CN113565672A

CN113565672A - Operation control method and device for hydroelectric generating set and storage medium

Info

Publication number: CN113565672A
Application number: CN202110867006.9A
Authority: CN
Inventors: 胡勇胜; 赵训新; 何葵东; 罗立军; 张培; 王卫玉; 莫凡; 胡蝶; 罗红祥; 侯凯; 李崇仕; 王胜军; 金艳; 肖杨; 姜晓峰; 胡边; 徐跃云; 肖启志; 李晓龙; 石元
Original assignee: Hunan Wuling Power Technology Co Ltd; Wuling Power Corp Ltd
Current assignee: Hunan Wuling Power Technology Co Ltd; Wuling Power Corp Ltd
Priority date: 2021-07-29
Filing date: 2021-07-29
Publication date: 2021-10-29
Anticipated expiration: 2041-07-29
Also published as: CN113565672B

Abstract

The present disclosure provides a method, an apparatus and a storage medium for controlling operation of a hydroelectric generating set, including: determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which are respectively corresponding to the plurality of water-turbine generator sets under the steady-state working condition, determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the defect degrees, the second running state and the second accumulated running time which are respectively corresponding to the plurality of water-turbine generator sets under the unsteady state working condition, determining target hydroelectric generating set information for executing a power generation task according to a load distribution table recording various load distribution schemes of a plurality of hydroelectric generating sets, wherein the load distribution schemes are calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions, according to the starting sequence and the information of the water turbine generator sets, the operation of the water turbine generator sets is controlled, and the operation control effect of the water turbine generator sets can be improved.

Description

Operation control method and device for hydroelectric generating set and storage medium

Technical Field

The disclosure relates to the technical field of hydraulic power plant equipment, in particular to a method and a device for controlling operation of a water turbine generator set and a storage medium.

Background

In the actual operation and maintenance process of the hydropower station, the operation state evaluation of the hydropower unit usually focuses on unit maintenance and state maintenance, and the optimization operation of the hydropower station is lack of guidance. For example: at present, no clear research is carried out on the management of the starting and stopping sequence of a plurality of water-turbine generator sets in a certain station, the starting and stopping of the water-turbine generator sets are judged only by an on-duty person subjectively, and generally, the sets with important equipment defects existing in the operation process are generally selected to be started finally; generally selecting the unit with relatively poor unit index to be started finally in the maintenance process; and selecting other units with corresponding overhaul and defect elimination services and finally starting the units. Moreover, the running conditions of the units under different working conditions (such as a steady-state working condition and an unsteady-state working condition) are different, and the adoption of the unified starting sequence does not consider the influence factors under different working conditions, so that the determination of the starting sequence of the units is influenced. In addition, the knowledge of the on-duty personnel on the equipment state is greatly different, and the defect definitions of the equipment are not completely the same among different personnel, so that the control of different personnel on the starting and stopping sequence is greatly different, and the starting and stopping sequence only considers the running state of the unit, so that the probability of the unit failing can be reduced in safety, but the highest-efficiency unit cannot be guaranteed to have higher running time in economy.

In addition, the load distribution of a plurality of hydroelectric generating sets in a certain station is mainly based on automatic distribution, and the main distribution strategies comprise: and (4) average distribution principle. However, according to the unit output head efficiency curve, the unit efficiency begins to decrease after reaching a certain value along with the increase of the output, which results in that under a certain special condition, the water consumption of the non-average distribution mode is smaller, so that the total water consumption of the hydropower station is not always in an optimal state when the load is distributed evenly.

Disclosure of Invention

The application provides a method and a device for controlling the operation of a water turbine generator set and a storage medium, and aims to solve one of the technical problems in the related art to at least a certain extent.

The embodiment of the first aspect of the application provides a method for controlling the operation of a water turbine generator set, which comprises the following steps: determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which are respectively corresponding to the plurality of water-turbine generator sets under the steady-state working condition; determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the defect degrees, the second running state and the second accumulated running time which are respectively corresponding to the plurality of water-turbine generator sets under the unsteady state working condition; determining target hydroelectric generating set information for executing a power generation task according to a load distribution table for recording various load distribution schemes of a plurality of hydroelectric generating sets, wherein the load distribution scheme is calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions; and controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

The embodiment of the second aspect of the application provides a hydroelectric set operation control device, includes: the first determining module is used for determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which respectively correspond to the plurality of water-turbine generator sets under the steady-state working condition; the second determining module is used for determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the defect degrees, the second running state and the second accumulated running time which correspond to the plurality of water-turbine generator sets respectively under the unsteady state working condition; the third determining module is used for determining target hydroelectric generating set information for executing a power generation task according to a load distribution table for recording various load distribution schemes of the plurality of hydroelectric generating sets, wherein the load distribution schemes are calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions; and the control module is used for controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

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 storage stores instructions which can be executed 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 operation control method of the hydroelectric generating set.

A fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for controlling the operation of a water turbine generator set disclosed in the embodiments of the present application.

In the embodiment, a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition is determined according to the operating efficiency, the first operating state and the first accumulated operating time which respectively correspond to the plurality of water-turbine generator sets under the steady-state working condition, a second target starting sequence of the plurality of water-turbine generator sets under the unsteady-state working condition is determined according to the defect degree, the second operating state and the second accumulated operating time which respectively correspond to the plurality of water-turbine generator sets under the unsteady-state working condition, and target water-turbine generator set information for executing a power generation task is determined according to a load distribution table which records a plurality of load distribution schemes of the plurality of water-turbine generator sets, wherein the load distribution scheme is obtained by calculation based on a water consumption minimum model and hydropower station constraint conditions and by adopting an optimization algorithm, and is obtained according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information, and controlling the operation of the plurality of water turbine generator sets. Therefore, the starting sequence of the multiple units can be determined according to the steady-state working condition and the non-steady-state working condition respectively, and the starting sequence can be determined according to different influence factors of different working conditions in the process of determining the starting sequence, so that the determined starting sequence is more scientific and reasonable, and the equipment safety and the economic benefit of the hydropower station can be guaranteed at the same time. In addition, the embodiment can determine the optimal unit combination to execute the power generation task, so that the economic benefit of the hydraulic power plant can be improved. Furthermore, the operation control effect of the water turbine generator set can be improved.

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 of which:

fig. 1 is a schematic flow chart of a method for controlling the operation of a hydro-turbo generator set according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a load distribution table provided according to an embodiment of the present disclosure;

fig. 3 is a schematic flow chart diagram of a method for controlling the operation of a hydro-turbo generator set according to another embodiment of the present disclosure;

FIG. 4a is a two-dimensional distribution plot of vane opening data according to an embodiment of the present disclosure;

FIG. 4b is a schematic illustration of a first load interval according to an embodiment of the disclosure;

fig. 4c is a schematic diagram of a value interval of a first load interval according to an embodiment of the present disclosure;

FIG. 5a is a two-dimensional distribution diagram of the heat data of the stator of the hydraulic generator according to the embodiment of the present disclosure;

FIG. 5b is a schematic view of a second load zone of the stator according to an embodiment of the present disclosure;

fig. 5c is a schematic diagram of a value interval of a second load interval of a stator according to an embodiment of the disclosure;

fig. 6 is a schematic flow chart diagram of a method for controlling the operation of a hydro-turbo generator set according to another embodiment of the present disclosure;

fig. 7 is a schematic view of a hydro-turbo generator set operation control device provided according to another embodiment of the present disclosure;

fig. 8 is a schematic view of a hydro-turbo generator set operation control device provided according to another embodiment of the present disclosure;

FIG. 9 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 problem that the starting sequence and the unit load distribution mode of a plurality of water turbine generator sets cannot be reasonably determined in the background art, so that the economic value of a hydropower station is influenced, the technical scheme of the embodiment provides the operation control method of the water turbine generator sets, and the method is explained by combining with a specific embodiment.

