Regulation and storage zone pump station scale optimization method, system and equipment based on uncertainty coverage degree and medium

Abstract

The invention discloses a regulation and storage zone pump station scale optimization method, system and device based on uncertainty coverage, and a medium. The method comprises the following steps: generating multiple groups of annual hourly rainfall scenes; dividing the water-saving annual irrigation quotas at equal intervals to obtain multi-stage water-saving annual irrigation quotas; the rainfall scene and the multi-stage water-saving annual irrigation quota are combined to form a combined scene; constructing a candidate pump station scale set; simulating each combined scene and each candidate pump station scale to obtain the overflow volume of the regulation and storage belt; calculating an initial uncertainty coverage degree under each joint scene and each candidate pump station scale; a first coverage robust curve is formed based on the initial uncertainty coverage, a first-layer inflection point of the pump station scale is identified and obtained, and an uncertainty interval is constructed; and the final uncertainty coverage is calculated in the uncertainty interval, a second coverage robust curve is formed, and the optimal pump station scale is obtained after identification. According to the method, scientificity, practicability and robustness of pump station scale selection are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pump station optimization, and in particular to a scale optimization method, system, device and medium for a pump station in a regulation and storage zone based on uncertainty coverage. BACKGROUND

[0002] In the engineering practice of pumping water by a pump station to relieve overflow in a regulation and storage zone and reduce the risk of environmental pollution, it is difficult to achieve a coordinated optimization between environmental benefits and economic benefits and determine the optimal pump station scale due to meteorological uncertainty. The existing methods for determining the pump station scale still have obvious shortcomings in concept and tools, which restrict the practical value and popularization and application. The specific defects are as follows: (1) The method of “design storm” is used instead of multi-year continuous process, so that the time sequence and intra-year cumulative effect are ignored. At present, the capacity and ability are often determined by using a single storm or a few typical storms, combining with IDF curve, Richardson method or rational formula. This method cannot reflect the coupling influence between multi-peak rainfall, soil moisture memory effect, previous conditions and seasonal water demand, and is prone to cause conservative or mismatched scheme; (2) The rainfall input and model uncertainty are not handled well, and the determination of pump station scale is prone to be biased The existing method often attributes the error to the model parameters, ignoring the rainfall estimation error which is the source of runoff uncertainty; thus, the input uncertainty and model structure / parameter uncertainty cannot be quantified, and the optimal pump station scale obtained will be highly sensitive to the scenario selection, and the stability is poor; (3) Irrigation water uncertainty is roughly described Different irrigation quotas are not fully reflected, which leads to distorted supply-demand matching and affects the judgment of the required pumping capacity; (4) More attention is paid to operation than planning, and there is a lack of robust selection method for scale determination The existing technology focuses on the pump station scheduling and energy consumption control of the existing pump station scale, and lacks a scientific decision-making method for determining the optimal pump station scale in the early stage of the project (new construction / expansion). Therefore, when the strategy decision-making is upgraded from “operation optimization” to “scale selection”, there is a lack of robust criteria and evidence chain that can be directly used.

[0003] Therefore, it is urgent to solve the above problems. SUMMARY

[0004] The first object of the present application is to provide a scale optimization method for a pump station in a regulation and storage zone based on uncertainty coverage, which improves the scientificity, practicality and robustness of pump station scale selection.

[0005] The second object of the present application is to provide a scale optimization system for a pump station in a regulation and storage zone based on uncertainty coverage.

[0006] A third object of the present application is to provide an electronic device.

[0007] A fourth object of the present application is to provide a computer-readable storage medium.

[0008] Technical scheme: To achieve the above object, the application discloses a regulating and storage belt pump station scale optimization method based on uncertainty coverage, which comprises the following steps: (1) Collect historical hourly rainfall data of multiple rainfall stations in the upstream water area of the target pump station, expand and generate yearly hourly rainfall scenarios, input each rainfall scenario into a calibrated watershed hydrological model, calculate and output the hourly time series of the upstream boundary flow of the regulating and storage belt, and calculate the hourly time series of the upstream boundary flow of the regulating and storage belt. (2) According to the minimum and maximum values of the water-saving annual irrigation quota, the water-saving annual irrigation quota is equally divided into levels, and the water-saving annual irrigation quota of each level is obtained; then the hourly scale regulating and storage belt upstream irrigation water demand under each rainfall scenario and each water-saving annual irrigation quota is calculated. (3) Any one rainfall scenario and any one water-saving annual irrigation quota are combined to form a joint scenario , and an uncertainty scenario set is formed, wherein the total number of joint scenarios is , ; (4) Set the optimization interval of the pump station scale, equally divide the optimization interval into K parts to obtain a candidate pump station scale set , and each candidate pump station scale , ; (5) According to the hourly time series of the upstream boundary flow of the regulating and storage belt and the hourly scale regulating and storage belt upstream irrigation water demand, the annual hourly regulating and storage belt water conservation continuous simulation is carried out for each joint scenario and each candidate pump station scale , and the annual hourly regulating and storage belt overflow volume is obtained. (6) According to the annual hourly regulating and storage belt overflow volume, the annual scale overflow water volume percentage and the initial uncertainty coverage under each joint scenario and each candidate pump station scale are calculated, and the initial uncertainty coverage refers to the proportion of scenarios that meet the condition of "annual overflow percentage not exceeding the target threshold percentage" in all joint scenarios under the candidate pump station scale . (7) Based on all candidate pump station scales and corresponding initial uncertainty coverage degrees, a relationship diagram of pump station scale and initial uncertainty coverage degree is drawn to form a first coverage degree robust curve, a first layer inflection point of pump station scale is obtained after identifying the inflection point, and an uncertainty interval for pump station scale optimization is constructed; (8) The final uncertainty coverage degree is calculated in the uncertainty interval to form a second coverage degree robust curve, a second layer inflection point is obtained after identifying the inflection point, and the second layer inflection point is the optimal pump station scale.

