranteed to run reasonably under the condition of deviating from the optimal working condition, and the service life of the water turbine generator set and the economic value of a hydraulic power plant are prolonged.
Description
Technical Field
The disclosure relates to the technical field of hydraulic power plant equipment, in particular to a method and a device for determining a starting sequence of an unsteady-state water turbine generator set and a storage medium.
Background
At present, no clear research is carried out on the management of the starting and stopping sequence of a plurality of hydraulic generator sets in a certain station, and the starting and stopping of the hydraulic generator sets are only subjectively judged by operators on duty. In addition, under the condition of deviating from good working conditions (such as unit pressure regulation, no-load operation and operation in an unremitting interval), the starting sequence is also judged by an on-duty person subjectively.
However, the knowledge of the duty personnel about the equipment state is greatly different, and the definition of the equipment defects is not completely the same among different personnel, so that the control of the starting sequence by different personnel is greatly different. Therefore, under the unsteady working condition, a reasonable starting sequence cannot be determined, and therefore the service life of the water turbine generator set and the economic value of a hydraulic power plant are influenced.
Disclosure of Invention
The application provides a method and a device for determining a starting sequence of an unsteady-state water turbine generator set and a storage medium, and aims to solve one of technical problems in the related art to at least a certain extent.
An embodiment of the first aspect of the application provides a method for determining a starting sequence of an unsteady-state water-turbine generator set, which comprises the following steps: determining a first starting sequence of the plurality of water turbine generator sets according to the health degrees corresponding to the plurality of water turbine generator sets respectively; determining a second starting sequence of the plurality of water turbine generator sets according to the operating states corresponding to the plurality of water turbine generator sets respectively; respectively determining the accumulated running time of the plurality of water turbine generator sets deviating from the optimal working condition; and determining a target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition according to the first starting sequence, the second starting sequence and the accumulated running time.
The embodiment of the second aspect of the application provides a device for determining the starting sequence of an unsteady-state water-turbine generator set, which comprises: the first sequencing module is used for determining a first starting sequence of the plurality of water-turbine generator sets according to the health degrees corresponding to the plurality of water-turbine generator sets respectively; the second sequencing module is used for determining a second starting sequence of the plurality of water-turbine generator sets according to the operating states respectively corresponding to the plurality of water-turbine generator sets; the first determining module is used for respectively determining annual accumulated running time of the plurality of water-turbine generator sets deviating from the optimal working condition; and the third sequencing module is used for determining the target starting sequence of the plurality of water-turbine generator sets under the unsteady working condition according to the first starting sequence, the second starting sequence and the annual accumulated running time.
An embodiment of a third aspect of the present application provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the unsteady-state water-turbine generator set starting sequence determining method in the embodiment of the application.
A fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable the computer to execute the method for determining the startup sequence of the unsteady-state water-turbine generator set disclosed in the embodiments of the present application.
In this embodiment, a first start-up sequence of the plurality of water turbine generator sets is determined according to the health degrees corresponding to the plurality of water turbine generator sets respectively, a second start-up sequence of the plurality of water turbine generator sets is determined according to the operating states corresponding to the plurality of water turbine generator sets respectively, the accumulated operating time of the plurality of water turbine generator sets deviating from the optimal operating condition is determined respectively, and a target start-up sequence of the plurality of water turbine generator sets under the unstable operating condition is determined according to the first start-up sequence, the second start-up sequence and the accumulated operating time. Therefore, the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition can be determined by combining various factors such as the health degree, the running state and the accumulated running time deviated from the optimal working condition of the water turbine generator sets, the water power plant can run reasonably under the condition of deviating from the optimal working condition, and the service life of the water turbine generator sets and the economic value of the water power plant are prolonged. And the technical problems that the service life of the water turbine generator set and the economic value of a hydraulic power plant are influenced because a reasonable starting sequence cannot be determined under an unsteady working condition in the related technology are solved.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
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The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart of a method for determining a startup sequence of an unsteady-state water-turbine generator set according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of a method for determining a startup sequence of an unsteady-state water-turbine generator set according to another embodiment of the disclosure;
FIG. 3a is a two-dimensional distribution diagram of the stator heating data of the hydraulic generator according to the embodiment of the disclosure;
FIG. 3b is a schematic diagram of a second load interval of a stator according to an embodiment of the present disclosure;
fig. 3c is a schematic diagram of a value interval of a second load interval of a stator according to an embodiment of the disclosure;
fig. 4 is a schematic diagram of a non-steady-state water turbine generator set starting sequence determining device according to another embodiment of the disclosure;
fig. 5 is a schematic diagram of a non-steady-state water turbine generator set starting sequence determining device according to another embodiment of the disclosure;
FIG. 6 illustrates a block diagram of an exemplary computer device suitable for use to implement embodiments of the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of illustrating the present disclosure and should not be construed as limiting the same. On the contrary, the embodiments of the disclosure include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
In order to solve the technical problems that a reasonable starting sequence cannot be determined under an unsteady state working condition and therefore the service life of the hydro-turbo generator set and the economic value of a hydraulic power plant are affected in the background art, the technical scheme of the embodiment provides a method for determining the starting sequence of the unsteady hydro-turbo generator set, and the method is explained with reference to specific embodiments.
