CN113586324B - Method and device for determining startup sequence of hydroelectric generating set and storage medium - Google Patents
Method and device for determining startup sequence of hydroelectric generating set and storage medium Download PDFInfo
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The disclosure provides a method, a device and a storage medium for determining a startup sequence of a hydroelectric generating set, wherein the method comprises the following steps: determining a first starting sequence of the plurality of water-turbine generator sets according to the operation efficiency corresponding to the plurality of water-turbine generator sets respectively; determining a second starting sequence of the plurality of hydroelectric generating sets according to the health degrees corresponding to the plurality of hydroelectric generating sets respectively; determining accumulated running time corresponding to each of the plurality of water-turbine generator sets; and determining the target starting-up sequence of the plurality of hydroelectric generating sets according to the first starting-up sequence, the second starting-up sequence and the accumulated running time, so that the starting-up sequence of the hydroelectric generating sets is more scientific and reasonable, and meanwhile, the equipment safety and the economic benefit of the hydropower station are ensured.
Description
Technical Field
The disclosure relates to the technical field of hydropower plant equipment, in particular to a method and a device for determining a startup sequence of a hydroelectric generating set and a storage medium.
Background
In the actual operation and maintenance process of the hydropower station, the operation state evaluation of the hydropower station is often focused on unit maintenance and state overhaul, and the optimized operation of the hydropower station is lacked. For example: at present, the on-off sequence management of a plurality of hydroelectric generating sets at a certain plant station has not been studied clearly, the on-off of the hydroelectric generating sets is only judged subjectively by operators on duty, and generally, the set with important equipment defects in the operation process is generally selected to be finally started; for a unit with relatively poor unit index in the overhaul process, the unit is generally selected to be started last; and selecting and finally starting other units with corresponding maintenance and defect elimination services.
However, the staff has a large difference in understanding the status of the equipment, and the definitions of the defects of the equipment are not completely the same among different staff, so that the control of the on-off sequence of the different staff has a large difference. In addition, the on-off sequence only considers the factors of the health state of the unit, and the efficiency of the unit is not considered, and the probability of the unit to fail can be reduced in terms of safety, but the highest-efficiency unit cannot be guaranteed to have higher running time in terms of economy.
In summary, the existing determining mode of the startup and shutdown sequence of the hydroelectric generating set mainly relies on subjective judgment by people and has single judgment factors, so that the economic value of the hydroelectric power plant is affected.
Disclosure of Invention
The application provides a method and a device for determining a startup sequence of a hydroelectric generating set and a storage medium, and aims to solve one of the technical problems in the related art to at least a certain extent.
An embodiment of a first aspect of the present application provides a method for determining a startup sequence of a water turbine generator set, including: determining a first starting sequence of the plurality of water-turbine generator sets according to the operation efficiency corresponding to the plurality of water-turbine generator sets respectively; determining a second starting sequence of the plurality of hydroelectric generating sets according to the health degrees corresponding to the plurality of hydroelectric generating sets respectively; determining accumulated running time corresponding to each of the plurality of water-turbine generator sets; and determining the target starting-up sequence of the plurality of hydroelectric generating sets according to the first starting-up sequence, the second starting-up sequence and the accumulated running time.
An embodiment of a second aspect of the present application provides a device for determining a startup sequence of a water turbine generator set, including: the first sequencing module is used for determining a first starting sequence of the plurality of water-turbine generator sets according to the operation efficiency 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 health degrees corresponding to the plurality of water-turbine generator sets respectively; the first determining module is used for determining accumulated running time corresponding to each of the plurality of water-turbine generator sets; and the third sequencing module is used for determining the target starting-up sequence of the plurality of water-turbine generator sets according to the first starting-up sequence, the second starting-up sequence and the 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 method for determining the startup sequence of the hydro-generator set.
An embodiment of a fourth aspect of the present application proposes a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method for determining a startup sequence of a hydro-generator set disclosed in the embodiment of the present application.
In this embodiment, according to the operation efficiencies respectively corresponding to the plurality of hydro-generator sets, a first startup sequence of the plurality of hydro-generator sets is determined, and according to the health degrees respectively corresponding to the plurality of hydro-generator sets, a second startup sequence of the plurality of hydro-generator sets is determined, and the accumulated operation time respectively corresponding to the plurality of hydro-generator sets is determined, and according to the first startup sequence, the second startup sequence, and the accumulated operation time, a target startup sequence of the plurality of hydro-generator sets is determined. Therefore, the starting-up sequence of the plurality of hydroelectric generating sets can be determined by combining various factors such as the operation efficiency, the health degree and the accumulated operation time of the hydroelectric generating sets, and the equipment safety and the economic benefit of the hydroelectric generating set can be ensured simultaneously. In addition, compared with human judgment, the technical scheme can determine the starting sequence according to the data, so that the starting sequence is more scientific and reasonable, and the working efficiency of the hydropower station is improved. The method solves the technical problems that the method for determining the startup and shutdown sequence of the hydroelectric generating set in the related technology mainly depends on artificial subjective judgment and has single judgment factors, so that the economic value of the hydroelectric power plant is influenced.
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.