[0009] Optionally, the step (1) comprises the following specific steps: The historical hourly rainfall data of a plurality of rainfall stations in the upstream water area of the target pump station is collected, and the duration is years, 2-3 years, and the time step is ; using the collected historical rainfall data as a basis, a rainfall generation model is used to generate a total of 10 sets of annual hourly rainfall scenarios , and the data is at least expanded by 10 times, i.e. ; each set of rainfall scenarios is input into the calibrated watershed hydrological model, and the hourly time series of the upstream water boundary flow of the regulation and storage belt is calculated and output , unit m 3 / h, , which represents the hourly sequence; the annual hourly water inflow data under each set of rainfall scenarios is recorded, and a time sequence diagram of the water inflow data can be drawn; The expression of the hourly time series of the upstream water boundary flow of the regulation and storage belt is: , wherein is a parameter of the watershed hydrological model, is a calculation process of the watershed hydrological model, and the watershed hydrological model is an LSPC model.

[0010] Optionally, the step (2) comprises the following specific steps: The minimum value and the maximum value of the water-saving annual irrigation quota are set, and the minimum value to the maximum value is equally divided into grades, , and the calculation formula of the water-saving annual irrigation quota of the grade is: , The unit of is​; Each rainfall scenario was obtained through simulation calculations using the LSPC model. Hourly irrigation water requirements Based on hourly irrigation water demand Calculate rainfall scenarios At any moment Hourly scale irrigation water demand weight The calculation formula is: , in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is ; Set the area of ​​farmland upstream of the water storage belt that needs irrigation If the unit is mu (a Chinese unit of area), then each rainfall scenario... and the Hourly scale upstream irrigation water demand of water storage zone under the annual water-saving quota The calculation formula is: , in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

[0011] Optionally, the specific steps for the continuous calculation of water conservation in the storage zone on an hourly basis throughout the year in step (5) include: At every moment The decision to activate the pumping station is based on the current water level and the water demand. The station is activated if irrigation water demand is insufficient, pumping water until the demand is met or the rated capacity is reached; otherwise, it is shut down. Under the premise of no minimum start-stop constraints and no energy consumption limitations, the pumping station operates at any given time. Pumping capacity of the pumping station The calculation formula is: , in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation; Storage belt Real-time water volume, in m³; For joint scenarios Hourly irrigation water requirements ; The overflow volume and water balance of the storage tank are calculated. First, the theoretical storage volume is calculated without considering the overflow. The calculation formula is as follows: , , is the storage belt without considering overflow is the water storage at time t is the storage belt is the water storage at time t is the joint scenario is the upstream inflow at time t, in m3 / h 3 , ; is the pump station hourly pumping volume, in m3 / h If exceeds the fixed storage capacity of the storage belt , overflow occurs, otherwise no overflow, the calculation formula of the overflow volume of the storage belt is , , , The unit of is m3 / h The unit of is m3 Update the water storage of the storage belt at time t , the calculation formula is .

[0012] Optionally, the step (6) comprises the following specific steps: According to the annual hourly overflow volume of the storage belt , calculate the cumulative annual overflow and inflow volume under each joint scenario and each candidate pump station scale , calculate the annual scale overflow water percentage , in %, the calculation formula of the annual scale overflow water percentage is , Set the annual scale overflow water target threshold percentage , in %; Under each candidate pump station scale , first construct the indicator function , the indicator function indicates whether the joint scenario meets the standard condition under the pump station scale , 1 if it meets the standard condition, otherwise 0; the expression of the indicator function is , Calculate the initial uncertainty coverage , in %, the initial uncertainty coverage The calculation formula is: .

[0013] Optionally, the step (7) comprises the following specific steps: Set the pump station scale And the initial uncertainty coverage The data points on the relationship diagram are Smoothed by the moving average method to form the first coverage robust curve, and the calculation formula is: , Wherein, Is half the width of the sliding window, and is an integer selected empirically, and the window size is , The smoothed first coverage robust curve is The first-order difference And the second-order difference Of the smoothed first coverage robust curve are calculated, and the calculation formula of the first-order difference Is: , The calculation formula of the second-order difference Is: , The first layer inflection point of the first coverage robust curve is defined as the position where the coverage improvement speed obviously decreases, that is, an inflection point appears when the second-order difference changes from positive to negative, that is, when The extreme point of the jump from positive to negative, the extreme point That meets the condition is the first layer inflection point , Specifically, the condition is: , Wherein Is a threshold empirical parameter considered to be set, Indicates that it meets the condition at the same time; According to the identified first layer inflection point , the uncertainty interval of pump station scale optimization is constructed, and the expression of the uncertainty interval is: , Wherein Is the lower limit of the uncertainty interval of the pump station scale optimization based on the first layer inflection point, Is the upper limit of the uncertainty interval of the pump station scale optimization based on the first layer inflection point; And Are empirical optimization coefficients, wherein , .