It should be noted that an execution main body of the method for determining the starting sequence of the unsteady-state water-turbine generator set in this embodiment may be an unsteady-state water-turbine generator set starting sequence determination device, the device may be implemented in a software and/or hardware manner, the device may be configured in an electronic device, and the electronic device may include, but is not limited to, a terminal, a server, and the like.
Fig. 1 is a schematic flow chart of a method for determining a startup sequence of an unsteady-state water-turbine generator set according to an embodiment of the present disclosure, and as shown in fig. 1, the method includes:
s101: and determining a first starting sequence of the plurality of water turbine generator sets according to the health degrees corresponding to the plurality of water turbine generator sets respectively.
The plurality of water turbine generator sets are arranged in the hydropower station and used for performing hydroelectric power generation, and the number of the plurality of water turbine generator sets can be determined according to the scale of the hydropower station without limitation.
The health degree can represent the health condition of the equipment of each hydroelectric generating set, such as: the health level may be indicated by, without limitation, wheel cavitation, cracks, unabated defects, and any other possible conditions.
And a plurality of hydroelectric generating sets are ordered according to the health degree, and the obtained sequence can be called as a first starting sequence, for example: according to the health degree, the plurality of water turbine generator sets are sequenced from high to low to obtain the first starting sequence, namely, the starting sequence of the plurality of water turbine generator sets can be determined according to the health degree of the water turbine generator sets.
For example, a plurality of hydro-turbo generator sets such as: unit 1, unit 2, unit 3, unit 4, and unit 5, the first boot sequence is, for example: unit 1, unit 2, unit 3, unit 4, and unit 5.
S102: and determining a second starting sequence of the plurality of water turbine generator sets according to the operating states respectively corresponding to the plurality of water turbine generator sets.
After the first starting sequence is determined, further, the second starting sequence of the plurality of water-turbine generator sets can be determined according to the operating states corresponding to the plurality of water-turbine generator sets respectively.
Wherein, the operating condition is used for describing the state characteristic among the hydroelectric set operation, for example: component heating characteristics, component runout characteristics, and any other possible status characteristics, without limitation herein.
And the plurality of hydroelectric generating sets are sequenced according to the operation state, and the obtained sequence can be called as a second starting sequence, for example: the plurality of water turbine generator sets are sequenced from low to high according to the operation state to obtain the second starting sequence, that is, the starting sequence of the plurality of water turbine generator sets can be determined according to the operation state of the water turbine generator sets, and the second starting sequence is, for example: unit 4, unit 1, unit 2, unit 3, unit 5.
S103: and respectively determining the accumulated running time of the plurality of water turbine generator sets deviating from the optimal working condition.
Further, the accumulated operation time of the plurality of water turbine generator sets deviating from the optimal working condition is respectively determined, wherein the deviation from the optimal working condition is as follows: the unit is in voltage regulation, no-load operation, and operation in an unremitting interval, and the accumulated operation time may be an annual accumulated operation time, or may also be an accumulated operation time calculated from installation, and is not limited herein. That is, the operating time of each hydro-turbo unit deviating from the optimum operating condition every year is calculated separately.
It should be noted that, the steps S101, S102, and S103 are not in sequence, and may be performed simultaneously or in a random order, which is not limited herein.
S104: and determining the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition according to the first starting sequence, the second starting sequence and the accumulated running time.
In some embodiments, the time difference between the longest aggregate running time and the shortest aggregate running time may be calculated. In practical application, a plurality of hydroelectric generating sets: the accumulated operation times corresponding to the unit 1, the unit 2, the unit 3, the unit 4 and the unit 5 can be respectively represented by TL1, TL2, TL3, TL4 and TL5, so that the unit with the longest accumulated operation time can be represented by TLmax { TL1, TL2, TL3, TL4 and TL5}, the unit with the shortest accumulated operation time can be represented by TLmin { TL1, TL2, TL3, TL4 and TL5}, and the time difference is TLmax-TLmin. And further, comparing the time difference value with a preset threshold value, and judging whether the time difference value is greater than or equal to the preset threshold value. The preset threshold may be flexibly determined according to an actual application scenario, for example: if the preset threshold is equal to 100 hours, judging whether the time difference is greater than or equal to the preset threshold, namely: and judging whether the time difference value is greater than or equal to 100. If the time difference is greater than or equal to the preset threshold (100 hours), the unit with the longest accumulated running time in the first starting sequence is moved to the last starting position to obtain a third starting sequence, for example: the unit with the longest accumulative running time is the unit 2 (the accumulative running time is 150 hours), the unit with the shortest accumulative running time is the unit 3 (the accumulative running time is 30 hours), and the time difference is not less than 100. In this case, the unit with the longest accumulated running time in the first boot order (i.e., the unit 2) is moved to the last boot position, and the corresponding third boot order is: the unit 1, the unit 3, the unit 4, the unit 5, and the unit 2, otherwise, the first starting sequence is used as the third starting sequence, that is, the first starting sequence is used as the third starting sequence when the time difference value is not greater than or equal to the preset threshold value.