Drawings
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, in which:
fig. 1 is a flowchart of a method for determining a startup sequence of a hydro-generator set according to an embodiment of the disclosure;
fig. 2 is a flowchart of a method for determining a startup sequence of a hydro-generator set according to another embodiment of the disclosure;
FIG. 3a is a two-dimensional distribution of vane opening data according to an embodiment of the present disclosure;
FIG. 3b is a schematic diagram of a first load zone according to an embodiment of the present disclosure;
FIG. 3c is a schematic diagram of a value interval of a first load interval according to an embodiment of the present disclosure;
FIG. 4a is a two-dimensional distribution of hydro-generator stator heat generation data in accordance with an embodiment of the disclosure;
FIG. 4b is a schematic diagram of a second load zone of a stator according to an embodiment of the present disclosure;
FIG. 4c is a schematic illustration of a value interval of a second load zone of a stator according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of a hydro-generator set start-up sequence determining device according to another embodiment of the present disclosure;
Fig. 6 is a schematic diagram of a hydro-generator set start-up sequence determining device according to another embodiment of the present disclosure;
fig. 7 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present application.
Detailed Description
Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present disclosure and are not to be construed as limiting the present disclosure. On the contrary, the embodiments of the disclosure include all alternatives, modifications, and equivalents as may be included within the spirit and scope of the appended claims.
Aiming at the problems that the starting and stopping sequence determining mode of the hydroelectric generating set in the background technology mainly depends on artificial subjective judgment and single judgment factor, so that the economic value of a hydropower plant is influenced, the technical scheme of the embodiment provides a method for determining the starting and stopping sequence of the hydroelectric generating set, and the method is described below with reference to specific embodiments.
It should be noted that, the execution body of the method for determining the startup sequence of the hydro-generator set in this embodiment may be a device for determining the startup sequence of the hydro-generator set, where the device may be implemented in a software and/or hardware manner, and the device may be configured in an electronic device, where the electronic device may include, but is not limited to, a terminal, a server, and so on.
Fig. 1 is a flow chart of a method for determining a startup sequence of a hydro-generator set according to an embodiment of the disclosure, 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 operation efficiencies respectively corresponding to the plurality of water-turbine generator sets.
In the embodiment of the disclosure, the first starting-up sequence of the plurality of water turbine generator sets may be determined according to the operation efficiencies respectively corresponding to the plurality of water turbine generator sets.
The plurality of hydroelectric generating sets are arranged in the hydropower station and used for generating hydropower, the number of the plurality of hydroelectric generating sets can be determined according to the scale of the hydropower station, and the hydropower station is not limited.
The operation efficiency can represent the corresponding work efficiency of each hydroelectric generating set in the operation process, the plurality of hydroelectric generating sets can respectively correspond to the operation efficiency of the hydroelectric generating sets, and the operation efficiency can be represented by any index of the hydroelectric generating sets, so that the operation efficiency is not limited.
The sequence obtained by sequencing the plurality of hydro-generator sets according to the operation efficiency may be referred to as a first start-up sequence, for example: the first startup sequence is obtained by sequencing the plurality of water turbine generator sets from high to low according to the operation efficiency, that is, the startup sequence of the plurality of water turbine generator sets can be determined according to the operation efficiency of the water turbine generator sets.
For example, a plurality of hydro-generator sets such as: unit 1, unit 2, unit 3, unit 4 and unit 5, a first start-up 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 hydroelectric generating sets according to the health degrees respectively corresponding to the plurality of hydroelectric generating sets.
After the first startup sequence is determined, further, the embodiment of the disclosure may further determine a second startup sequence of the plurality of hydro-turbo generator sets according to health degrees corresponding to the plurality of hydro-turbo generator sets respectively.
The health degree is used for describing the health condition or abnormal condition in the operation process of the hydro-generator set, and the health degree can be represented by one or more indexes, which is not limited herein.
And the plurality of hydro-generator sets are ordered according to the health degree, the obtained sequence may be called a second starting-up sequence, for example: the second startup sequence is obtained by sequencing the plurality of hydro-turbo generator sets from low to high according to the health degree, that is, the startup sequence of the plurality of hydro-turbo generator sets can be determined according to the health degree of the hydro-turbo generator sets according to the embodiment of the disclosure, and the second startup sequence is as follows: unit 4, unit 1, unit 2, unit 3, unit 5.
S103: and determining the accumulated running time corresponding to each of the plurality of water-turbine generator sets.
Further, the respective accumulated operating times of the plurality of hydro-generator sets are determined, wherein the accumulated operating time may be an annual accumulated operating time, or may also be an accumulated operating time calculated from the installation time, which is not limited herein.
The steps S101, S102, and S103 may be performed simultaneously or in random order, without limitation.
S104: and determining the target starting-up sequence of the plurality of water-turbine generator sets according to the first starting-up sequence, the second starting-up sequence and the accumulated running time.
In some embodiments, the first power-on sequence, the second power-on sequence, and the accumulated running time may respectively correspond to different weight values. In the process of determining the target starting sequence, the position, the accumulated running time and the corresponding weight value of the water-turbine generator set in the first starting sequence and the second starting sequence can be combined to perform weighted calculation, and then the plurality of water-turbine generator sets are sequenced according to the weighted calculation result to obtain the target starting sequence. Thus, the target power-on sequence may have different emphasis, such as: the efficiency, the health degree and the like can be strategically biased in the starting process, so that the target starting sequence can be flexibly determined according to different weight values.