[0014] Optionally, step (8) includes the following specific steps: Uncertainty range for pump station size optimization based on the first inflection point Inside, there is a total of Candidate size , The smoothed initial uncertainty coverage for each candidate size is known to be... The initial uncertainty coverage after smoothing within the uncertainty interval As sample points, according to candidate size Sort the samples from smallest to largest to form an ordered set. : , For the sample set The empirical cumulative distribution function of the coverage is denoted as the final uncertainty coverage. ,in At any sample point The function value is defined as the value of a sample that is less than or equal to 0. The sum of the initial uncertainty coverage of the sample points, and the final uncertainty coverage. The calculation formula is: , Final Uncertainty Coverage A second coverage robustness curve is generated, and inflection points are identified on the second coverage robustness curve to obtain the second layer inflection points. The calculation formula is: , The final uncertainty coverage of the pump station size The first derivative, The final uncertainty coverage of the pump station size The second derivative, The curvature of the second coverage robust curve is the point where the maximum curvature indicates the most significant point where the growth rate slows down. The marginal increment of the uncertain coverage shows a decreasing trend, and the marginal increment is the differential gain of the scale of adjacent pumping stations; The size of the pumping station to maximize the objective function ; As the determination condition, where This means simultaneously satisfying, This refers to the marginal increment or discrete difference of the uncertainty coverage with respect to the pump station size. If the pump station size level is... , This refers to the total number of pump station sizes within the uncertainty interval of pump station size optimization. Then: , This indicates that the scale of the pumping station has been increased from... Increase to How much has the coverage improved? It indicates a monotonically decreasing or diminishing trend.

[0015] Based on the same inventive concept, this invention discloses a system for optimizing the scale of water storage and regulation pumping stations based on uncertainty coverage, comprising: The upstream inflow calculation module is used to collect historical hourly rainfall data from multiple rain gauge stations in the upstream inflow area of ​​the target pumping station, and expand the generation... The system generates hourly rainfall scenarios throughout the year. Each rainfall scenario is input into a calibrated watershed hydrological model to calculate and output hourly time series of inflow boundary flow upstream of the storage zone. The upstream irrigation water demand calculation module is used to divide the annual water-saving irrigation quota into equal intervals based on the minimum and maximum values ​​of the annual water-saving irrigation quota. The water-saving annual irrigation quota for each level is obtained; then the hourly-scale irrigation demand of the upstream of the storage zone is calculated for each rainfall scenario and each level of the water-saving annual irrigation quota. The uncertainty scenario set module is used to combine any set of rainfall scenarios and any level of annual water-saving irrigation quota to form a joint scenario. These together form a set of uncertainty scenarios, where the total number of joint scenarios is... , ; The candidate pump station size set module is used to define the optimization interval for pump station size, divide the optimization interval into K equal parts, and obtain the candidate pump station size set. Size of each candidate pumping station , ; The water conservation continuous simulation module is used to perform simulations for each joint scenario based on the hourly time series of the inflow boundary flow upstream of the storage zone and the hourly-scale irrigation water demand upstream of the storage zone. and the size of each candidate pumping station A continuous simulation of the water volume conservation of the storage zone was conducted hourly throughout the year to obtain the pumping volume of the pumping station, the overflow volume of the storage zone, and the water storage volume of the storage zone hourly throughout the year. The initial uncertainty coverage calculation module calculates each joint scenario based on the hourly overflow volume of the storage zone throughout the year. and the size of each candidate pumping station The cumulative annual overflow and inflow are used to calculate the annual-scale overflow percentage and initial uncertainty coverage. The initial uncertainty coverage refers to the coverage at the candidate pumping station scale. all joint scenarios the proportion of scenarios that satisfy "annual overflow percentage does not exceed target threshold percentage"; The first layer of inflection point identification module is used for drawing a relationship diagram of pump station scale and initial uncertainty coverage degree based on all candidate pump station scales and corresponding initial uncertainty coverage degrees, forming a first coverage degree robust curve, identifying an inflection point of the first layer of pump station scale, and constructing an uncertainty interval of pump station scale optimization. The second layer of inflection point identification module is used for calculating a final uncertainty coverage degree in the uncertainty interval, forming a second coverage degree robust curve, identifying a second layer of inflection point, and obtaining the optimal pump station scale.

[0016] Based on the same inventive concept, the present application discloses an electronic device, comprising one or more processors, one or more memories, and one or more programs stored in the memories and configured to be executed by the processors, and the programs loaded into the processors realize the steps of the uncertainty coverage-based optimization method for the scale of the pump station in the regulation and storage zone as described above.

[0017] Based on the same inventive concept, the present application discloses a computer readable storage medium, which stores a computer program, and the computer program comprises program instructions, and the program instructions make the processor execute the steps of the uncertainty coverage-based optimization method for the scale of the pump station in the regulation and storage zone when executed by the processor.