In other embodiments, before the third starting sequence is determined according to the accumulated running time, the running state and the defect type of each unit can be determined, and if the unit has a type-A defect (for example, the unit cannot work due to a serious defect), or a maintenance state, or a shutdown and defect elimination state, the unit is removed from the first starting sequence and is prompted; if the unit has B-type defects (for example, common defects can work), the unit is moved to the last starting position to adjust the first starting sequence.
Further, according to the second starting sequence, the third starting sequence and the corresponding third weight values, the target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition is determined.
For example, the second startup sequence (the unit 4, the unit 1, the unit 2, the unit 3, and the unit 5) may be represented by Y, the third startup sequence (the unit 1, the unit 3, the unit 4, the unit 5, and the unit 2) may be represented by J, a third weight value of the second startup sequence Y is 0.3, and a third weight value of the third startup sequence J is 0.7, so that a score Q of each hydro-generator set is 0.7J +0.3Y, and then the plurality of hydro-generator sets are sorted from small to large according to Q to obtain a target startup sequence, for example: unit 1, unit 4, unit 3, unit 5, unit 2. Thus, the target boot sequence may have different emphasis points, such as: in the starting process, the health degree or the running state can be strategically weighted, so that the target starting sequence can be flexibly determined according to different weight values.
In this embodiment, a first start-up sequence of the plurality of water turbine generator sets is determined according to the health degrees corresponding to the plurality of water turbine generator sets respectively, a second start-up sequence of the plurality of water turbine generator sets is determined according to the operating states corresponding to the plurality of water turbine generator sets respectively, the accumulated operating time of the plurality of water turbine generator sets deviating from the optimal operating condition is determined respectively, and a target start-up sequence of the plurality of water turbine generator sets under the unstable operating condition is determined according to the first start-up sequence, the second start-up sequence and the accumulated operating time. Therefore, the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition can be determined by combining various factors such as the health degree, the running state and the accumulated running time deviated from the optimal working condition of the water turbine generator sets, the water power plant can run reasonably under the condition of deviating from the optimal working condition, and the service life of the water turbine generator sets and the economic value of the water power plant are prolonged. And the technical problems that the service life of the water turbine generator set and the economic value of a hydraulic power plant are influenced because a reasonable starting sequence cannot be determined under an unsteady working condition in the related technology are solved.
Fig. 2 is a schematic flow chart of a method for determining a startup sequence of an unsteady-state water-turbine generator set according to another embodiment of the present disclosure, and as shown in fig. 2, the method includes:
s201: and respectively acquiring the cavitation erosion quantity of the rotating wheel, the crack length of the rotating wheel and the quantity of unprocessed defects in the preset time of the plurality of water-turbine generator sets.
According to the embodiment of the disclosure, firstly, the cavitation erosion quantity of the runner, the crack length of the runner and the quantity of unprocessed defects in the preset time of the plurality of hydroelectric generating sets are respectively obtained.
The preset time can be a maintenance period, that is, the cavitation erosion number of the rotating wheel, the crack length of the rotating wheel and the number of unprocessed defects found in the maintenance process can be obtained.
S202: and determining a cavitation grade corresponding to the cavitation quantity of the rotating wheel, a crack grade corresponding to the crack length of the rotating wheel and a defect grade corresponding to the quantity of unprocessed defects according to a preset grade rule.
For example, the cavitation may be divided into 5 levels according to the number of the cavitation from low to high, and the number of the cavitation corresponding to the 5 levels is sequentially: 0 to 19, 20 to 50, 50 to 100, 100 to 200, 200 or more, unit: and (4) respectively. And determining the cavitation level corresponding to the cavitation quantity of the runner of each hydroelectric generating set according to the level.
The cracks can be divided into 5 grades according to the length of the cracks from low to high, and the lengths of the cracks corresponding to the 5 grades are as follows: 0 to 29, 30 to 79, 80 to 149, 150 to 300, 300 or more, unit: mm. According to the grade, the crack grade corresponding to the crack length of each hydroelectric generating set can be determined.
Unprocessed defects can be classified into A, B, C types of defects, and if a unit with a type A defect exists, the unit is deleted in a first starting sequence (namely, does not participate in sorting); if the set with the type B defects exists, arranging the set to the last starting position of the first starting sequence; if there is a C-type defect, the number of C-type defects is used as the defect level.