It should be noted that an execution main body of the method for controlling the operation of the water turbine generator set in this embodiment may be a water turbine generator set operation control 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 controlling the operation of a hydro-turbo generator set according to an embodiment of the present disclosure, as shown in fig. 1, the method includes:

s101: and determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which are respectively corresponding to the plurality of water-turbine generator sets under the steady-state working condition.

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.

Under the steady-state working condition, the plurality of water turbine generator sets can be understood to operate under the good working condition, and when the plurality of water turbine generator sets operate under the steady-state working condition, the plurality of water turbine generator sets can have corresponding operating efficiency, operating state (first operating state) and accumulated operating time (first accumulated operating time).

And sequencing the starting sequence of the plurality of water turbine generator sets according to the operating efficiency, the first operating state, the first accumulated operating time and other factors, wherein the obtained sequence can be called as a first target starting sequence.

S102: and determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady working condition according to the defect degrees, the second running state and the second accumulated running time which are respectively corresponding to the plurality of water-turbine generator sets under the unsteady working condition.

Wherein, unsteady state operating mode can be understood as a plurality of hydroelectric set operation under deviating from good operating mode, for example: and the voltage regulation, no-load operation, non-recommended interval operation and the like are carried out on the unit, and the limitation is not carried out.

And when the plurality of water turbine generator sets operate under the unsteady working condition, the plurality of water turbine generator sets can have corresponding defect degrees, operating states (second operating states) and accumulated operating time (second accumulated operating time).

And sequencing the starting sequence of the plurality of water turbine generator sets according to the defect degree, the second running state, the second accumulated running time and other factors, wherein the obtained sequence can be called as a second target starting sequence.

S103: and determining target hydroelectric generating set information for executing a power generation task according to a load distribution table for recording various load distribution schemes of the plurality of hydroelectric generating sets, wherein the load distribution scheme is calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions.

Wherein, the power generation task is used for instructing the power station to generate electricity to the power generation task can correspond to there is the total amount of load, promptly: the hydropower station performs the total load of the power generation task, and the embodiment may first receive the total load of the power generation task. Furthermore, the load distribution table for recording various load distribution schemes of the plurality of hydroelectric generating sets can be read.

For example, the plurality of hydroelectric generating sets include, for example, a set No. 1, a set No. 2, a set No. 3, a set No. 4, and a set No. 5, and the plurality of hydroelectric generating sets may have different load distribution schemes under different total loads. Fig. 2 is a schematic structural diagram of a load distribution table provided according to an embodiment of the present disclosure, and as shown in fig. 2, each row of the load distribution table represents a load distribution scheme, for example: the first row represents a power generation task with a total load of 70 ten thousand kw, and the power generation task with 70 ten thousand kw is completed by starting the No. 2 unit load of 24 ten thousand kw, starting the No. 4 unit load of 23 ten thousand kw, and starting the No. 5 unit load of 23 ten thousand kw.

The load distribution table is obtained by calculating various load distribution schemes based on a minimum water consumption model and hydropower station constraint conditions and by adopting an optimization algorithm, namely, each load distribution scheme is obtained by calculating the optimization algorithm on the premise of meeting the hydropower station constraint conditions and the minimum water consumption, and the load distribution table can be continuously calculated, and is calculated in real time under the condition that the constraint conditions and the water consumption are changed, so that the load distribution scheme in the load distribution table is the optimal distribution scheme.

In some embodiments, the minimum water consumption model is expressed as:

wherein W is the total water consumption of the hydropower station,

in a time period t, the ith hydroelectric generating set works at a working water head of Ht and a load of Ht

The current generation flow rate; Δ T represents a period duration;

showing the state of the water-turbine generator set i in the time period t when the water-turbine generator set is stopped

Runtime

Q_up，i，Q_dn，iRespectively representing the water consumption in the starting and stopping processes, including the water consumption converted by mechanical wear and the like of the units in the starting and stopping processes, wherein N is the number of the hydropower station units; t is the number of the scheduling period time.

In other embodiments, the hydropower station constraints include at least one of:

load balance constraint of hydropower station:

e is the total power generation amount of the power station, Ni (t) is the load born by the ith unit under the load requirement in the t period;

and (3) restriction of upstream water level of the hydropower station: z_min≤Z≤Z_maxZ is the operating water level of the power station, Z_min、Z_maxRespectively the upper and lower limits of the upstream water level of the power station in each period;

secondly, water level amplitude variation constraint: i Z '-Z' < delta Z, wherein Z 'and Z' are respectively the initial and final water levels of the power station in time period, and delta Z is the maximum allowable value of water level amplitude variation;

output restraint of the hydroelectric generating set: p_min≤P_i(t)≤P_max，P_min，P_maxThe output of the unit of the ith unit is respectively the upper limit and the lower limit;

fourthly, the generating flow of the hydroelectric generating set is restrained: q_min≤Q_i(t)≤Q_max，_Qmin，Q_maxThe minimum and maximum generating flow of the ith unit respectively;

fifth, restricting the running water head of the hydropower station: h_min≤H≤H_maxH is the operating head of the plant, H_minIs the minimum stable operating head, H, of the power station_maxThe maximum stable operation water head of the power station;

sixthly, rotating reserve capacity constraint:

is the sum of the installed capacity of the machine set,

is the total output of the unit, and Nmin is the lower limit of the rotating reserve capacity of the power station;

the constraint of the unit non-operational area is provided, wherein, for example, the division of the unit operational area is shown in table 1:

TABLE 1

The non-recommended operating region (vortex region), non-recommended operating region (cavitation region), and prohibited operating region (vibration region) may be non-operable regions.

And (b) restricting the start-up and shutdown time of the unit: x_Ki≥ _KiTOr X_Gi≥ _GiT，X_KiIs the starting time of the ith unit, T_KiIs the lower limit of the starting time of the ith unit, X_GiDown time of ith unit, T_GiIs the lower limit of the downtime of the ith unit.

In other embodiments, the optimization algorithm may be, for example, a dynamic programming algorithm, and the calculation process for solving the load distribution method by using the dynamic programming method is as follows:

taking k as 1,2. n as a calculation stage number, and calculating the corresponding optimal flow of the power station by stage by recursion according to the sequence of the number of the water-turbine generator sets and the load of the hydropower station from small to large, wherein the recursion calculation formula is as follows:

wherein the content of the first and second substances,

the total load of the units from 1 to k in the k stage is shown,

represents a total load of

Under the condition of a water head H, optimizing the total working flow when distributing the load among No. 1-k units,

indicating a boundary condition, and the initial value is 0.