In other embodiments, a first time difference value for the longest aggregate run time and the shortest aggregate run time may also be calculated. In practical application, a plurality of hydroelectric generating sets: the cumulative operation time 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, and then the unit with the longest cumulative operation time can be represented by tlmax=max { TL1, TL2, TL3, TL4 and TL5}, and the unit with the shortest cumulative operation time can be represented by tlmin=min { TL1, TL2, TL3, TL4 and TL5}, and the first time difference value=tlmax-TLmin. Further, the first time difference value is compared with a first threshold value, and whether the first time difference value is larger than or equal to the first threshold value is judged. The first threshold may be flexibly determined according to an actual application scenario, for example: and if the first threshold value is equal to 1000 hours, judging whether the first time difference value is greater than or equal to the first threshold value, namely: it is determined whether the first time difference +.1000 is true. If the first time difference is greater than or equal to the first threshold (1000 hours), the longest unit of accumulated running time in the first startup sequence is moved to the last startup position to obtain a third startup sequence, for example: the longest unit of the accumulated running time is unit 2 (1500 hours of the accumulated running time), and the shortest unit of the accumulated running time is unit 3 (300 hours of the accumulated running time), the first time difference is equal to or larger than 1000. In this case, the longest unit of accumulated running time in the first startup sequence (i.e., unit 2) is moved to the last startup position, and the corresponding third startup sequence is: and if the first time difference value is not greater than or equal to the first threshold value, the first starting sequence is used as the third starting sequence. Further, a predetermined number of low health units are determined according to the second power-on sequence, for example: and if the preset number is 2, selecting two units with low health degree according to the second starting sequence, namely: the units 4 and 1 and the positions of the units with low health degree in the third starting sequence are moved backwards, namely: in the third starting-up sequence, the positions of the unit 4 and the unit 1 are shifted backwards (for example, shifted backwards by one bit), and the target starting-up sequence is obtained as follows: unit 3, unit 1, unit 5, unit 4, unit 2. Therefore, the target starting-up sequence determined by adopting the sequencing mode of the embodiment can select the most efficient and healthiest unit to start up preferentially, so that the equipment safety and the economic benefit of the hydropower station can be ensured simultaneously.
Some embodiments may also determine the running status and defect type of each unit before determining the target start-up sequence according to the accumulated running time, and if the unit has a type a defect (for example, serious defect causes no work), the unit may be removed from the first start-up sequence and prompted; if the unit has a B-type defect (such as a general defect, can work), the unit is moved to a last starting position.
In some embodiments, a shutdown sequence of a plurality of hydro-generator sets may also be determined.
Specifically, the target startup sequence is inverted to obtain a candidate shutdown sequence, and the target startup sequence is combined: the unit 3, the unit 1, the unit 5, the unit 4 and the unit 2, and the candidate shutdown sequence is as follows: unit 2, unit 4, unit 5, unit 1, unit 3.
Further, determining continuous operation time corresponding to each of the plurality of water turbine generator sets, wherein the continuous operation time is, for example, the operation time from the last starting up of the set to the statistical time node operation time, and the plurality of water turbine generator sets: the corresponding continuous operation times of the units 1, 2, 3, 4 and 5 can be represented by TC1, TC2, TC3, TC4 and TC5 respectively.
Further, a second time difference between the longest continuous operation time unit and the shortest continuous operation time unit is calculated, and whether the second time difference is greater than or equal to a second threshold is determined.
The longest continuous running time unit may be represented by tcmax=max { TC1, TC2, TC3, TC4, TC5}, and the shortest continuous running time unit may be represented by tcmin=min { TC1, TC2, TC3, TC4, TC5}, and the second time difference value=tcmax-TCmin. Further, the second time difference value is compared with a second threshold value, and whether the second time difference value is larger than or equal to the second threshold value is judged. The second threshold may be flexibly determined according to an actual application scenario, for example: and if the second threshold is 100 hours, judging whether the second time difference value is greater than or equal to the second threshold, namely: it is determined whether the second time difference ∈100 is true. If the second time difference is greater than or equal to the second threshold, moving the longest continuous running time unit in the candidate shutdown sequence to the first shutdown position, and moving the shortest continuous running time unit to the last shutdown position to obtain a target shutdown sequence, for example: the longest unit with continuous operation time is the unit 4, the shortest unit with continuous operation time is the unit 5, then the unit 4 is moved to the first shutdown position in the candidate shutdown sequence, the unit 5 is moved to the last shutdown position in the candidate shutdown sequence, and the obtained target shutdown sequence is as follows: unit 4, unit 2, unit 1, unit 3, unit 5. And if the second time difference value is smaller than the second threshold value, otherwise, taking the candidate shutdown sequence as a target shutdown sequence. Therefore, in the process of determining the shutdown sequence, the continuous operation time of the unit can be combined, so that the service life of the unit can be prolonged while the economic benefit is ensured.
According to the embodiment of the disclosure, a first starting-up sequence of the plurality of hydroelectric generating sets is determined according to the operation efficiency respectively corresponding to the plurality of hydroelectric generating sets, a second starting-up sequence of the plurality of hydroelectric generating sets is determined according to the health degree respectively corresponding to the plurality of hydroelectric generating sets, the accumulated operation time respectively corresponding to the plurality of hydroelectric generating sets is determined, and the target starting-up sequence of the plurality of hydroelectric generating sets is determined according to the first starting-up sequence, the second starting-up sequence and the accumulated operation time. Therefore, the determined target starting-up sequence can be combined with various factors such as the operation efficiency, the health degree, the accumulated operation time and the like of the hydroelectric generating set, so that the equipment safety and the economic benefit of the hydroelectric generating set can be ensured at the same time. In addition, compared with human judgment, the technical scheme can determine the starting sequence according to the data, so that the starting sequence is more scientific and reasonable, and the working efficiency of the hydropower station is improved. The method solves the technical problems that the method for determining the startup and shutdown sequence of the hydroelectric generating set in the related technology mainly depends on artificial subjective judgment and has single judgment factors, so that the economic value of the hydroelectric power plant is influenced.