[0018] Advantages: Compared with the prior art, the present application has the following remarkable advantages: (1) The present application overcomes the problems of the prior art in determining the scale of the pump station in the regulation and storage zone, such as "replacing continuous process with design storm, insufficient description of uncertainty, and lack of coverage degree and robust selection, and improves the scientificity, practicality and robustness of the selection of the scale of the pump station; (2) The present application constructs an integrated logic chain of annual scale and hourly step of "rainfall scenario- watershed hydrological model-regulation and storage zone-pump station linkage", and adopts a unified pump station starting logic of "pumping when there is water and water demand, and pumping not exceeding the scale of the pump station", which comprehensively represents the coupling effect of multi-peak rainfall, early bottom water and seasonal water demand, and provides interpretable whole-process evidence for the selection of the scale of the pump station; (3) The present application constructs a multi-rainfall scenario library in view of meteorological uncertainty and water demand difference, forms a multi-level water demand time sequence based on LSPC, forms a million-level joint scenario in combination with different pump station scales, measures the reliability of the optimization result by uncertainty coverage degree, and improves the robustness and reproducibility of the conclusion; (4) The present application introduces water demand uncertainty based on LSPC, constructs water demand uncertainty based on LSPC model in interval equidistance grading, combines with hourly water demand sequence output by the model, finely expresses structural differences of different quotas and water demand time sequence, corrects supply-demand mismatch, thereby accurately defines required pumping capacity and supports scale determination; (5) The present application proposes an integrated selection framework of "pumping station scale-uncertainty coverage-inflexion point", identifies a first layer inflection point on a "overflow percentage-pumping station scale" robust curve, and identifies a second layer inflection point on an "uncertainty coverage-pumping station scale" robust curve; gives a minimum pumping station scale meeting target coverage within budget and technical boundaries, realizes collaborative optimization of overflow reduction / environmental benefit and investment utilization / economic benefit, and improves scientificity, practicality and generalizability of the scheme. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a flowchart of the present application; Figure 2 is a system framework diagram of the present application; Figure 3 is a time sequence diagram of inflow data in the present application; Figure 4 is a time sequence diagram of hourly pumping amount of the pumping station in the present application; Figure 5 is a time sequence diagram of overflow of the regulation and storage belt in the present application; Figure 6 is a time sequence diagram of storage water amount of the regulation and storage belt in the present application; Figure 7 is a first coverage robust curve diagram in the present application; Figure 8 is a second coverage robust curve diagram in the present application. DETAILED DESCRIPTION

[0020] In order to make the objectives, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and should not be used to limit the present application.

[0021] It should be understood that the present application can be implemented in different forms, and should not be interpreted as being limited to the embodiments presented herein. On the contrary, these embodiments are provided to make the disclosure complete and complete, and to fully convey the scope of the present application to those skilled in the art. In the drawings, the sizes and relative sizes of the components may be exaggerated for clarity. The same reference signs represent the same components throughout.

[0022] Embodiment 1: as Figure 1As shown, the application discloses a regulating and storing belt pump station scale optimization method based on uncertainty coverage, and comprises the following steps: (1) collect historical hourly rainfall data of multiple rainfall stations in the upstream water area of the target pump station, expand to generate a group of annual hourly rainfall scenarios, input each rainfall scenario into the calibrated watershed hydrological model, calculate and output the hourly time series of the upstream water boundary flow of the regulating and storing belt.

[0023] Step (1) comprises the following specific steps: Collect historical hourly rainfall data of multiple rainfall stations in the upstream water area of the target pump station, the duration is 2-3 years, the time step is 1 hour; using the collected historical rainfall data as the basis, a rainfall generation model is used to generate a group of annual hourly rainfall scenarios , the data is at least expanded by 10 times, that is ; input each rainfall scenario into the calibrated watershed hydrological model, calculate and output the hourly time series of the upstream water boundary flow of the regulating and storing belt , unit m 3 / h, , represents the hour sequence, ; record the annual 8760-hour water inflow data under each rainfall scenario, and draw a time sequence graph of the water inflow data; The expression of the hourly time series of the upstream water boundary flow of the regulating and storing belt is: , , wherein is the parameter of the watershed hydrological model, is the calculation process of the watershed hydrological model, and the watershed hydrological model is an LSPC model.

[0024] (2) according to the minimum and maximum values of the water-saving annual irrigation quota, equally divide the water-saving annual irrigation quota into levels, to obtain the water-saving annual irrigation quota of each level; then calculate the hourly scale irrigation water demand of the upstream of the regulating and storing belt under each rainfall scenario and each water-saving annual irrigation quota.

[0025] Step (2) comprises the following specific steps: Set the minimum value and the maximum value of the water-saving annual irrigation quota, the minimum value is 218 , and the maximum value is 450 , and the minimum value​ To the maximum value The gradations are equidistant from each other. class, , Then the first Grade A water-saving annual irrigation quota The calculation formula is: , The unit is .

[0026] Each rainfall scenario was obtained through simulation calculations using the LSPC model. Hourly irrigation water requirements Based on hourly irrigation water demand Calculate rainfall scenarios At any moment Hourly scale irrigation water demand weight The calculation formula is: , in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is .

[0027] Set the area of ​​farmland upstream of the water storage belt that needs irrigation If the unit is mu (a Chinese unit of area), then each rainfall scenario... and the Hourly scale upstream irrigation water demand of water storage zone under the annual water-saving quota The calculation formula is: , in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

[0028] (3) Combine any set of rainfall scenarios and any level of water-saving annual irrigation quota to form a joint scenario. All possible combinations are grouped into an uncertainty scenario set, and the total number of joint scenarios in the uncertainty simulation set is... , Each joint scenario , correspond Group rainfall scenarios, correspond Grade A water-saving annual irrigation quota.