It is understood that the above example is only illustrative of solving the load distribution table by using a dynamic programming algorithm, and in practical applications, the load distribution table may be solved by using any other possible optimization algorithm, for example: the load distribution table can also be solved by adopting an annealing particle swarm algorithm, which is not limited in this respect.

Further, the target hydroelectric generating set information for determining to execute the power generation task from the plurality of hydroelectric generating sets can be determined according to the total load and the load distribution table.

The target hydro-generator set information includes, for example, the number, serial number, and load amount of the target hydro-generator set, and any other possible information, which is not limited in this respect.

For example, if the total load amount of the power generation task is 70 ten thousand kw, the load distribution scheme determined according to the load distribution table is 24 ten thousand kw of the No. 2 unit load, 23 ten thousand kw of the No. 4 unit load, and 23 ten thousand kw of the No. 5 unit load, the number of the target water-turbine generator sets is 3, the numbers of the target water-turbine generator sets are No. 2, No. 4, and No. 5, and the load amounts of the target water-turbine generator sets are 24 ten thousand kw, 23 ten thousand kw, and 23 ten thousand kw in this order.

In some embodiments, each row of data of the load distribution table represents a load distribution scheme, and the operation of determining the target number of the hydro-turbo generator sets, and the target load amount of the hydro-turbo generator sets to perform the power generation task from among the plurality of hydro-turbo generator sets, based on the total amount of the load and the load distribution table, includes the steps of:

step 1: selecting a J-th line from the load distribution table, wherein the J-th line belongs to any line of the load distribution table;

step 2: calculate the total load of J rows

Wherein N (J, k) represents the load capacity of the kth unit on the J-th row;

step 3: judgment J₁If J is equal to the total load of the power generation task₁If the load is equal to the total load of the power generation task, taking the number of the J-th line of units as the number of the target water-turbine generator sets, and taking the load of the J-th line of units as the load of the target water-turbine generator sets; if J₁If the total load of the power generation task is less than the total load of the power generation task, executing J +1 and turning Step 2; if J₁And if the total load of the generating task is greater than the total load of the generating task, adjusting the load of the J-th line unit by adopting a two-point linear interpolation method to obtain the load of the target hydroelectric generating set.

In actual practice, each row of the load distribution table may be traversed to determine if there are rows equal to the total amount of load of the power generation task (i.e., the load distribution scheme). If so, taking the running machine set of the row as a target hydroelectric generating set; and if not, determining the row with the total load being greater than the total load and being closest to the total load, and taking the running unit of the row as the target water-turbine generator set.

For example, if J is 1, i.e. the 1 st row of the load distribution table is selected, the total load of the 1 st row is calculated

And J₁The number of the units working in the 1 st row is taken as the number of the target hydroelectric generating sets, and the number of the target hydroelectric generating sets is set to be No. 2 unit, No. 4 unit and No. 5 unit correspondingly, and the load capacity of the target hydroelectric generating sets is 24 ten thousand kw, 23 ten thousand kw and 23 ten thousand kw in sequence; if J is 4, then choose the second of the load distribution table4 lines, then calculate the total load of the 4 th line

Less than the total amount of load for the power generation mission (e.g., 70 ten thousand kw), J ═ J +1, where the rows of the load distribution table may cycle through, for example: when J +1 traverses to the 1 st line, Step2 is executed continuously; and if the 1 st row does not exist in the load distribution table, and the total power of the 2 nd row (J is 2) is determined to be larger than and closest to the total load amount of the power generation task after the traversal, taking the machine set operated in the 2 nd row as a target hydroelectric generating set, and adjusting (for example, adjusting by adopting a two-point linear interpolation method) the load amount of the 2 nd row machine set to obtain the load amount of the target hydroelectric generating set.

S104: and controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

After the first target starting sequence, the second target starting sequence and the target hydroelectric generating set information are determined, the plurality of hydroelectric generating sets can be further controlled according to the first target starting sequence, the second target starting sequence and the target hydroelectric generating set information, for example: and when a first target starting sequence is adopted under a steady-state working condition, or a second target starting sequence is adopted under an unsteady-state working condition, or a power generation task is received, the information of the target water-turbine generator set can be determined to execute the power generation task.

Fig. 3 is a schematic flow chart of a method for controlling the operation of a hydro-turbo generator set according to another embodiment of the present disclosure, and as shown in fig. 3, determining a first target startup sequence of a plurality of hydro-turbo generator sets under a steady-state operating condition includes:

s301: and respectively acquiring guide vane opening data of the plurality of water turbine generator sets in preset time.

In this embodiment, can acquire the stator opening data in a plurality of hydroelectric set scheduled times under the steady state operating mode respectively, for example: and acquiring guide vane opening data (data acquired by using a sensor in real time) of each hydroelectric generating set within one year, wherein the guide vane opening data can also correspond to set load data. In addition, in the process of acquiring the guide vane opening data, the guide vane opening data can be cleaned and filtered for improving the data accuracy, for example: and eliminating abnormal data of the unit during maintenance and the guide vane opening sensor.

S302: and determining the guide vane opening average value of the water-turbine generator set in a preset first load interval according to the guide vane opening data, and taking the guide vane opening average value as the operating efficiency of the water-turbine generator set.

Wherein, first load interval can be the load interval under hydroelectric set normal operating condition, and first load interval is for example: 180-250MW interval. The embodiment of the disclosure can calculate the average value of the guide vane opening data in the first load interval as the operating efficiency of the water turbine generator set. Generally, in the same load interval, the lower the average value of the opening degree of the guide vane is, the higher the operation efficiency is, for example: the average value of the opening degree of the guide vanes of the unit 1 is 63%, the average value of the opening degree of the guide vanes of the unit 2 is 67%, and then the running efficiency of the unit 1 is greater than that of the unit 2. That is to say, this disclosed embodiment can adopt hydroelectric set's stator opening data as operating efficiency, consequently can be directly perceived accurate reflection unit's operating efficiency through the stator opening.

In some embodiments, in the operation of determining the average value of the guide vane opening of the hydro-turbo generator set in the preset first load interval according to the guide vane opening data, a data two-dimensional distribution graph may be established according to the guide vane opening data and the corresponding load data, and fig. 4a is a two-dimensional distribution graph of the guide vane opening data according to the embodiment of the disclosure, as shown in fig. 4a, where the unit load data is a vertical coordinate and the guide vane opening data is a horizontal coordinate.

Further, a first regression model for representing the relationship between the guide vane opening and the unit load may be constructed according to the guide vane opening data and the corresponding load data, for example: a curve (i.e., a first regression model) is fitted to the data distribution in the two-dimensional distribution map.