S203: and determining the health degree respectively corresponding to the plurality of water-turbine generator sets according to the cavitation level, the crack level, the defect level and the first weighted values respectively corresponding to the defect level.
The cavitation level, the crack level and the defect level can correspond to first weight values respectively, weighting calculation can be carried out according to the cavitation level, the crack level and the defect level of each water-turbine generator set and the corresponding first weight values respectively in the process of determining the health degree, and the obtained numerical values serve as the health degree of each water-turbine generator set.
For example, the cavitation level may be represented by Zq, and the first weight value corresponding to the cavitation level is 0.2; the crack grade can be represented by Zl, and the first weight value corresponding to the crack grade is 0.4; the defect level may be represented by QX, and the first weighting value corresponding to the defect level is 0.4, so that the health degree of each hydro-turbo generator set is Zq 0.2+ Zl 0.4+ QX 0.4.
S204: and determining a first starting sequence of the plurality of water turbine generator sets according to the health degrees corresponding to the plurality of water turbine generator sets respectively.
For the description of S204, reference may be made to the foregoing embodiments specifically, which are not described herein again.
S205: and respectively acquiring heating data and runout data of a plurality of components in a preset time of the plurality of water turbine generator sets.
Further, heat generation data and runout data of a plurality of components within a predetermined time (for example, 1 year) per hydroelectric generating set are acquired.
In some embodiments, the plurality of components include, for example, one or more of an upper guide, a lower guide, a water guide, a thrust bearing bush of a hydro-generator, a stator of the hydro-generator, a rotor of the hydro-generator, and any other possible components, and the heat generation data may be heat generation data of each of the above components during operation, which is not limited thereto.
The oscillation data includes, for example, one or more of an upper guide X-direction oscillation degree, an upper guide Y-direction oscillation degree, a water guide X-direction oscillation degree, a water guide Y-direction oscillation degree, a thrust X-direction oscillation degree, a thrust Y-direction oscillation degree, an upper frame X-direction oscillation, an upper frame Y-direction oscillation, an upper frame vertical oscillation, a lower frame X-direction oscillation, a lower frame Y-direction oscillation, a lower frame vertical oscillation, a top cover horizontal oscillation X-direction, a top cover horizontal oscillation Y-direction, a top cover horizontal oscillation Z-direction, a stator core X-direction horizontal oscillation, and a stator base Z-direction horizontal oscillation of the hydro-generator, which is not limited thereto.
S206: and calculating the temperature average value of the water-turbine generator set in a preset first load interval according to the heating data.
Wherein, first load interval can be the load interval under the hydroelectric set abnormal operation state, and first load interval is for example: the range of 0-180 MW. In actual operation, the heating data of each component of the hydroelectric generating set collected by the sensor during operation in a load interval of 0-180MW can be utilized, and the average value is calculated to obtain the temperature average value.
In some embodiments, in the operation of calculating the average value of the temperature of the hydro-turbo set in the preset first load interval, the two-dimensional data distribution map may be established by using the acquired heat generation data of each component and the corresponding load data.
For example, the component is a stator of a hydro-generator, fig. 3a is a two-dimensional distribution diagram of heating data of the stator of the hydro-generator according to the embodiment of the present disclosure, as shown in fig. 3a, the heating data of the stator within 1 year and corresponding load data are obtained through big data, and a coordinate system is established, where the load data of the unit is an abscissa and the heating data of the stator (temperature of the stator) is an ordinate. The other components construct the two-dimensional distribution map similarly to the stator of the hydraulic generator, and are not described herein, so that each component can have a corresponding two-dimensional distribution map.
Further, according to the heating data of each component and the corresponding load data, a first regression model for representing the relationship between the heating condition of each component and the unit load is constructed. For example: from the stator temperature and the corresponding load data in fig. 3a, a first regression model of the stator temperature is constructed, namely: a curve (i.e., a first regression model) is fitted to the data distribution in the two-dimensional distribution plot of fig. 3 a.
In some embodiments, assuming the unit load as a dependent variable and the stator temperature as an independent variable, the regression equation between the dependent variable Y and the independent variable x (the first regression model) may have the following form Y ═ β0+β1x1+ ε, wherein β0、β1For the regression coefficients, ε represents the randomness error and independently follows a normal distribution.
Will influence factor x1Substituting the formula to obtain:
yi＝β0+βixi+εi
obtaining a linear sample regression equation:
the estimation of the regression coefficient in the linear regression equation adopts a least square method, and the method is characterized in that the sum of the squares of the residuals:
pair SSE to beta0、β1Calculating partial derivative, making it equal to zero, and obtaining standard equation set after finishing:
by solving the above equation set, regression coefficient β can be obtained0、β1Thereby obtaining the first regression model.
In other embodiments, the first regression model may be further represented as: y ═ cxa+ bx, or y ═ c ' ln (x + a ') + b ' x, where a, a ', b ', c ' are coefficient values for each component (a, b ', c)>1) The solving method is similar to the solving process, and is not described herein again.