Fig. 2 is a flow chart of a method for determining a startup sequence of a hydro-generator set according to another embodiment of the disclosure, as shown in fig. 2, the method includes:
S201: and respectively acquiring the opening data of the guide vanes in the preset time of the plurality of water turbine generator sets.
In some embodiments, vane opening data within a predetermined time of a plurality of hydro-generator sets may be obtained, for example: and acquiring guide vane opening data (data acquired in real time by using a sensor) of each hydroelectric generating set within one year, wherein the guide vane opening data can also correspond to organic set load data. In addition, in the process of acquiring the guide vane opening data, in order to improve the data accuracy, the guide vane opening data may be cleaned and filtered, for example: and eliminating abnormal data of the guide vane opening sensor during unit overhaul.
S202: and determining a guide vane opening average value of the hydroelectric generating set in a preset first load interval according to the guide vane opening data, and taking the guide vane opening average value as the running efficiency of the hydroelectric generating set.
The first load interval may be a load interval of the water-turbine generator set in a normal operation state, where the first load interval is, for example: 180-250MW interval. According to the embodiment of the disclosure, the average value of the guide vane opening data in the first load interval can be calculated and used as the running efficiency of the hydroelectric generating set. Generally, the lower the average value of the vane opening in the same load interval, the higher the running efficiency, for example: and the average value of the opening of the guide vanes of the unit 1 is 63%, and the average value of the opening of the guide vanes of the unit 2 is 67%, so that the running efficiency of the unit 1 is greater than that of the unit 2.
That is, the embodiment of the disclosure can adopt the guide vane opening degree data of the hydroelectric generating set as the operation efficiency, so that the operation efficiency of the set can be intuitively and accurately reflected through the guide vane opening degree.
In some embodiments, in an operation of determining a guide vane opening average value of a hydroelectric generating set in a preset first load interval according to guide vane opening data, a data two-dimensional distribution diagram may be established for the guide vane opening data and corresponding load data, and fig. 3a is a two-dimensional distribution diagram of the guide vane opening data according to an embodiment of the disclosure, as shown in fig. 3a, where the set load data is an ordinate, and the guide vane opening data is an abscissa.
Further, a first regression model may be constructed from the vane opening data and the corresponding load data for representing a relationship between vane opening and unit load, such as: a curve (i.e., a first regression model) is fitted to the data distribution in the two-dimensional distribution map.
In some embodiments, the unit load is taken as an independent variable by taking the single-machine guide vane opening data as an independent variable, and the regression equation between the independent variable Y and the independent variable x is set as follows: y=β 0 +β 1 x 1 +ε, where β 0 、β 1 Epsilon represents the randomness error and is independently subject to normal distribution, which is a regression coefficient.
Will influence factor x 1 The following is carried into the above formula:
y i ＝β 0 +β i x i +ε i
obtaining a linear sample regression equation:
the estimation of regression coefficient in the linear regression equation adopts a least square method, and the sum of squares of residual errors:
couple SSE to beta 0 、β 1 And (3) obtaining a partial derivative, and enabling the partial derivative to be equal to zero, and obtaining a standard equation set after finishing:
by solving the above equation set, the regression coefficient β can be obtained 0 、β 1 To obtain the first regression model.
Other embodiments, the first regression model may alsoExpressed as: y=cx a +bx, or y=c 'ln (x+a')+b 'x, where a, a', b ', c' are each part coefficient value (a>1) The solving method is the same as that of the solving process, and is not repeated here.
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, e.g., 180-250MW, as shown in fig. 3b, according to an embodiment of the present disclosure. The value interval of the first load interval may be determined according to an actual application scenario, and fig. 3c is a schematic diagram of the value interval of the first load interval according to an embodiment of the disclosure, as shown in fig. 3c, where the value interval in the embodiment may take 1MW.
Further, sampling is performed on the first regression model based on the first load interval and the value interval of the first load interval, and a plurality of guide vane opening sample data are determined. As shown in fig. 3c, that is, the guide vane opening data corresponding to the loads of 180, 181, 182..250 MW are taken on the curve of the first regression model as guide vane opening sample data. Further, a first arithmetic average of a plurality of vane opening sample data is calculated, and the first arithmetic average is taken as a vane opening average.
S203: and determining a first starting sequence of the plurality of water-turbine generator sets according to the operation efficiencies respectively corresponding to the plurality of water-turbine generator sets.
The description of S203 may be specifically referred to the above embodiments, and will not be repeated here.
S204: and respectively acquiring heating data and runout data of a plurality of parts within a preset time of a plurality of water turbine generator sets.
Before determining the second starting-up sequence, the embodiment can also respectively acquire heating data and runout data of a plurality of components within a preset time of a plurality of hydro-generator sets.
In some embodiments, the plurality of components may include, for example, one or more of a hydro-generator up-lead, down-lead, water-lead, hydro-generator thrust bearing, hydro-generator stator, hydro-generator rotor, and any other possible component, and the heat generation data may be heat generation data of each of the above components during operation, without limitation.