In some embodiments, the regression equation between the dependent variable Y and the independent variable x may have the following forms, where the dependent variable is the opening data of the single-machine guide vane and the unit load is the independent variable: y ═ beta₀+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:

y_i＝β₀+β_ix_i+ε_i

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 ═ cx^a+ 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, the first load interval and the value interval of the first load interval are determined. FIG. 4b is a schematic diagram of a first load interval according to an embodiment of the disclosure, as shown in FIG. 4b, the first load interval is, for example, 180 MW and 250 MW. The value interval of the first load interval may be determined according to an actual application scenario, and fig. 4c is a schematic diagram of the value interval of the first load interval according to the embodiment of the present disclosure, as shown in fig. 4c, the 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 guide vane opening sample data are determined. As shown in fig. 4c, that is, the guide vane opening data corresponding to 180, 181, 182.. 250MW loads are taken from the curve of the first regression model as the guide vane opening sample data. Further, a first arithmetic mean value of the plurality of guide vane opening degree sample data is calculated, and the first arithmetic mean value is used as the guide vane opening degree mean value.

S303: and determining a first starting sequence of the plurality of water-turbine generator sets according to the operating efficiency corresponding to the plurality of water-turbine generator sets under the steady-state working condition.

Further, the plurality of hydroelectric generating sets are sorted according to the average value of the opening degree of the guide vanes (operation efficiency), and the obtained sequence may be referred to as a first starting sequence, for example: the plurality of water-turbine generator sets are sequenced from high to low according to the operation efficiency to obtain the first starting sequence, namely, the starting 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-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.

S304: 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, the heating data and the runout data of a plurality of components in a preset time of a plurality of water turbine generator sets can be respectively acquired, and the heating data and the runout data of the embodiment are the heating data and the runout data of the water turbine generator sets collected under the steady-state working condition.

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.

S305: and determining the temperature average value of the water-turbine generator set in a preset second load interval according to the heating data.

Wherein, the second load interval can be the load interval under hydroelectric set normal operating condition, and the second load interval is for example: and in the 180-250MW interval, namely, when the water turbine generator set runs in the 180-250MW load interval, calculating the average value of the heating data of each component to obtain the temperature average value.

In some embodiments, in the operation of determining the average value of the temperature of the hydro-turbo set in the preset second load interval, the heat generation data of each component and the corresponding load data may be used to establish a data two-dimensional distribution map.

For example, the component is a stator of a hydro-generator, fig. 5a 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. 5a, the heating data of the stator within one 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, a second regression model for representing the relationship between the heating condition of each component and the unit load is constructed according to the heating data of each component and the corresponding load data. For example: from the stator temperatures and the corresponding load data in fig. 5a, a second regression model of the stator temperatures is constructed, namely: a curve (i.e., a second regression model) is fitted to the data distribution in the two-dimensional distribution plot of fig. 5 a. Thus, a corresponding second regression model may 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, a second load interval and a value interval of the second load interval are determined. FIG. 5b is a schematic diagram of a second load interval of the stator according to the embodiment of the disclosure, as shown in FIG. 5b, the second load interval is, for example, 180 MW. The value interval of the second load interval may be determined according to an actual application scenario, and fig. 5c is a schematic diagram of the value interval of the second load interval of the stator according to the embodiment of the present disclosure, as shown in fig. 5c, the value interval in this embodiment may be 1 MW.

And further, sampling in the two regression models based on the second load interval and the value interval of the second load interval, and determining a plurality of temperature sample data of the corresponding component. For example: as shown in fig. 5c, the stator temperatures corresponding to 180, 181, 182.. 250MW loads are taken on the curve of the second regression model as stator temperature sample data. Further, a second 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 second arithmetic mean value of the stator.

It is understood that the calculation flow of the second arithmetic mean value of each component can be the same as the calculation flow of the stator component, and is not 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 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 weighted average according to the second arithmetic mean value of every part and corresponding weight value and calculate, obtains every hydroelectric set's temperature average value, for example: temperature average (second stator temperature average weight + rotor temperature average weight)/n.

S306: and determining the average value of the runout of the water-turbine generator set in a preset third load interval according to the runout data.

Wherein, the third load interval can be the load interval under hydroelectric set normal operating condition, and the third load interval is for example: and in the 180-250MW interval, namely, calculating the average value of the vibration data of each part when the water turbine generator set operates in the 180-250MW load interval to obtain the vibration average value.

In some embodiments, in the operation of determining the average value of the runout of the hydro-turbo generator set in the preset third load interval, the runout of each component and the corresponding load data may be used to establish a two-dimensional data distribution map (the same is the construction mode of the heat generation data and the guide vane opening data).

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 of each component and the corresponding load data, 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 similar to the first regression model and the second regression model, which is not described herein again.

Further, determining a value interval between a third load interval and the third load interval, for example: the third loading interval can be 180-250MW, and the value interval of the third loading interval can be 1 MW.

And further, sampling is carried out on the third regression model based on the third load interval and the value interval of the third load interval, and a plurality of runout sample data of the corresponding component are determined. For example: and (3) taking runout data corresponding to 180, 181, 182.. 250MW loads on a curve of a third 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 third arithmetic mean value of a plurality of runout sample data of 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 third calculation number mean value of the guide X-direction runout on the hydraulic generator.

It can 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 guide X direction on the hydraulic generator, and is not described herein again. Thus, a corresponding third arithmetic mean value may be determined for each component's vibration condition.

Further, a weighted average calculation is performed on a plurality of third calculation number average values corresponding to the plurality of components, and a runout average 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 third arithmetic number average value of every part and the weighted value that corresponds, obtains every hydroelectric set's runout average value.

S307: and determining a first running state of the plurality of water turbine generator sets according to the temperature average value, the runout average value and the corresponding first weight values.

For example, the temperature average value may be represented by JR, the runout average value may be represented by JZ, the temperature average value corresponds to a weight value of, for example, 0.3, and the runout average value corresponds to a weight value of, for example, 0.7, then the first operating state calculation formula of each hydro-turbo generator set may be represented as: 0.3JR +0.7 JZ.

S308: and determining a second starting sequence of the plurality of water turbine generator sets according to the first running states respectively corresponding to the plurality of water turbine generator sets under the steady-state working condition.

That is, the plurality of hydro-turbo generator sets are ordered according to the first operating state, and the resulting sequence may be referred to as a second start-up sequence, for example: the plurality of water turbine generator sets are sequenced from low to high according to the operation states 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 first 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.

S309: and determining first accumulated running time corresponding to the plurality of water turbine generator sets respectively under the steady-state working condition.

The first accumulated operation time may be an accumulated operation time under an annual steady-state condition, or may also be an accumulated operation time calculated from the time of installation, which is not limited herein.

S310: and determining a first target starting sequence according to the first starting sequence, the second starting sequence and the first accumulated running time.