Further, a first load interval and a value interval of the first load interval are determined. Fig. 3b is a schematic diagram of a first load interval of a stator according to an embodiment of the present disclosure, as shown in fig. 3b, the first load interval may be, for example, 0-180MW, a value interval of the first load interval may be determined according to an actual application scenario, and fig. 3c is a schematic diagram of a value interval of the first load interval of the stator according to an embodiment of the present disclosure, as shown in fig. 3c, a value interval in this embodiment may be 1 MW.
Further, sampling is carried out on the first regression model based on the first load interval and the value interval of the first load interval, and a plurality of temperature sample data of the corresponding component are determined. For example: as shown in fig. 3c, the stator temperature corresponding to the load of 0, 1, 2.. 180MW is taken as the stator temperature sample data on the curve of the first regression model. Further, a first arithmetic mean of a plurality of temperature sample data for each component is calculated, for example: and carrying out mean value calculation on the stator temperature sample data to obtain a first arithmetic mean value of the stator.
It is understood that the calculation process of the first arithmetic mean value of each component can be the same as the calculation process of the stator component, and is not described herein. Thus, for each component, a corresponding first arithmetic mean may be determined.
Further, a weighted average calculation is performed on a plurality of first arithmetic mean values corresponding to the plurality of components, and a temperature mean value is determined. That is to say, different parts can correspond different weight values, can carry out the average calculation of weighing according to the first arithmetic mean value of every part and the weight value that corresponds, obtains every hydroelectric set's temperature average value, for example: temperature average ∑ (stator temperature first arithmetic average weight + rotor temperature first arithmetic average weight + ·.)/n.
S207: and calculating the average value of the runout of the water-turbine generator set in a preset second load interval according to the runout data.
Wherein, the second load interval can be the load interval under the hydroelectric set abnormal operation state, and the second load interval is for example: and (3) in the range of 0-180MW, namely, calculating the average value of the runout data of each part when the hydroelectric generating set operates in the load range of 0-180MW to obtain the runout average value.
In some embodiments, in the operation of determining the average value of the runout of the hydro-turbo set in the preset second load interval, the runout of each component and the corresponding load data may be used to build a data two-dimensional distribution map (the same as the heating data building mode).
For example, the runout data is guide X-direction runout data on the hydraulic generator, the guide X-direction runout data on the hydraulic generator within one year and corresponding load data are obtained through big data, and a two-dimensional distribution map is constructed.
Further, according to the runout data (for example, the direction X on the hydraulic generator) of each component and the corresponding load data, a second regression model for representing the relationship between the vibration condition of each component and the load of the unit is constructed, so that the corresponding second regression model can be obtained for each component.
The form of the second regression model may be similar to that of the first regression model, and is not described herein again.
Further, determining a value interval between the second load interval and the second load interval, for example: the second load interval can be 0-180MW, and the value interval of the second load interval can be 1 MW.
And further, sampling is carried out on the three regression models based on the second load interval and the value interval of the second load interval, and a plurality of runout sample data of the corresponding component are determined. For example: and taking runout data corresponding to 0, 1, 2.. 180MW load on a curve of a second regression model corresponding to the guide X direction on the hydraulic generator as sample data of the guide X direction runout on the hydraulic generator.
Further, a second arithmetic mean of a plurality of runout sample data for each component is calculated, for example: and carrying out mean value calculation on the sample data of the guide X-direction runout on the hydraulic generator to obtain a second arithmetic mean value of the guide X-direction runout on the hydraulic generator.
It can be understood that the calculation process of the second arithmetic mean value of each component may be the same as the calculation process of the guide X direction on the hydraulic generator, and is not described herein again. Thus, a corresponding second arithmetic mean value may be determined for the vibration situation of each component.
Further, a weighted average calculation is performed on a plurality of second arithmetic mean values corresponding to the plurality of components, and a runout mean value is determined. That is to say, different parts can correspond different weighted values, can carry out the average calculation of weighing according to the second arithmetic mean value of every part and the weighted value that corresponds, obtains every hydroelectric set's runout average value.
S208: and determining the operating states respectively corresponding to the plurality of water-turbine generator sets according to the temperature average value, the runout average value and the second weighted values respectively corresponding to the runout average value.
For example, the plurality of hydroelectric generating sets can be sorted from high to low according to the average temperature value, and the serial number (for example, 1 to 5) is used as a score; similarly, the plurality of hydroelectric generating sets can be sorted from high to low according to the average runout value, and the serial number (for example, 1 to 5) is used as the score. The temperature average value serial number may be represented by JR, and the corresponding second weight value may be 0.3, the runout average value serial number may be represented by JZ, and the corresponding second weight value may be 0.7, and then the operating state corresponding to each of the hydroelectric generating sets is 0.3JR +0.7JZ, respectively.