[0029] (4) According to the engineering investment and operation requirements, the upper limit and lower limit of the pump station scale to be optimized are determined, and the optimization interval of the pump station scale is obtained , the pump station scale refers to the rated pumping and drainage flow of the pump station under the design working condition, the pump station scale is expressed in hourly scale, and the unit is ; the design working condition refers to the design head, design speed, and rated unit configuration and parallel system mode; the optimization interval of the pump station scale is equally divided into K parts, K = 10-50, the optimization step is calculated, and the calculation formula of the optimization step is: , The candidate pump station scale set is obtained , The candidate pump station scale Each is a candidate scale.

[0030] (5) According to the hourly time series of the upstream boundary flow of the regulation and storage zone and the hourly scale of the irrigation water demand of the regulation and storage zone, the hourly water conservation continuous simulation of the regulation and storage zone is carried out for each joint scenario and each candidate pump station scale , and the hourly pumping amount of the pump station, the overflow amount of the regulation and storage zone, and the storage amount of the regulation and storage zone in a year are obtained.

[0031] Step (5) includes the following specific steps: For each joint scenario and each candidate pump station scale in the set of uncertain scenarios, the hourly water conservation continuous simulation of the regulation and storage zone is carried out, the hourly pumping amount , the overflow amount , and the storage amount of the regulation and storage zone in a year are simulated, and the hourly pumping amount time series diagram, the regulation and storage zone overflow time series diagram, and the regulation and storage zone storage amount time series diagram are drawn.

[0032] The specific steps of the hourly water conservation continuous simulation of the regulation and storage zone include: At each time , it is determined whether the pump station is started according to the current storage amount and water demand; it is assumed that the pump station is started when the irrigation water demand is not met, and pumping is carried out until the demand is met or the rated capacity is reached; otherwise, it is closed; under the premise of no minimum start-stop constraint and no energy consumption limit, the calculation formula of the pump station pumping amount at time is: , Wherein, is the candidate scale, representing the rated pumping and drainage capacity of the pump station under current investigation, is the regulation and storage zone the storage volume at time t+1, unit: m³; for a certain joint scenario the hourly irrigation water demand, ; this formula ensures that the pumping volume of the pumping station is upper limited by the water demand, but does not exceed the pumping station scale and will not exceed the existing storage.

[0033] The calculation of the overflow water volume of the regulation and storage belt and the water volume balance calculation of the regulation and storage belt are carried out. First, the theoretical storage volume without considering overflow is calculated, and the calculation formula is: , wherein, the storage volume at time t+1 without considering overflow, the storage volume at time t of the regulation and storage belt, for a certain joint scenario the upstream hourly inflow, unit: m³ / h, 3 ; ; the hourly pumping volume of the pumping station, unit: m³ / h.

[0034] If exceeds the fixed storage capacity of the regulation and storage belt , overflow occurs, otherwise no overflow, and the calculation formula of the overflow volume of the regulation and storage belt is: , wherein, the unit of is m³ / h; the unit of is m³; the storage volume at time t+1 of the regulation and storage belt is updated, and the calculation formula is: .

[0035] In an embodiment, under the condition of “a certain joint scenario + a certain pumping station scale”, the annual scale regulation and storage belt linkage continuous simulation results are shown in Figure 3 , Figure 4 , Figure 5 and Figure 6 , the horizontal axis is month Jan–Dec, and the hourly cumulative display is shown; Figure 3 , Figure 4 , Figure 5 and Figure 6 present the mechanism chain in turn: inflow → overflow → pumping to irrigation area → storage volume of regulation and storage belt. As shown in Figure 3 , the annual inflow is of a multi-peak type, and the high-frequency rainstorm period from late spring to early autumn (about April–September) appears several times with short duration peaks, and the highest peak value is significantly higher than that in other periods. The winter inflow is low and stable; this represents that under this joint scenario, the rainfall-concentration process concentrates the runoff in the flood season. As shown in​​Figure 4 As shown, the overflow curve is highly correlated with the inflow peak: whenever the inflow surges in a short time and the storage of the regulating reservoir is close to full, a sharp peak of overflow occurs; multiple overflow waves in flood season, with the peak value synchronized with the inflow peak, indicate that in the current scale of the pumping station and the configuration of the reservoir capacity, the extreme water inflow period will still trigger the over-limit water discharge. As shown, Figure 5 the pumping process is mainly constrained by two factors: one is the upper limit of the rated scale of the pumping station; the other is the current irrigation water demand; the curve fluctuates frequently in the spring and summer crop growing season, and locally reaches a plateau, that is, close to the upper limit of the pumping station capacity, and falls significantly in winter; it can be seen that in the water demand season, the pumping station is in a “capacity supply” state most of the time; when the water demand is weak or the water storage is insufficient, the pumping is reduced to a low level. As shown, Figure 6 the storage increases rapidly at the beginning of the year with the inflow accumulation, and reaches and remains at the top for a long time in the second quarter, and then maintains a high plateau, indicating that in this scenario, the effective capacity of the regulating reservoir is occupied early; when the inflow continues to come but the pumping station and the downstream absorption capacity are insufficient, Figure 6 multiple overflows occur; when the pumping is enhanced or the water inflow is weakened in individual periods, the water storage may fall slightly, but overall it is close to the upper limit. Figure 3 , Figure 4 , Figure 5 and Figure 6 The comprehensive results show that: in this joint scenario and the current scale of the pumping station, the reservoir capacity utilization tends to be saturated and repeated overflow occurs in the flood season; the pumping curve has multiple plateaus, indicating that the pumping station capacity becomes the constraint, rather than the water demand or inflow constraint, suggesting that there is potential benefit in expanding the scale or optimizing the operation (linked with the water distribution side); if the first layer inflection point is identified by the robust curve of “overflow volume – scale”, this scenario belongs to the typical performance on the left side of the inflection point: increasing the scale of the pumping station is expected to significantly reduce the sharp peak overflow in the flood season; the long-term plateau of the water storage also suggests that: under the same reservoir capacity, increasing the scale of the pumping station or reserving capacity before the flood season (operation strategy) can reduce the overflow risk of extreme events.