In some embodiments, a first time difference value may be calculated for the longest accumulated run time unit and the shortest accumulated run time unit. In practical application, a plurality of hydroelectric generating sets: the first accumulated operating times corresponding to the unit 1, the unit 2, the unit 3, the unit 4, and the unit 5 may be represented by TL1, TL2, TL3, TL4, and TL5, respectively, so that the first unit with the longest accumulated operating time may be represented by TLmax ═ Max { TL1, TL2, TL3, TL4, and TL5}, and the first unit with the shortest accumulated operating time may be represented by TLmin ═ Min { TL1, TL2, TL3, TL4, and TL5}, and the first time difference is TLmax-TLmin. Further, the first time difference value is compared with a first threshold value, and whether the first time difference value is greater 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: if the first threshold is equal to 1000 hours, determining whether the first time difference is greater than or equal to the first threshold, that is: and judging whether the first time difference value is greater than or equal to 1000. If the first time difference is greater than or equal to the first threshold (1000 hours), the first longest accumulated running time unit in the first boot sequence is moved to the last boot position to obtain a fifth boot sequence, for example: the unit with the longest first accumulated operation time is the unit 2 (the first accumulated operation time is 1500 hours), the unit with the shortest first accumulated operation time is the unit 3 (the first accumulated operation time is 300 hours), and the first time difference value is larger than or equal to 1000. In this case, the first longest accumulated running time unit (i.e., unit 2) in the first boot order is moved to the last boot position, and the corresponding fifth boot order is: otherwise, the first boot sequence is taken as a fifth boot sequence, that is, the first boot sequence is taken as the fifth boot sequence if the first time difference value is not greater than or equal to the first threshold value. Further, a predetermined number of units with a low first operating state are determined according to the second boot sequence, for example: if the preset number is 2, two units with low first running state are selected according to the second starting sequence, namely: the unit 4 and the unit 1 move back the position of the unit with the low first running state in the fifth starting sequence, namely: in the fifth boot sequence, the positions of the unit 4 and the unit 1 are shifted backward (for example, shifted backward by one bit), and the first target boot sequence is obtained as follows: unit 3, unit 1, unit 5, unit 4, unit 2. Therefore, the first target starting sequence determined by the sequencing mode of the embodiment can select the most efficient and healthier unit to start preferentially, so that the equipment safety and the economic benefit of the hydropower station can be guaranteed at the same time.

In some embodiments, before determining the first target boot sequence according to the first 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), the unit can be removed from the first boot sequence and prompted; if the unit has B type defects (for example, general defects can work), the unit is moved to the last starting position. Therefore, the first target starting sequence determined by the embodiment can be combined with various factors such as the operating efficiency, the first operating state and the first accumulated operating time of the hydroelectric generating set when the hydroelectric generating set operates under the steady-state working condition, and therefore the equipment safety and the economic benefit of the hydropower station under the steady-state working condition can be guaranteed at the same time.

In some embodiments, the shutdown sequence of the multiple hydroelectric generating sets under the steady-state working condition can be further determined.

Specifically, first, a first target boot sequence is inverted to obtain a candidate shutdown sequence, and in combination with the first target boot sequence: unit 3, unit 1, unit 5, unit 4, unit 2, then the candidate shutdown order is: unit 2, unit 4, unit 5, unit 1, unit 3.

Further, determining respective corresponding continuous operation time of the plurality of hydroelectric generating sets under a steady-state working condition, wherein the continuous operation time is, for example, the operation time of the set from the last startup to the statistical time node, and the plurality of hydroelectric generating sets: the corresponding continuous operation times of the unit 1, the unit 2, the unit 3, the unit 4 and the unit 5 can be respectively represented by TC1, TC2, TC3, TC4 and TC 5.

Further, a second time difference value of the longest continuous operation time unit and the shortest continuous operation time unit is calculated, and whether the second time difference value is larger than or equal to a second threshold value is judged.

The longest sustained operation time unit may be represented as TCmax ═ Max { TC1, TC2, TC3, TC4, and TC5}, the shortest sustained operation time unit may be represented as TCmin ═ Min { TC1, TC2, TC3, TC4, and TC5}, and the second time difference is TCmax-TCmin. And further, comparing the second time difference value with a second threshold value, and judging whether the second time difference value is greater than or equal to the second threshold value. The second threshold may be flexibly determined according to an actual application scenario, for example: if the second threshold is 100 hours, determining whether the second time difference is greater than or equal to the second threshold, that is: and judging whether the second time difference value is equal to or larger than 100. If the second time difference is greater than or equal to the second threshold, moving the longest sustained operation time unit in the candidate shutdown sequence to the first shutdown position, and moving the shortest sustained operation time unit to the last shutdown position to obtain a target shutdown sequence, for example: if the longest unit with continuous operation time is the unit 4, and the shortest unit with continuous operation time is the unit 5, the unit 4 is moved to the first shutdown position in the candidate shutdown sequence, and 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 is smaller than the second threshold, otherwise, taking the candidate shutdown sequence as the target shutdown sequence. Therefore, the continuous operation time of the unit can be combined in the process of determining the shutdown sequence, so that the service life of the unit can be prolonged while economic benefit is guaranteed.

Fig. 6 is a schematic flow chart of a method for controlling the operation of the hydroelectric generating sets according to another embodiment of the present disclosure, and as shown in fig. 6, determining a second target startup sequence of the plurality of hydroelectric generating sets under an unsteady state condition includes:

s601: 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 number of the runner, the crack length of the runner and the number of unprocessed defects in the preset time of the plurality of water-turbine generator sets are respectively obtained, wherein the cavitation erosion number of the runner, the crack length of the runner and the number of unprocessed defects are data of the water-turbine generator sets under the unsteady working condition.

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.

S602: 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.

The unprocessed defects can be classified into A, B, C types of defects, and if a unit with the A type of defects exists, the unit is deleted in the 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 starting sequence; if there is a C-type defect, the number of C-type defects is used as the defect level.

S603: and determining the defect degrees respectively corresponding to the plurality of water-turbine generator sets according to the cavitation level, the crack level, the defect level and the second weighted values respectively corresponding to the defect levels.

The cavitation level, the crack level and the defect level can correspond to second 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 second weight values respectively in the process of determining the defect degree, and the obtained numerical value is used as the defect degree of each water-turbine generator set.

For example, the cavitation level may be represented by Zq, and the second weight value corresponding to the cavitation level is 0.2; the crack grade can be represented by Zl, and the second weight value corresponding to the crack grade is 0.4; the defect level may be represented by QX, and the second weighting value corresponding to the defect level is 0.4, so that the defect degree of each hydro-turbo generator set is Zq 0.2+ Zl 0.4+ QX 0.4.

S604: and determining a third opening and closing sequence of the plurality of water turbine generator sets according to the defect degrees corresponding to the plurality of water turbine generator sets under the unsteady state working condition.

That is to say, the multiple hydroelectric generating sets under the unsteady state working condition are sequenced according to the defect degree, and the obtained sequence can be called as a third starting sequence.

S605: and determining the fourth starting sequence of the plurality of water turbine generator sets according to the second running states respectively corresponding to the plurality of water turbine generator sets under the unsteady working condition.

The second operation state can be determined according to heating data and runout data of a plurality of components in a preset time of the plurality of water turbine generator sets under the unsteady state working condition, and further the plurality of water turbine generator sets are sequenced according to the second operation state to obtain a fourth generator sequence under the unsteady state working condition. The determination manner of the second operation state is the same as the determination manner of the first operation state, and is not described herein again.

S606: and determining second accumulated running time of the plurality of hydroelectric generating sets under the unsteady working condition.

The second accumulated operation time may be an accumulated operation time under an annual unsteady condition, for example: the running time deviating from the good working condition, such as the unit pressure regulation, the no-load running, the non-recommended interval running and the like, is not limited. That is, the operating time of each hydro-turbo unit deviating from the optimum operating condition every year is calculated separately.

S607: and determining a second target starting sequence according to the third starting sequence, the fourth starting sequence and the second accumulated running time.