The runout data includes, for example, one or more of an upper guide X-direction runout, an upper guide Y-direction runout, a water guide X-direction runout, a water guide Y-direction runout, a thrust X-direction runout, a thrust Y-direction runout, 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 of the hydro-generator, without limitation.
S205: and determining the average temperature value of the hydroelectric generating set in a preset second load interval according to the heating data.
The second load interval may be a load interval of the water-turbine generator set in a normal operation state, where the second load interval is, for example: and calculating the average value of heating data of each component to obtain a temperature average value when the water-turbine generator set runs in the 180-250MW load interval.
In some embodiments, in the operation of determining the average value of the temperatures of the hydro-generator set in the preset second load interval, the heating data of each component and the corresponding load data may be set up to form a data two-dimensional distribution map.
For example, the component is a hydro-generator stator, fig. 4a is a two-dimensional distribution diagram of heat generation data of the hydro-generator stator according to the embodiment of the disclosure, and as shown in fig. 4a, the heat generation data of the stator and the corresponding load data within one year are obtained through big data, and a coordinate system is established, wherein the unit load data is an abscissa, and the heat generation data (stator temperature) of the stator is an ordinate. The construction of the two-dimensional profile by the other components is similar to the hydro-generator stator and is not described in detail herein, so that there may be a corresponding two-dimensional profile for each component.
Further, a second regression model for representing the relationship between the heat generation condition of each component and the unit load is constructed based on the heat generation data of each component and the corresponding load data. For example: from the stator temperature and the corresponding load data in fig. 4a, a second regression model of the stator temperature is constructed, namely: the data distribution in the two-dimensional distribution graph according to fig. 4a fits a curve (i.e. the second regression model). Thus, a corresponding second regression model may be derived for each component.
The form of the second regression model may be the same as that of the first regression model, and will not be described here.
Further, a second load interval and a value interval of the second load interval are determined. Fig. 4b is a schematic diagram of a second load section of a stator according to an embodiment of the present disclosure, as shown in fig. 4b, the second load section being, for example, 180-250MW. The interval between the second load intervals may be determined according to an actual application scenario, and fig. 4c is a schematic diagram of the interval between the second load intervals of the stator according to an embodiment of the disclosure, as shown in fig. 4c, where the interval between the second load intervals may take 1MW.
Further, sampling is performed on the two-regression model based on the second load interval and the value interval of the second load interval, and a plurality of temperature sample data of the corresponding component are determined. For example: as shown in fig. 4c, the stator temperatures corresponding to the 180, 181, 182..250 MW load were taken on the curve of the second regression model as stator temperature sample data. Further, a second arithmetic mean of the plurality of temperature sample data for each component is calculated, for example: and carrying out average value calculation on the stator temperature sample data to obtain a second arithmetic average value of the stator.
It is understood that the calculation process of the second arithmetic mean of each component may be the same as that of the stator component, and will not be described herein. Thus, for each component a corresponding second arithmetic mean may be determined.
Further, a weighted average calculation is performed on a plurality of second arithmetic averages corresponding to the plurality of components, and a temperature average is determined. That is, different components may correspond to different weight values, and a weighted average calculation may be performed according to the second arithmetic average value of each component and the corresponding weight value, to obtain a temperature average value of each hydroelectric generating set, for example: temperature average = Σ (stator temperature second arithmetic mean × weight) second calculation of +rotor temperature mean +. Weight...)/n.
S206: and determining the runout average value of the hydroelectric generating set in a preset third load interval according to the runout data.
The third load interval may be a load interval of the water-turbine generator set in a normal operation state, for example: and calculating the average value of the runout data of each component in the 180-250MW interval, namely, the running of the hydro-generator set in the 180-250MW load interval, and obtaining the runout average value.
In some embodiments, in the operation of determining the average value of the runout of the hydro-generator set in the preset third load interval, a two-dimensional data distribution map (similar to the heat generation data and the vane opening data construction mode) may be established for the runout of each component and the corresponding load data.
For example, the runout data is upper guide X-direction runout data of the hydraulic generator, and the upper guide X-direction runout data and corresponding load data of the hydraulic generator in one year are obtained through big data, so that a two-dimensional distribution map is constructed.
Further, according to the runout data and the corresponding load data of each component, a third regression model for representing the relation between the vibration condition of each component and the unit load is constructed, so that the corresponding third regression model can be obtained for each component.
The form of the third regression model may be the same as the first regression model and the second regression model, and will not be described here.
Further, a third load interval and a value interval of the third load interval are determined, for example: the third load interval can take 180-250MW, and the third load interval can take 1MW.
Further, sampling is performed in a third regression model based on a third load interval and a value interval of the third load interval, and a plurality of runout sample data of the corresponding component are determined. For example: and taking the runout data corresponding to the loads of 180, 181 and 182 DEG and 250MW on a curve of a third regression model corresponding to the upper guide X direction of the hydraulic generator as upper guide X direction runout sample data of the hydraulic generator.
Further, a third arithmetic average of the plurality of runout sample data for each component is calculated, for example: and carrying out average value calculation on the upper guide X-direction runout sample data of the hydraulic generator to obtain a third arithmetic average value of the upper guide X-direction of the hydraulic generator.
It is to be understood that the calculation process of the third arithmetic mean value of each component may be the same as the calculation process of the guiding X direction on the hydraulic generator, and will not be described herein. Thus, a corresponding third arithmetic mean value may be determined for each component vibration condition.