S209: and determining a second starting sequence of the plurality of water turbine generator sets according to the operating states respectively corresponding to the plurality of water turbine generator sets.
S210: and respectively determining the accumulated running time of the plurality of water turbine generator sets deviating from the optimal working condition.
S211: and determining the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition according to the first starting sequence, the second starting sequence and the accumulated running time.
For the description of S209 to S211, reference may be made to the above embodiments, which are not described herein again.
In this embodiment, a first start-up sequence of the plurality of water turbine generator sets is determined according to the health degrees corresponding to the plurality of water turbine generator sets respectively, a second start-up sequence of the plurality of water turbine generator sets is determined according to the operating states corresponding to the plurality of water turbine generator sets respectively, the accumulated operating time of the plurality of water turbine generator sets deviating from the optimal operating condition is determined respectively, and a target start-up sequence of the plurality of water turbine generator sets under the unstable operating condition is determined according to the first start-up sequence, the second start-up sequence and the accumulated operating time. Therefore, the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition can be determined by combining various factors such as the health degree, the running state and the accumulated running time deviated from the optimal working condition of the water turbine generator sets, the water power plant can run reasonably under the condition of deviating from the optimal working condition, and the service life of the water turbine generator sets and the economic value of the water power plant are prolonged. And the technical problems that the service life of the water turbine generator set and the economic value of a hydraulic power plant are influenced because a reasonable starting sequence cannot be determined under an unsteady working condition in the related technology are solved. In addition, the temperature data and the runout data of various defects and a plurality of components can be combined in the process of calculating the running state and the health degree, and the temperature average value and the runout average value are determined by constructing a regression equation, so that the health degree and the running state of the unit can be accurately determined, and the accuracy of a target starting sequence is improved.
Fig. 4 is a schematic diagram of a non-steady-state water turbine generator set starting sequence determining device according to another embodiment of the disclosure. As shown in fig. 4, the unsteady-state hydroelectric generating set startup sequence determining apparatus 40 includes:
the first sequencing module 401 is configured to determine a first starting sequence of the plurality of water turbine generator sets according to the health degrees corresponding to the plurality of water turbine generator sets respectively;
the second sequencing module 402 is configured to determine a second starting sequence of the plurality of water turbine generator sets according to respective corresponding operating states of the plurality of water turbine generator sets;
the first determining module 403 is configured to determine annual accumulated operating time of the plurality of water turbine generator sets deviating from the optimal working condition; and
and the third sequencing module 404 is configured to determine a target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition according to the first starting sequence, the second starting sequence and the annual accumulated operating time.
Optionally, in some embodiments, fig. 5 is a schematic diagram of a device for determining a startup sequence of an unsteady-state water turbine generator set according to another embodiment of the present disclosure, as shown in fig. 5, the device 40 further includes: a first obtaining module 405, configured to obtain the cavitation erosion number of the runner, the crack length of the runner, and the number of unprocessed defects in a predetermined time of the multiple hydro-generator sets, respectively; the second determining module 406 is configured to determine, according to a preset grade rule, a cavitation grade corresponding to the cavitation quantity of the rotating wheel, a crack grade corresponding to the crack length of the rotating wheel, and a defect grade corresponding to the unprocessed defect quantity; and the third determining module 407 is configured to determine the health degrees corresponding to the multiple water turbine generator sets respectively according to the cavitation level, the crack level, the defect level and the corresponding first weight values respectively.
Optionally, in some embodiments, as shown in fig. 5, the apparatus 40 further comprises: a second obtaining module 408, configured to obtain heating data and runout data of a plurality of components in a predetermined time of the plurality of water turbine generator sets, respectively; the first calculating module 409 is used for calculating the temperature average value of the water-turbine generator set in a preset first load interval according to the heating data; the second calculating module 410 is configured to calculate a runout average value of the water turbine generator set in a preset second load interval according to the runout data; and a third determining module 411, configured to determine, according to the temperature average value, the runout average value, and the second weight values respectively corresponding to the runout average value, operating states respectively corresponding to the multiple water turbine generator sets.
Optionally, in some embodiments, the first calculating module 409 is specifically configured to: constructing a first regression model for representing the relationship between the heating condition of each component and the unit load according to the heating data of each component and the corresponding load data; determining a first load interval and a value interval of the first load interval; sampling in a regression model based on the first load interval and the value interval of the first load interval, and determining a plurality of temperature sample data of each component; calculating a first arithmetic mean of a plurality of temperature sample data for each component; a weighted average calculation is performed on a plurality of first arithmetic mean values corresponding to the plurality of components, and a temperature mean value is determined.