In some embodiments, a time difference between the second longest cumulative operating time unit and the second shortest cumulative operating time unit may be calculated. In practical application, a plurality of hydroelectric generating sets: the second accumulated operating times corresponding to the unit 1, the unit 2, the unit 3, the unit 4, and the unit 5 may be represented by TL1, TL2, TL3, TL4, and TL5, respectively, so that the second unit with the longest accumulated operating time may be represented by TLmax ═ Max { TL1, TL2, TL3, TL4, and TL5}, and the second unit with the shortest accumulated operating time may be represented by TLmin ═ Min { TL1, TL2, TL3, TL4, and TL5}, and the time difference is TLmax-TLmin. And further, comparing the time difference value with a second threshold value, and judging whether the time difference value is greater than or equal to the second threshold value. The second threshold may be flexibly determined according to an actual application scenario, for example: if the second threshold is equal to 100 hours, determining whether the time difference is greater than or equal to the second threshold, that is: 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 second threshold (100 hours), moving the longest unit with the second accumulated running time in the third starting sequence to the last starting position to obtain the third starting sequence, for example: and if the unit with the longest second accumulated operation time is the unit 2 (the second accumulated operation time is 150 hours), and the unit with the shortest second accumulated operation time is the unit 3 (the second accumulated operation time is 30 hours), the time difference is ≧ 100. In this case, the unit with the longest accumulated operation time in the third starting sequence (i.e., the unit 2) is moved to the last starting position, and the corresponding sixth starting sequence is: the unit 1, the unit 3, the unit 4, the unit 5 and the unit 2, otherwise, the third starting sequence is used as the sixth starting sequence.

And further, determining a second target starting sequence of the plurality of water turbine generator sets under the unsteady state working condition according to the fourth starting sequence, the sixth starting sequence and the corresponding third weight values.

For example, the fourth starting sequence (the unit 4, the unit 1, the unit 2, the unit 3, and the unit 5) may be represented by Y, the sixth starting 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 fourth starting sequence Y is 0.3, and a third weight value of the third starting 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, so as to obtain a second target starting sequence. Thus, the second target boot sequence may have different emphasis points, such as: in the starting process, the defect degree or the running state can be strategically emphasized, so that the starting sequence of the second target can be flexibly determined according to different weight values.

Fig. 7 is a schematic view of a hydro-turbo generator set operation control device provided according to another embodiment of the present disclosure. As shown in fig. 7, the hydro-turbo set operation control device 70 includes:

the first determining module 701 is used for determining a first target starting sequence of the plurality of water turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which respectively correspond to the plurality of water turbine generator sets under the steady-state working condition;

the second determining module 702 is configured to determine a second target starting sequence of the multiple water turbine generator sets under the unsteady state condition according to the defect degrees, the second operating states, and the second accumulated operating time respectively corresponding to the multiple water turbine generator sets under the unsteady state condition;

a third determining module 703, configured to determine, according to a load distribution table that records multiple load distribution schemes of multiple hydro-generator sets, information of a target hydro-generator set that performs a power generation task, where the load distribution scheme is calculated by using an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions; and

and the control module 704 is used for controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

Alternatively, in some embodiments, fig. 8 is a schematic diagram of an operation control device of a hydro-turbo generator set according to another embodiment of the present disclosure, and as shown in fig. 8, the first determining module 701 includes: the first determining submodule 7011 is configured to determine a first starting sequence of the plurality of water turbine generator sets according to the operating efficiencies corresponding to the plurality of water turbine generator sets respectively under the steady-state operating condition; the second determining submodule 7012 is configured to determine a second starting sequence of the plurality of water turbine generator sets according to the first operating states corresponding to the plurality of water turbine generator sets respectively under the steady-state operating condition; the third determining submodule 7013 is configured to determine first accumulated operating times corresponding to the plurality of water turbine generator sets respectively under the steady-state operating condition; the fourth determining sub-module 7014 is configured to determine the first target boot sequence according to the first boot sequence, the second boot sequence, and the first accumulated running time.

Optionally, in some embodiments, as shown in fig. 8, the second determining module 702 includes: the fifth determining submodule 7021 is configured to determine a third starting sequence of the multiple water turbine generator sets according to the defect degrees corresponding to the multiple water turbine generator sets under the unsteady-state working condition; a sixth determining submodule 7022, configured to determine a fourth starting sequence of the multiple water turbine generator sets according to second operating states corresponding to the multiple water turbine generator sets respectively under the unsteady-state working condition; the seventh determining submodule 7023 is configured to determine second accumulated operating times of the plurality of water turbine generator sets under the unsteady-state working condition; and the eighth determining sub-module 7024 is configured to determine a second target boot sequence according to the third boot sequence, the fourth boot sequence, and the second accumulated running time.

Optionally, in some embodiments, as shown in fig. 8, the first determining module 701 further includes: an operating efficiency determination sub-module 7015 for: respectively acquiring guide vane opening data of a plurality of water turbine generator sets within preset time; and determining the guide vane opening average value of the water-turbine generator set in a preset first load interval according to the guide vane opening data, and taking the guide vane opening average value as the operating efficiency of the water-turbine generator set.

Optionally, in some embodiments, the operation efficiency determination sub-module 7015 is specifically configured to: constructing a first regression model for expressing the relation between the guide vane opening and the unit load according to the guide vane opening data 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 the first load interval and the value interval of the first load interval, and determining sample data of a plurality of guide vane opening degrees; and calculating a first arithmetic mean value of the plurality of guide vane opening sample data, and taking the first arithmetic mean value as the guide vane opening mean value.

Optionally, in some embodiments, as shown in fig. 8, the first determining module 701 further includes: an operation state determination sub-module 7016 for: respectively acquiring heating data and runout data of a plurality of components in a preset time of a plurality of water turbine generator sets; determining the temperature average value of the water-turbine generator set in a preset second load interval according to the heating data; determining the average value of the runout of the hydroelectric generating set in a preset third load interval according to the runout data; and determining a first running state of the plurality of water turbine generator sets according to the temperature average value, the runout average value and the corresponding first weight values.

Optionally, in some embodiments, the operation status determining sub-module 7016 is specifically configured to: constructing a second 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 second load interval and a value interval of the second load interval; sampling in a second 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 a plurality of temperature sample data for each component; and performing weighted average calculation on a plurality of second arithmetic mean values corresponding to the plurality of components to determine a temperature mean value.

Optionally, in some embodiments, the operation status determining sub-module 7016 is specifically configured to: constructing a third regression model for expressing 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 the value interval of the third load interval, and determining a plurality of runout sample data of each component; calculating a third arithmetic mean value of a plurality of runout sample data of each component; and performing weighted average calculation on a plurality of third calculation number average values corresponding to the plurality of components to determine a runout average value.

Optionally, in some embodiments, the fourth determining sub-module 7014 is specifically configured to: calculating a first time difference value of the longest unit with the first accumulated running time and the shortest unit with the first accumulated running time, and judging whether the first time difference value is greater than or equal to a first threshold value; if the first time difference value is larger than or equal to the first threshold value, moving the unit with the longest first accumulated running time in the first starting sequence to the last starting position to obtain a fifth starting sequence; otherwise, the first boot sequence is used as a fifth boot sequence; and determining a preset number of units with low first running states according to the second starting sequence, and moving back the positions of the units with low first running states in the fifth starting sequence to obtain a first target starting sequence.