[0036] (6) According to the annual hourly overflow volume of the regulating reservoir, calculate the cumulative annual overflow volume and inflow volume under each joint scenario and each candidate pumping station scale , calculate the annual overflow volume percentage and the initial uncertainty coverage, and the initial uncertainty coverage refers to the proportion of scenarios that meet the “annual overflow percentage does not exceed the target threshold percentage” in all joint scenarios under the candidate pumping station scale .

[0037] Step (6) includes the following specific steps: According to the annual hourly overflow data of the regulating reservoir , calculate each joint scenario and each candidate pumping station scale the annual percentage of overflow water volume , in percentage. The formula for calculating the annual percentage of overflow water volume is: , The target threshold percentage of annual overflow water volume is set as , in percentage.

[0038] For each candidate pump station scale , first construct the indicator function , where the indicator function represents whether the joint scenario meets the compliance condition at the pump station scale , and 1 if it meets the compliance condition, otherwise 0; the expression of the indicator function is: .

[0039] Calculate the initial uncertainty coverage , in percentage, which refers to the proportion of scenarios that meet the condition of "annual overflow percentage not exceeding the target threshold percentage" among all joint scenarios at the pump station scale . The formula for calculating the initial uncertainty coverage is: .

[0040] (7) Based on all candidate pump station scales and corresponding initial uncertainty coverages, draw a relationship graph of pump station scale and initial uncertainty coverage , in the form of a histogram, and smooth the relationship graph to reduce fluctuations to obtain the first coverage robustness curve. After identifying the inflection point, obtain the first layer of inflection points of the pump station scale , and construct the uncertainty interval for pump station scale optimization.

[0041] Step (7) includes the following specific steps: Let the data points on the relationship graph of pump station scale and initial uncertainty coverage be . The sliding average method can be used to smooth the first coverage robustness curve, and the calculation formula is: , where is half the width of the sliding window, which is an integer selected empirically, and the window size is , This is the first coverage robust curve after smoothing.

[0042] To further analyze the efficiency of coverage improvement, the smoothed first coverage robust curve is differentially processed, and the first-order difference is calculated. and second-order difference First-order difference The calculation formula is: , Second-order difference The calculation formula is: .

[0043] The first inflection point of the first coverage robustness curve is defined as the position where the coverage improvement rate decreases significantly, that is, the inflection point occurs where the second difference changes from positive to negative. Extreme points that jump from positive to negative, and extreme points that satisfy the conditions. This is the first inflection point. The specific conditions to be met are as follows: , in The threshold is set as an empirical parameter. or , This means that both conditions are met simultaneously.

[0044] Based on the identified first-layer inflection point The uncertainty interval for optimizing the scale of the pumping station is constructed, and the expression for the uncertainty interval is: , in This is the lower bound of the uncertainty interval for optimizing the pump station size based on the first-level inflection point. The upper limit of the uncertainty interval for optimizing the pump station scale based on the first inflection point; and For the empirical optimization coefficients, where , , , .

[0045] like Figure 7 As shown, based on 52,560 scenarios, the first inflection point of the storage zone A is 6,000 cubic meters per day, with an uncertainty range of 4,000 cubic meters per day to 9,000 cubic meters per day.

[0046] (8) In the uncertainty interval Internal calculation of final uncertainty coverage A second coverage robust curve is formed, and inflection points are identified on the second coverage robust curve to obtain the second layer inflection points. Second inflection point This is the optimal pump station size.

[0047] Step (8) includes the following specific steps: Uncertainty range for pump station size optimization based on the first inflection point Inside, there is a total of Candidate size , The smoothed initial uncertainty coverage for each candidate size is known to be... The initial uncertainty coverage after smoothing within the uncertainty interval As sample points, according to candidate size Sort the samples from smallest to largest to form an ordered set. : , For the sample set The empirical cumulative distribution function of the coverage is denoted as the final uncertainty coverage. ,in At any sample point The function value is defined as the value of a sample that is less than or equal to 0. The sum of the initial uncertainty coverage of the sample points, and the final uncertainty coverage. The calculation formula is: , Final Uncertainty Coverage A second coverage robustness curve is generated, and inflection points are identified on the second coverage robustness curve to obtain the second layer inflection points. The calculation formula is: , For the final uncertainty coverage of the pump station size The first derivative, For the final uncertainty coverage of the pump station size The second derivative, The curvature of the second coverage robust curve is the point where the maximum curvature indicates the most significant point where the growth rate slows down. The marginal increment of the uncertainty coverage shows a decreasing trend, which is used to eliminate local noise and lock in the true turning point of "rapid increase → slow increase". The marginal increment is the differential gain of the scale of adjacent pumping stations. The size of the pumping station to maximize the objective function ; As the determination condition, where This means simultaneously satisfying, is the marginal increment or discrete difference of the uncertainty coverage to the pump station scale, if the pump station scale level is , is the total number of pump station scales in the uncertainty interval of the pump station scale optimization, then: , represents the increase of the pump station scale from to , how much does the coverage increase? represents a monotonic decrease or decreasing trend, meaning that near the inflection point, especially after the inflection point, a trend of from big to small, the marginal gain is getting smaller and smaller; used to prevent mistaking noise points as inflection points by "maximum curvature" alone; only when "the curvature is maximum at the pump station scale and "the marginal coverage continues to decline or no longer rises" after that, the corresponding pump station scale is identified as the second layer inflection point .