Optionally, in some embodiments, the second calculating module 410 is specifically configured to: constructing a second regression model for expressing the relationship between the runout condition of each component and the unit load according to the runout data of each component and the corresponding load data; determining a second load interval and a value interval of the second load interval; sampling in a second regression model based on a second load interval and the value interval of the second load interval, and determining a plurality of runout sample data of each component; calculating a second arithmetic mean value of a plurality of runout sample data of each component; and performing weighted average calculation on a plurality of second arithmetic average values corresponding to the plurality of components to determine a runout average value.
Optionally, in some embodiments, the third sorting module 404 is specifically configured to: calculating a time difference value of the longest accumulated operation time unit and the shortest accumulated operation time unit, and judging whether the time difference value is greater than or equal to a preset threshold value or not; if the time difference is larger than or equal to a preset threshold value, moving the unit with the longest accumulated running time in the first starting sequence to the last starting position to obtain a third starting sequence; otherwise, the first starting sequence is used as a third starting sequence; and determining the target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the second starting sequence, the third starting sequence and the corresponding third weight values.
Optionally, some embodiments, the plurality of components comprises at least one of: the hydraulic generator comprises a hydraulic generator upper guide, a hydraulic generator lower guide, a hydraulic generator thrust bearing bush, a hydraulic generator stator and a hydraulic generator rotor; the runout data includes at least one of: the hydraulic generator comprises an upper guide X-direction swing degree, an upper guide Y-direction swing degree, a water guide X-direction swing degree, a water guide Y-direction swing degree, a thrust X-direction swing degree, a thrust Y-direction swing degree, an upper frame X-direction vibration, an upper frame Y-direction vibration, an upper frame vertical vibration, a lower frame X-direction vibration, a lower frame Y-direction vibration, a lower frame vertical vibration, a top cover horizontal vibration X-direction, a top cover horizontal vibration Y-direction, a top cover horizontal vibration Z-direction, a stator core X-direction horizontal vibration and a stator base Z-direction horizontal vibration.
In this embodiment, a first start-up sequence of the plurality of water turbine generator sets is determined according to the health degrees corresponding to the plurality of water turbine generator sets respectively, a second start-up sequence of the plurality of water turbine generator sets is determined according to the operating states corresponding to the plurality of water turbine generator sets respectively, the accumulated operating time of the plurality of water turbine generator sets deviating from the optimal operating condition is determined respectively, and a target start-up sequence of the plurality of water turbine generator sets under the unstable operating condition is determined according to the first start-up sequence, the second start-up sequence and the accumulated operating time. Therefore, the target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition can be determined by combining various factors such as the health degree, the running state and the accumulated running time deviated from the optimal working condition of the water turbine generator sets, the water power plant can run reasonably under the condition of deviating from the optimal working condition, and the service life of the water turbine generator sets and the economic value of the water power plant are prolonged. And the technical problems that the service life of the water turbine generator set and the economic value of a hydraulic power plant are influenced because a reasonable starting sequence cannot be determined under an unsteady working condition in the related technology are solved.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
In order to implement the foregoing embodiments, the present application further provides a computer program product, which when executed by an instruction processor in the computer program product, executes the method for determining the startup sequence of the unsteady-state water-turbine generator set according to the foregoing embodiments of the present application.
FIG. 6 illustrates a block diagram of an exemplary computer device suitable for use to implement embodiments of the present application. The computer device 12 shown in fig. 6 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present application.
As shown in FIG. 6, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Although not shown in FIG. 6, a disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a Compact disk Read Only Memory (CD-ROM), a Digital versatile disk Read Only Memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described herein.
The processing unit 16 executes the program stored in the system memory 28 to execute various functional applications and methods, such as the method for determining the starting sequence of the unsteady-state water turbine generator set mentioned in the foregoing embodiments.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present application, "a plurality" means two or more unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for determining a starting sequence of an unsteady-state water turbine generator set is characterized by comprising the following steps:
determining a first starting sequence of the plurality of water turbine generator sets according to the health degrees corresponding to the plurality of water turbine generator sets respectively;
determining a second starting sequence of the plurality of water turbine generator sets according to the operating states corresponding to the plurality of water turbine generator sets respectively;
respectively determining the accumulated running time of the plurality of water turbine generator sets deviating from the optimal working condition; and
and determining the target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the first starting sequence, the second starting sequence and the accumulated running time.
2. The method of claim 1, wherein prior to determining a first startup sequence of the plurality of hydro-generator sets based on the respective health levels of the plurality of hydro-generator sets, further comprising:
respectively acquiring the cavitation erosion quantity of the rotating wheel, the crack length of the rotating wheel and the quantity of unprocessed defects in the preset time of the plurality of hydroelectric generating sets;
determining a cavitation grade corresponding to the cavitation quantity of the rotating wheel, a crack grade corresponding to the crack length of the rotating wheel and a defect grade corresponding to the quantity of unprocessed defects according to a preset grade rule; and
and determining the health degree corresponding to each of the plurality of water-turbine generator sets according to the cavitation level, the crack level, the defect level and the corresponding first weight value.