Further, a weighted average calculation is performed on a plurality of third calculation number averages corresponding to the plurality of components, and a runout average value is determined. That is, different components may correspond to different weight values, and a weighted average calculation may be performed according to the third arithmetic average value of each component and the corresponding weight value, to obtain a runout average value of each hydroelectric generating set.
S207: and determining the health degree of the plurality of hydroelectric generating sets according to the temperature average value, the runout average value and the corresponding weight value.
For example, the temperature average value may be represented by JR, the runout average value may be represented by JZ, the weight value corresponding to the temperature average value is, for example, 0.3, and the weight value corresponding to the runout average value is, for example, 0.7, and then the health degree calculation formula of each hydro-generator set may be represented as follows: 0.3jr+0.7jz.
S208: and determining a second starting sequence of the plurality of hydroelectric generating sets according to the health degrees respectively corresponding to the plurality of hydroelectric generating sets.
S209: and determining the accumulated running time corresponding to each of the plurality of water-turbine generator sets.
S210: and determining the target starting-up sequence of the plurality of water-turbine generator sets according to the first starting-up sequence, the second starting-up sequence and the accumulated running time.
The descriptions of S208-S210 may be specifically referred to the above embodiments, and are not repeated here.
According to the embodiment of the disclosure, a first starting-up sequence of the plurality of hydroelectric generating sets is determined according to the operation efficiency respectively corresponding to the plurality of hydroelectric generating sets, a second starting-up sequence of the plurality of hydroelectric generating sets is determined according to the health degree respectively corresponding to the plurality of hydroelectric generating sets, the accumulated operation time respectively corresponding to the plurality of hydroelectric generating sets is determined, and the target starting-up sequence of the plurality of hydroelectric generating sets is determined according to the first starting-up sequence, the second starting-up sequence and the accumulated operation time. Therefore, the determined target starting-up sequence can be combined with various factors such as the operation efficiency, the health degree, the accumulated operation time and the like of the hydroelectric generating set, so that the equipment safety and the economic benefit of the hydroelectric generating set can be ensured at the same time. In addition, compared with human judgment, the technical scheme can determine the starting sequence according to the data, so that the starting sequence is more scientific and reasonable, and the working efficiency of the hydropower station is improved. In addition, in the process of determining the health degree and the operation efficiency of the unit, various influencing factors of various components are combined, and the final health degree, the operation efficiency and the like are determined in a big data statistical mode, so that the calculation result is more accurate, and the rationality of the starting sequence is further improved.
Fig. 5 is a schematic diagram of a hydro-generator set startup sequence determining device according to another embodiment of the present disclosure. As shown in fig. 5, the apparatus 50 for determining a startup sequence of a hydro-generator set includes:
the first sequencing module 501 is configured to determine a first starting-up sequence of the plurality of water-turbine generator sets according to operation efficiencies corresponding to the plurality of water-turbine generator sets respectively;
the second sequencing module 502 is configured to determine a second startup sequence of the plurality of hydro-generator sets according to health degrees corresponding to the plurality of hydro-generator sets respectively;
a first determining module 503, configured to determine accumulated operation times corresponding to the plurality of hydro-generator sets respectively; and
the third ordering module 504 is configured to determine a target startup sequence of the plurality of hydro-generator sets according to the first startup sequence, the second startup sequence, and the accumulated running time.
Optionally, in some embodiments, fig. 6 is a schematic diagram of a device for determining a startup sequence of a hydro-generator set according to another embodiment of the disclosure, as shown in fig. 6, where the device 50 further includes: the first obtaining module 505 is configured to obtain guide vane opening data in a predetermined time of the plurality of hydro-generator sets respectively; and a second determining module 506, configured to determine, according to the vane opening data, a vane opening average value of the hydroelectric generating set in a preset first load interval, and use the vane opening average value as an operating efficiency of the hydroelectric generating set.
Optionally, in some embodiments, the second determining module 506 is specifically configured to: constructing a first regression model for representing the relation between the opening degree of the guide vane and the load of the unit according to the opening degree data of the guide vane and the corresponding load data; determining a first load interval and a value interval of the first load interval; sampling in a first regression model based on a first load interval and a value interval of the first load interval, and determining a plurality of guide vane opening sample data; and calculating a first arithmetic average of the plurality of vane opening sample data, and taking the first arithmetic average as a vane opening average.
Optionally, in some embodiments, as shown in fig. 6, the apparatus 50 further includes: the second obtaining module 507 is configured to obtain heat data and runout data of a plurality of components within a predetermined time of the plurality of water-turbine generator sets respectively; a third determining module 508, configured to determine, according to the heating data, a temperature average value of the hydroelectric generating set in a preset second load interval; a fourth determining module 509, configured to determine a runout average value of the hydroelectric generating set in a preset third load interval according to the runout data; and a fifth determining module 510, configured to determine health degrees of the plurality of hydro-generator sets according to the temperature average value, the runout average value, and the corresponding weight values.
Optionally, in some embodiments, the third determining module 508 is specifically configured to: constructing a second regression model for representing the relation 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 second load interval and a value interval of the second load interval; sampling in a two-regression model based on the second load interval and the value interval of the second load interval, and determining a plurality of temperature sample data of each component; calculating a second arithmetic mean of the plurality of temperature sample data for each component; and carrying out weighted average calculation on a plurality of second arithmetic averages corresponding to the plurality of components to determine a temperature average.