[0048] As shown in Figure 8 , as the pump station scale increases, its coverage of scenarios considering various factor uncertainties also increases, that is, the increase of the pump station scale can meet the minimum spill flow of the regulation and storage zone in more cases. The uncertainty coverage of a certain pump station scale represents the applicable range of this pump station scale, so when the coverage is higher, it means that this pump station scale is applicable to more cases. From Figure 7 , it can be seen that there is a very strong nonlinearity between the increase of the pump station scale and the uncertainty scenario coverage, and when the pump station scale increases to a certain extent, the benefits brought by the continued increase of the pump station scale gradually decrease. Therefore, the second layer inflection point of the critical pump station scale is identified, and the optimal pump station scale of the regulation and storage zone A is 7000 m3 / d. In this pump station scale case, about 95% of the scenarios can achieve the regulation and storage zone spill flow within the overflow percentage target.

[0049] Using the same method, the pumping station scale of regulation and storage zone B and regulation and storage zone C were optimized. The optimal pumping station scale for regulation and storage zone B was found to be 8,000 cubic meters / day, and the optimal pumping station scale for regulation and storage zone C was found to be 12,000 cubic meters / day. The three zones showed significant differences in service scale and regulation and storage capacity: regulation and storage zone B had the largest volume (155,219 cubic meters) and the smallest irrigated area (2,310 mu). The unit area available for regulation and storage was approximately 0.00672 million cubic meters / mu (≈67 m³ / mu), which is the highest level of "surplus" in regulation and storage and has the strongest buffer against extreme inflows and peak water demand. Storage belt A has a medium volume (90,799 cubic meters) and a medium area (2,863 mu), with a storage capacity of approximately 0.00317 million cubic meters per mu (≈32 m³ / mu). Its overall pressure is moderate, and reasonable pumping can balance overflow reduction and irrigation. Storage belt C has the largest irrigation area (7,330 mu) but the smallest volume (72,960 cubic meters), with a storage capacity of only approximately 0.000995 million cubic meters per mu (≈10 m³ / mu). It is the most "stressed" and more prone to overflow and backflow during the flood season, making it most sensitive to pump station capacity and operational strategies. The overall storage pressure ranking is: Storage belt C > Storage belt A > Storage belt B.

[0050] Example 2: As Figure 2 As shown, this invention discloses a system for optimizing the scale of water storage pumping stations based on uncertain coverage, comprising: The upstream inflow calculation module is used to collect historical hourly rainfall data from multiple rain gauge stations in the upstream inflow area of ​​the target pumping station, and expand the generation... The system generates hourly rainfall scenarios throughout the year. Each rainfall scenario is input into a calibrated watershed hydrological model to calculate and output hourly time series of inflow boundary flow upstream of the storage zone.

[0051] The upstream inflow calculation module collects historical hourly rainfall data from multiple rain gauge stations within the upstream inflow area of ​​the target pumping station, spanning [duration missing]. Year, The time step is 2~3. The duration is 1 hour; based on the collected historical rainfall data, a rainfall generation model is used to generate rainfall. Hourly rainfall scenarios throughout the year The data should be expanded by at least 10 times, that is Each set of rainfall scenarios Input a calibrated watershed hydrological model, calculate and output the hourly time series of inflow boundary discharge upstream of the storage zone. Unit m 3 / h, Represents an hourly sequence. It records the annual water inflow data for 8760 hours under each rainfall scenario and can draw a time series diagram of the water inflow data.

[0052] Hourly time series of inflow boundary flow upstream of the regulating reservoir The expression is: , in For the parameters of the watershed hydrological model, This describes the calculation process of the watershed hydrological model, which is the LSPC model.

[0053] The upstream irrigation water demand calculation module is used to divide the annual water-saving irrigation quota into equal intervals based on the minimum and maximum values ​​of the annual water-saving irrigation quota. The system is divided into levels to obtain the annual irrigation quota for each level of water saving; then the hourly-scale irrigation water demand of the upstream of the storage zone is calculated for each rainfall scenario and each level of annual irrigation quota for water saving.

[0054] The minimum value of the annual water-saving irrigation quota is set in the upstream irrigation water demand calculation module. and maximum value minimum value 218 maximum value 450 , with minimum value To the maximum value The gradations are equidistant from each other. class, , Then the first Grade A water-saving annual irrigation quota The calculation formula is: , The unit is .

[0055] Each rainfall scenario was obtained through simulation calculations using the LSPC model. Hourly irrigation water requirements Based on hourly irrigation water demand Calculate rainfall scenarios At any moment Hourly scale irrigation water demand weight The calculation formula is: , in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is .