3. The method of claim 1, wherein prior to determining a second startup sequence of the plurality of hydro-generator sets based on the respective operating conditions of the plurality of hydro-generator sets, further comprising:
respectively acquiring heating data and runout data of a plurality of components in a preset time of the plurality of water turbine generator sets;
calculating the temperature average value of the water-turbine generator set in a preset first load interval according to the heating data;
calculating the average value of the runout of the hydroelectric generating set in a preset second load interval according to the runout data; and
and determining the running states respectively corresponding to the plurality of water-turbine generator sets according to the temperature average value, the runout average value and the second weighted values respectively corresponding to the temperature average value and the runout average value.
4. The method of claim 3, wherein determining an average temperature of the hydro-turbo generator set over a preset first load interval based on the thermal data comprises:
constructing a first regression model for representing the relationship between the heating condition of each component and the unit load according to the heating data of each component and the corresponding load data;
determining the first load interval and the value interval of the first load interval;
sampling in the regression model based on the first load interval and the value interval of the first load interval, and determining a plurality of temperature sample data of each component;
calculating a first arithmetic mean of a plurality of temperature sample data for each component; and
and carrying out weighted average calculation on a plurality of first arithmetic mean values corresponding to the plurality of components, and determining the temperature mean value.
5. The method of claim 3, wherein determining an average value of the runout of the hydroelectric generating set over a second predetermined load interval based on the runout data comprises:
constructing a second regression model for expressing the relationship between the runout condition of each component and the unit load according to the runout data of each component and the corresponding load data;
determining the second load interval and the value interval of the second load interval;
sampling in the second regression model based on the second load interval and the value interval of the second load interval, and determining a plurality of runout sample data of each component;
calculating a second arithmetic mean value of a plurality of runout sample data of each component; and
and performing weighted average calculation on a plurality of second arithmetic mean values corresponding to the plurality of components to determine the runout mean value.
6. The method of claim 1, wherein determining the target startup sequence of the plurality of hydro-turbo generator sets under the non-steady state condition according to the first startup sequence, the second startup sequence, and the accumulated operating time comprises:
calculating a time difference value of the longest accumulated operation time unit and the shortest accumulated operation time unit, and judging whether the time difference value is greater than or equal to a preset threshold value;
if the time difference is greater than or equal to the preset threshold, moving the unit with the longest accumulated running time in the first starting sequence to the last starting position to obtain a third starting sequence; otherwise, the first starting sequence is used as the third starting sequence;
and determining a target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the second starting sequence, the third starting sequence and the corresponding third weight values.
7. The method of any of claims 3-5, wherein the plurality of components comprises at least one of:
the hydraulic generator comprises a hydraulic generator upper guide, a hydraulic generator lower guide, a hydraulic generator thrust bearing bush, a hydraulic generator stator and a hydraulic generator rotor;
the runout data includes at least one of:
the hydraulic generator comprises an upper guide X-direction swing degree, an upper guide Y-direction swing degree, a water guide X-direction swing degree, a water guide Y-direction swing degree, a thrust X-direction swing degree, a thrust Y-direction swing degree, an upper frame X-direction vibration, an upper frame Y-direction vibration, an upper frame vertical vibration, a lower frame X-direction vibration, a lower frame Y-direction vibration, a lower frame vertical vibration, a top cover horizontal vibration X-direction, a top cover horizontal vibration Y-direction, a top cover horizontal vibration Z-direction, a stator core X-direction horizontal vibration and a stator base Z-direction horizontal vibration.
8. The utility model provides an unsteady state hydroelectric set start-up order confirming device which characterized in that includes:
the first sequencing module is used for determining a first starting sequence of the plurality of water-turbine generator sets according to the health degrees corresponding to the plurality of water-turbine generator sets respectively;
the second sequencing module is used for determining a second starting sequence of the plurality of water-turbine generator sets according to the operating states respectively corresponding to the plurality of water-turbine generator sets;
the first determining module is used for respectively determining annual accumulated running time of the plurality of water-turbine generator sets deviating from the optimal working condition; and
and the third sequencing module is used for determining the target starting sequence of the plurality of water-turbine generator sets under the unsteady working condition according to the first starting sequence, the second starting sequence and the annual accumulated running time.
9. The apparatus of claim 8, wherein the apparatus further comprises:
the first acquisition module is used for respectively acquiring the cavitation erosion quantity of the rotating wheel, the crack length of the rotating wheel and the quantity of unprocessed defects in the preset time of the plurality of water-turbine generator sets; and
the second determining module is used for determining a cavitation grade corresponding to the cavitation quantity of the rotating wheel, a crack grade corresponding to the crack length of the rotating wheel and a defect grade corresponding to the unprocessed defect quantity according to a preset grade rule;
and the third determining module is used for determining the health degrees corresponding to the plurality of water-turbine generator sets respectively according to the cavitation level, the crack level, the defect level and the corresponding first weight values respectively.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
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