Optionally, in some embodiments, as shown in fig. 8, the first determining module 701 further includes: shutdown sequence determining submodule 7017 is specifically configured to: negating the first target startup sequence to obtain a candidate shutdown sequence; determining the corresponding continuous operation time of the plurality of water turbine generator sets; calculating a second time difference value of the longest continuous operation time unit and the shortest continuous operation time unit, and judging whether the second time difference value is greater than or equal to a second threshold value; if the second time difference is larger than or equal to a second threshold value, moving the longest continuous operation time unit in the candidate shutdown sequence to the first shutdown position, and moving the shortest continuous operation time unit to the last shutdown position to obtain a target shutdown sequence; and if not, taking the candidate shutdown sequence as a target shutdown sequence.

Optionally, in some embodiments, as shown in fig. 8, the second determining module 702 further includes: the defect level determination sub-module 7025 is specifically configured to: 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 determining the defect degrees respectively corresponding to the plurality of water-turbine generator sets according to the cavitation level, the crack level, the defect level and the second weighted values respectively corresponding to the defect levels.

Optionally, in some embodiments, the eighth determining sub-module 7024 is specifically configured to: calculating a time difference value between the longest unit with the second accumulated running time and the shortest unit with the second accumulated running time, and judging whether the time difference value is greater than or equal to a second threshold value; if the time difference is larger than or equal to a second threshold value, moving the longest unit with the second accumulated running time in the third starting sequence to the last starting position to obtain a sixth starting sequence; otherwise, taking the third starting sequence as a sixth starting sequence; and determining a second target starting sequence according to the fourth starting sequence, the sixth starting sequence and the corresponding third weight values.

Optionally, in some embodiments, the minimum water consumption model is expressed as:

wherein W is the total water consumption of the hydropower station,

The current generation flow rate; Δ T represents a period duration;

Runtime

Q_up，i，Q_dn，iRespectively representing the water consumption in the starting and stopping processes, wherein N is the number of hydropower station units; t is the number of the scheduling period time.

Optionally, in some embodiments, the optimization algorithm is a dynamic programming algorithm, and the calculation process is as follows: taking k as 1,2. n as a calculation stage number, and calculating the corresponding optimal flow of the power station by stage by recursion according to the sequence of the number of the water-turbine generator sets and the load of the hydropower station from small to large, wherein the recursion calculation formula is as follows:

wherein the content of the first and second substances,

the total load of the units from 1 to k in the k stage is shown,

represents a total load of

indicating a boundary condition, and the initial value is 0.

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 achieve the above embodiments, the present application also provides a computer program product, which when executed by an instruction processor in the computer program product, executes the method for controlling the operation of the water turbine generator set according to the foregoing embodiments of the present application.

FIG. 9 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. 9 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present application.

As shown in FIG. 9, 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.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. These architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus, to name a few.

Computer device 12 typically includes a variety of computer system readable media. Such media may 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 (RAM) 30 and/or cache Memory 32. 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 and write to non-removable, nonvolatile magnetic media (not shown in FIG. 9, and commonly referred to as a "hard drive").

Although not shown in FIG. 9, 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.

Computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with computer device 12, and/or with any devices (e.g., network card, modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Moreover, computer device 12 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network such as the Internet) via Network adapter 20. As shown, network adapter 20 communicates with the other modules of computer device 12 via bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processing unit 16 executes various functional applications and the operation of the hydro-turbo set by executing a program stored in the system memory 28, for example, to implement the hydro-turbo set operation control 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 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

1. A method for controlling the operation of a hydroelectric generating set is characterized by comprising the following steps:

determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which are respectively corresponding to the plurality of water-turbine generator sets under the steady-state working condition;

determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the defect degrees, the second running state and the second accumulated running time which are respectively corresponding to the plurality of water-turbine generator sets under the unsteady state working condition;

determining target hydroelectric generating set information for executing a power generation task according to a load distribution table for recording various load distribution schemes of a plurality of hydroelectric generating sets, wherein the load distribution scheme is calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions; and

and controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

2. The method of claim 1, wherein determining a first target startup sequence of the plurality of hydro-generator sets under the steady-state operating condition according to the operating efficiencies, the first operating state, and the first accumulated operating time respectively corresponding to the plurality of hydro-generator sets under the steady-state operating condition comprises:

determining a first starting sequence of the plurality of water-turbine generator sets according to the operating efficiency corresponding to the plurality of water-turbine generator sets under the steady-state working condition;

determining a second starting sequence of the plurality of water-turbine generator sets according to first operation states respectively corresponding to the plurality of water-turbine generator sets under a steady-state working condition;

determining first accumulated running time respectively corresponding to the plurality of water turbine generator sets under a steady-state working condition;

and determining the first target starting sequence according to the first starting sequence, the second starting sequence and the first accumulated running time.

3. The method according to claim 1, wherein determining a second target startup sequence of the plurality of water turbine generator sets under the unsteady state condition according to the defect degrees, the second operation state and the second accumulated operation time respectively corresponding to the plurality of water turbine generator sets under the unsteady state condition comprises:

determining a third opening sequence of the plurality of water turbine generator sets according to the defect degrees respectively corresponding to the plurality of water turbine generator sets under the unsteady state working condition;

determining a fourth starting sequence of the plurality of water turbine generator sets according to second operation states respectively corresponding to the plurality of water turbine generator sets under the unsteady state working condition;

determining second accumulated running time of the plurality of water turbine generator sets under the unsteady-state working condition;

and determining the second target starting sequence according to the third starting sequence, the fourth starting sequence and the second accumulated running time.

4. The method of claim 2, wherein prior to determining a first startup sequence of the plurality of hydro-generator sets based on respective operating efficiencies of the plurality of hydro-generator sets under steady state operating conditions, further comprising:

respectively acquiring guide vane opening data of the plurality of water turbine generator sets within preset time; and

and determining the guide vane opening average value of the water-turbine generator set in a preset first load interval according to the guide vane opening data, and taking the guide vane opening average value as the operating efficiency of the water-turbine generator set.

5. The method of claim 4, wherein determining an average value of the guide vane opening of the hydro-turbo generator set in a preset first load interval according to the guide vane opening data comprises:

constructing a first regression model for representing the relation between the guide vane opening and the unit load according to the guide vane opening data and the corresponding load data;

determining the first load interval and 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 sample data of a plurality of guide vane opening degrees; and

and calculating a first arithmetic mean value of the plurality of guide vane opening sample data, and taking the first arithmetic mean value as the guide vane opening mean value.

6. The method of claim 2, wherein prior to determining a second turn-on sequence for the plurality of hydro-generator sets based on the respective corresponding first operating conditions of the plurality of hydro-generator sets under steady state conditions, 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;

determining the temperature average value of the water-turbine generator set in a preset second load interval according to the heating data;

determining the average value of the runout of the hydroelectric generating set in a preset third load interval according to the runout data; and

and determining a first running state of the plurality of water-turbine generator sets according to the temperature average value, the runout average value and the corresponding first weight values.