Optionally, in some embodiments, the fourth determining module 509 is specifically configured to: constructing a third regression model for representing the relation 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 third load interval and a value interval of the third load interval; sampling in a third regression model based on a third load interval and a value interval of the third load interval, and determining a plurality of runout sample data of each component; calculating a third arithmetic mean of the plurality of runout sample data for each component; and carrying out weighted average calculation on a plurality of third calculation average values corresponding to the plurality of components, and determining a runout average value.
Optionally, in some embodiments, the third sorting module 504 is specifically configured to: calculating a first time difference value of the longest accumulated running time unit and the shortest accumulated running time unit, and judging whether the first time difference value is larger than or equal to a first threshold value; if the first time difference value is larger than the first threshold value, moving the longest unit of accumulated running time in the first starting sequence to a last starting position to obtain a third starting sequence; otherwise, the first starting sequence is used as a third starting sequence; and determining a preset number of units with low health degree according to the second starting sequence, and moving the positions of the units with low health degree in the third starting sequence backwards to obtain the target starting sequence.
Optionally, in some embodiments, as shown in fig. 6, the apparatus 50 further includes: the fourth sorting module 511 is specifically configured to: reversing the target startup sequence to obtain a candidate shutdown sequence; determining continuous operation time corresponding to each of the plurality of water-turbine generator sets; calculating a second time difference value of the continuous operation time longest unit and the continuous operation time shortest unit, and judging whether the second time difference value is larger than or equal to a second threshold value; if the second time difference value is larger than the second threshold value, moving the unit with the longest continuous operation time in the candidate shutdown sequence to the first shutdown position, and moving the unit with the shortest continuous operation time to the last shutdown position to obtain a target shutdown sequence; otherwise, the candidate shutdown sequence is used as the target shutdown sequence.
In this embodiment, according to the operation efficiencies respectively corresponding to the plurality of hydro-generator sets, a first startup sequence of the plurality of hydro-generator sets is determined, and according to the health degrees respectively corresponding to the plurality of hydro-generator sets, a second startup sequence of the plurality of hydro-generator sets is determined, and the accumulated operation time respectively corresponding to the plurality of hydro-generator sets is determined, and according to the first startup sequence, the second startup sequence, and the accumulated operation time, a target startup sequence of the plurality of hydro-generator sets is determined. Therefore, the starting-up sequence of the plurality of hydroelectric generating sets can be determined by combining various factors such as the operation efficiency, the health degree and the accumulated operation time of the hydroelectric generating sets, and the equipment safety and the economic benefit of the hydroelectric generating set can be ensured simultaneously. In addition, compared with human judgment, the technical scheme can determine the starting sequence according to the data, so that the starting sequence is more scientific and reasonable, and the working efficiency of the hydropower station is improved. The method solves the technical problems that the method for determining the startup and shutdown sequence of the hydroelectric generating set in the related technology mainly depends on artificial subjective judgment and has single judgment factors, so that the economic value of the hydroelectric power plant is influenced.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
In order to implement the above embodiments, the present application further provides a computer program product, which when executed by an instruction processor in the computer program product, performs the method for determining the startup sequence of the hydro-generator set according to the foregoing embodiments of the present application.
Fig. 7 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present application. The computer device 12 shown in fig. 7 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments herein.
As shown in fig. 7, the computer device 12 is in the form of a general purpose computing device. Components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry Standard architecture (Industry Standard Architecture; hereinafter ISA) bus, micro channel architecture (Micro Channel Architecture; hereinafter MAC) bus, enhanced ISA bus, video electronics standards Association (Video Electronics Standards Association; hereinafter VESA) local bus, and peripheral component interconnect (Peripheral Component Interconnection; hereinafter PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
Memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) 30 and/or cache memory 32. The computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, commonly referred to as a "hard disk drive").
Although not shown in fig. 7, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a compact disk read only memory (Compact Disc Read Only Memory; hereinafter CD-ROM), digital versatile read only optical disk (Digital Video Disc Read Only Memory; hereinafter DVD-ROM), or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the present application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, 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 or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods in the embodiments described herein.
The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer device 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Moreover, the computer device 12 may also communicate with one or more networks such as a local area network (Local Area Network; hereinafter LAN), a wide area network (Wide Area Network; hereinafter WAN) and/or a public network such as the Internet via the network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and hydro-generator set start-up sequence determination by running programs stored in the system memory 28, for example, implementing the hydro-generator set start-up sequence determination method mentioned in the foregoing embodiment.
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 application 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 application 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 is to be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected 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," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
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 further implementations are included within the scope of the preferred embodiment of the present application 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 embodiments of the present application.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," 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 present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. 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 will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (9)
1. The method for determining the startup sequence of the hydroelectric generating set is characterized by comprising the following steps of:
determining a first starting sequence of the plurality of water-turbine generator sets according to the operation efficiency corresponding to the plurality of water-turbine generator sets respectively;
determining a second starting sequence of the plurality of hydroelectric generating sets according to the health degrees respectively corresponding to the plurality of hydroelectric generating sets;
determining the corresponding accumulated running time of the plurality of water-turbine generator sets; and
determining target startup orders of the plurality of hydroelectric generating sets according to the first startup order, the second startup order and the accumulated operation time, wherein a first time difference value of a set with the longest accumulated operation time and a set with the shortest accumulated operation time is calculated, and judging whether the first time difference value is larger than or equal to a first threshold value: and if the first time difference value is greater than or equal to the first threshold value, moving the longest unit with accumulated running time in the first starting sequence to a last starting position to obtain a third starting sequence, otherwise, taking the first starting sequence as the third starting sequence, determining a preset number of units with low health degree according to the second starting sequence, and moving the positions of the units with low health degree in the third starting sequence backwards to obtain the target starting sequence.