7. The method of claim 6, wherein determining the average temperature of the hydro-turbo generator set over a preset second load interval based on the thermal data comprises:

constructing a second 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 second load interval and the value interval of the second load interval;

sampling in the two regression models 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 a plurality of temperature sample data for each component;

and carrying out weighted average calculation on a plurality of second arithmetic mean values corresponding to the plurality of components, and determining the temperature mean value.

8. The method of claim 6, wherein determining an average value of the runout of the hydroelectric generating set over a predetermined third load interval based on the runout data comprises:

constructing a third regression model for expressing 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 third load interval and 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 value of a plurality of runout sample data of each component;

and carrying out weighted average calculation on a plurality of third calculation average values corresponding to the plurality of components to determine the runout average value.

9. The method of claim 2, wherein determining the first target boot order based on the first boot order, the second boot order, and the first accumulated runtime comprises:

calculating a first time difference value of the longest unit with the first accumulated running time and the shortest unit with the first accumulated running time, and judging whether the first time difference value is greater than or equal to a first threshold value;

if the first time difference value is greater than or equal to the first threshold value, moving the first longest accumulated running time unit in the first starting sequence to the last starting position to obtain a fifth starting sequence; otherwise, the first starting sequence is used as the fifth starting sequence;

and determining a preset number of units with low first running state according to the second starting sequence, and moving back the position of the unit with low first running state in the fifth starting sequence to obtain the first target starting sequence.

10. The method of claim 2, further comprising:

negating the first target starting sequence to obtain a candidate shutdown sequence;

determining the continuous operation time corresponding to the plurality of water turbine generator sets respectively;

calculating a second time difference value of the longest continuous operation time unit and the shortest continuous operation time unit, and judging whether the second time difference value is greater than or equal to a second threshold value;

if the second time difference is greater than or equal to the second threshold, moving the longest sustained operation time unit in the candidate shutdown sequence to the first shutdown position, and moving the shortest sustained operation time unit to the last shutdown position to obtain a target shutdown sequence; and if not, taking the candidate shutdown sequence as the target shutdown sequence.

11. The method according to claim 3, wherein before determining the third starting sequence of the plurality of hydro-generator sets according to the defect degrees corresponding to the plurality of hydro-generator sets under the unsteady state condition, the method further comprises:

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 defect degrees respectively corresponding to the plurality of water-turbine generator sets according to the cavitation level, the crack level, the defect level and the second weighted values respectively corresponding to the defect levels.

12. The method of claim 3, wherein determining the second target boot order based on the third opening order, the fourth opening order, and the second accumulated runtime comprises:

calculating a time difference value of the longest unit with the second accumulated running time and the shortest unit with the second accumulated running time, and judging whether the time difference value is greater than or equal to a second threshold value;

if the time difference is greater than or equal to the second threshold, moving the longest second accumulated running time unit in the third starting sequence to the last starting position to obtain a sixth starting sequence; otherwise, taking the third starting sequence as the sixth starting sequence;

and determining the second target starting sequence according to the fourth starting sequence, the sixth starting sequence and the corresponding third weight values.

13. The method of claim 1, wherein the minimum water consumption model is represented as:

wherein W is the total water consumption of the hydropower station,

The current generation flow rate; Δ T represents a period duration;

Runtime

14. The method of claim 1, wherein the optimization algorithm is a dynamic programming algorithm, and the calculation process is as follows:

wherein the content of the first and second substances,

the total load of the units from 1 to k in the k stage is shown,

represents a total load of

indicating a boundary condition, and the initial value is 0.

15. The method of any of claims 6-8, 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.

16. A hydroelectric generating set operation control device, characterized by comprising:

the first determining module is used for determining a first target starting sequence of the plurality of water-turbine generator sets under the steady-state working condition according to the operating efficiency, the first operating state and the first accumulated operating time which respectively correspond to the plurality of water-turbine generator sets under the steady-state working condition;

the second determining module is used for determining a second target starting sequence of the plurality of water-turbine generator sets under the unsteady state working condition according to the defect degrees, the second running states and the second accumulated running time which correspond to the plurality of water-turbine generator sets under the unsteady state working condition respectively;

the third determining module is used for determining target hydroelectric generating set information for executing a power generation task according to a load distribution table for recording various load distribution schemes of the plurality of hydroelectric generating sets, wherein the load distribution schemes are calculated by adopting an optimization algorithm based on a minimum water consumption model and hydropower station constraint conditions; and

and the control module is used for controlling the plurality of water-turbine generator sets to operate according to the first target starting sequence, the second target starting sequence and the target water-turbine generator set information.

17. The apparatus of claim 16, wherein the first determining module comprises:

the first determining submodule is used for determining a first starting sequence of the plurality of water-turbine generator sets according to the operating efficiencies corresponding to the plurality of water-turbine generator sets under the steady-state working condition;

the second determining submodule is used for determining a second starting sequence of the plurality of water-turbine generator sets according to the first operating states respectively corresponding to the plurality of water-turbine generator sets under the steady-state working condition;

the third determining submodule is used for determining first accumulated running time corresponding to the plurality of water-turbine generator sets under the steady-state working condition;

and the fourth determining submodule is used for determining the first target starting sequence according to the first starting sequence, the second starting sequence and the first accumulated running time.

18. The apparatus of claim 16, wherein the second determining module comprises:

the fifth determining submodule is used for determining a third opening sequence of the plurality of water-turbine generator sets according to the defect degrees respectively corresponding to the plurality of water-turbine generator sets under the unsteady state working condition;

the sixth determining submodule is used for determining a fourth starting sequence of the plurality of water-turbine generator sets according to second running states corresponding to the plurality of water-turbine generator sets under the unsteady state working condition;

the seventh determining submodule is used for determining second accumulated running time of the plurality of water turbine generator sets under the unsteady working condition;

and the eighth determining submodule is used for determining the second target starting sequence according to the third starting sequence, the fourth starting sequence and the second accumulated running time.

19. The apparatus of claim 17, wherein the first determining module further comprises: an operational efficiency determination submodule for:

20. The apparatus of claim 19, wherein the operational efficiency determination submodule is specifically configured to:

21. The apparatus of claim 17, wherein the first determining module further comprises: an operation state determination submodule for:

22. The apparatus of claim 21, wherein the operational status determination submodule is specifically configured to:

23. The apparatus of claim 21, wherein the operational status determination submodule is specifically configured to:

24. The apparatus of claim 17, wherein the fourth determination submodule is specifically configured to:

25. The apparatus of claim 17, wherein the first determining module further comprises: a shutdown sequence determination submodule, specifically configured to:

26. The apparatus of claim 18, wherein the second determining module further comprises: a defect level determination submodule, specifically configured to:

27. The apparatus of claim 18, wherein the eighth determination submodule is specifically configured to:

28. The apparatus of claim 16, wherein the minimum water consumption model is expressed as:

wherein W is the total water consumption of the hydropower station,

The current generation flow rate; Δ T represents a period duration;

Runtime

29. The apparatus of claim 16, wherein the optimization algorithm is a dynamic programming algorithm, and the calculation process is as follows:

wherein the content of the first and second substances,

the total load of the units from 1 to k in the k stage is shown,

represents a total load of

indicating a boundary condition, and the initial value is 0.

30. 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 1-15.