2. The method of claim 1, wherein prior to determining the first start-up sequence for the plurality of hydro-generator sets based on the respective operating efficiencies for the plurality of hydro-generator sets, comprising:
respectively acquiring guide vane opening data of the plurality of hydroelectric generating sets within a preset time; and
and determining a guide vane opening average value of the hydroelectric generating set in a preset first load interval according to the guide vane opening data, and taking the guide vane opening average value as the running efficiency of the hydroelectric generating set.
3. The method of claim 2, wherein determining a vane opening average value of the hydro-generator set over a preset first load interval based on the vane opening data comprises:
constructing a first regression model for representing the relation between the opening degree of the guide vane and the load of the unit according to the opening degree data of the guide vane and the corresponding load data;
determining the value interval of the first load interval;
sampling in the first regression model based on the first load interval and the value interval of the first load interval, and determining a plurality of guide vane opening sample data; and
A first arithmetic average of the plurality of vane opening sample data is calculated and taken as the vane opening average.
4. The method of claim 1, wherein prior to determining the second power-on sequence of the plurality of hydro-generator sets according to the respective health degrees of the plurality of hydro-generator sets, further comprising:
respectively acquiring heating data and runout data of a plurality of components within a preset time of the plurality of hydroelectric generating sets;
determining a temperature average value of the hydroelectric generating set in a preset second load interval according to the heating data;
determining a runout average value of the hydroelectric generating set in a preset third load interval according to the runout data; and
and determining the health degree of the plurality of water turbine generator sets according to the temperature average value, the runout average value and the corresponding weight value.
5. The method of claim 4, wherein determining a temperature average of the hydro-generator set at a preset second load interval based on the heat generation data comprises:
constructing a second regression model for representing the relation 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 value interval of the second load interval;
sampling in the two-regression model based on the second load interval and the value interval of the second load interval, and determining a plurality of temperature sample data of each component;
calculating a second arithmetic mean of the plurality of temperature sample data for each component;
and carrying out weighted average calculation on a plurality of second arithmetic averages corresponding to the plurality of components, and determining the temperature average.
6. The method of claim 4, wherein determining a runout average value for the hydro-generator set over a preset third load interval based on the runout data comprises:
constructing a third regression model for representing the relation 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 value interval of the third load interval;
sampling in the third regression model based on the third load interval and the value interval of the third load interval, and determining a plurality of runout sample data of each component;
calculating a third arithmetic mean of the plurality of runout sample data for each component;
And carrying out weighted average calculation on a plurality of third calculation number average values corresponding to the plurality of components, and determining the runout average value.
7. The method as recited in claim 1, further comprising:
inverting the target startup sequence to obtain a candidate shutdown sequence;
determining continuous operation time corresponding to each of the plurality of water-turbine generator sets;
calculating a second time difference value of the continuous operation time longest unit and the continuous operation time shortest unit, and judging whether the second time difference value is larger than or equal to a second threshold value;
if the second time difference value is greater than or equal to the second threshold value, moving the longest continuous operation time unit in the candidate shutdown sequence to a first shutdown position, and moving the shortest continuous operation time unit to a last shutdown position to obtain a target shutdown sequence; otherwise, the candidate shutdown sequence is used as the target shutdown sequence.
8. The method of any of claims 4-6, wherein the plurality of components comprises at least one of:
the hydraulic generator comprises an upper guide, a lower guide, a water guide, a hydraulic generator thrust bearing bush, a hydraulic generator stator and a hydraulic generator rotor;
The runout data comprises 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.
9. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-8.
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| JPH09310674A (en) * | 1996-05-20 | 1997-12-02 | Toshiba Eng Co Ltd | Start control device for hydraulic turbine generator |
| CN102946117A (en) * | 2012-10-26 | 2013-02-27 | 广东电网公司电力调度控制中心 | Method and system for optimizing starting sequence of power generators |
| CN106523260A (en) * | 2016-11-17 | 2017-03-22 | 贵州电网有限责任公司电力科学研究院 | Guide vane opening degree based unit efficiency sequencing and load distributing method of hydropower station |
| CN112818549A (en) * | 2021-02-05 | 2021-05-18 | 四川大学 | Hierarchical dimension reduction dynamic planning method for hydropower station load optimized distribution |
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2021
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| JPH09310674A (en) * | 1996-05-20 | 1997-12-02 | Toshiba Eng Co Ltd | Start control device for hydraulic turbine generator |
| CN102946117A (en) * | 2012-10-26 | 2013-02-27 | 广东电网公司电力调度控制中心 | Method and system for optimizing starting sequence of power generators |
| CN106523260A (en) * | 2016-11-17 | 2017-03-22 | 贵州电网有限责任公司电力科学研究院 | Guide vane opening degree based unit efficiency sequencing and load distributing method of hydropower station |
| CN112818549A (en) * | 2021-02-05 | 2021-05-18 | 四川大学 | Hierarchical dimension reduction dynamic planning method for hydropower station load optimized distribution |
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