[0056] Set the area of ​​farmland upstream of the water storage belt that needs irrigation If the unit is mu (a Chinese unit of area), then each rainfall scenario... and the hourly scale regulation and storage upstream irrigation water demand under the level- i water-saving annual irrigation quota The calculation formula is: , wherein, The unit is , is the level- i annual irrigation quota, is the hourly scale irrigation water demand weight. The uncertainty scenario set module is configured to combine any set of rainfall scenarios and any level- i water-saving annual irrigation quota to form a joint scenario

[0057] and form an uncertainty scenario set, wherein the total number of joint scenarios is , . The candidate pump station scale set module is configured to determine the upper limit and lower limit of the scale of the pump station to be optimized according to the engineering investment and operation requirements, and obtain the optimization interval of the pump station scale

[0058] , wherein the pump station scale refers to the rated pumping and drainage flow of the pump station under the design condition, the pump station scale is expressed in the hourly scale, and the unit is ; the design condition refers to the design lift, the design rotating speed, and the rated unit configuration and parallel system mode; the optimization interval of the pump station scale is equally divided into K parts, K = 10-50, the optimization step is calculated, and the calculation formula of the optimization step is: , The candidate pump station scale set is obtained, , then the candidate pump station scale is obtained, each is a candidate scale.

[0059] The water conservation continuous simulation module is configured to perform, for each joint scenario and each candidate pump station scale , the hourly water conservation continuous simulation of the regulation and storage zone in a whole year to obtain the hourly pumping amount of the pump station, the overflow amount of the regulation and storage zone, and the storage amount of the regulation and storage zone in a whole year.

[0060] In the water conservation continuous simulation module, for each joint scenario in the uncertainty scenario set and each candidate pump station scale , the hourly water conservation continuous simulation of the regulation and storage zone in a whole year is performed to simulate the hourly pumping amount of the pump station , the overflow amount of the regulation and storage zone , and the storage amount of the regulation and storage zone And corresponding hourly time-series diagrams of pumping volume, overflow of storage tank, and water storage of storage tank are drawn throughout the year.

[0061] The specific steps for continuous calculation of water conservation in the reservoir area on an hourly basis throughout the year include: At every moment The decision to activate the pumping station is based on the current water level and the water demand. The station is activated if irrigation water demand is insufficient, pumping water until the demand is met or the rated capacity is reached; otherwise, it is shut down. Under the premise of no minimum start-stop constraints and no energy consumption limitations, the pumping station operates at any given time. Pumping capacity of the pumping station The calculation formula is: , in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation. Storage belt Real-time water volume, in m³; For joint scenarios Hourly irrigation water requirements This formula ensures that the pumping capacity of the pumping station is limited to meeting the water demand, but does not exceed the scale of the pumping station or the existing water storage.

[0062] The overflow volume and water balance of the storage tank are calculated. First, the theoretical storage volume is calculated without considering the overflow. The calculation formula is as follows: , in, To disregard the water volume in the storage zone at time t+1 during overflow, To regulate the water storage volume at time t, For joint scenarios The upstream water inflow for the next hour, in cubic meters (m³). 3 / h, ; This represents the pumping capacity of the pumping station per hour, expressed in m³ / h.

[0063] like Exceeding the fixed storage capacity of the storage belt If it overflows, then overflow occurs; otherwise, there is no overflow. The overflow volume is regulated by the storage system. The calculation formula is: , in, The unit is m³ / h; The unit is m³; Update the water storage capacity of the regulating reservoir at time t+1. The calculation formula is: .

[0064] An initial uncertainty coverage calculation module calculates the accumulated annual spill flow and inflow water volume under each joint scenario and each candidate pumping station scale according to the annual hourly regulating reservoir spill flow data, calculates the annual scale spill flow water percentage, and calculates the initial uncertainty coverage.

[0065] In the initial uncertainty coverage calculation module, the accumulated annual spill flow and inflow water volume under each joint scenario and each candidate pumping station scale are calculated according to the annual hourly regulating reservoir spill flow data. The calculation formula of the annual scale spill flow water percentage is: , The annual scale spill flow water target threshold percentage is set as .

[0066] Under each candidate pumping station scale , a dummy function is first constructed, where the dummy function represents whether the joint scenario meets the standard condition under the pumping station scale , and is recorded as 1 if it meets the standard condition, or 0 otherwise; the expression of the dummy function is: , The initial uncertainty coverage is calculated, which is the percentage of scenarios that meet the condition of “annual spill flow percentage not exceeding the target threshold percentage” among all joint scenarios under the pumping station scale . The calculation formula of the initial uncertainty coverage is: .

[0067] A first layer inflection point identification module is used to draw a relationship diagram of the pumping station scale and the initial uncertainty coverage based on all candidate pumping station scales and corresponding initial uncertainty coverages, form a first coverage robustness curve, identify the first layer inflection point of the pumping station scale after the inflection point is identified, and construct an uncertainty interval for pumping station scale optimization. ​​​​​​​​​

[0068] The first layer inflection point identification module is provided with a pump station scale and initial uncertainty coverage The data points on the relationship diagram are The sliding average method can be used for smoothing to form a first coverage robust curve, and the calculation formula is: , Wherein, is half the width of the sliding window, and is an integer selected empirically, The window size is , The first coverage robust curve after smoothing.

[0069] In order to further analyze the efficiency of coverage improvement, the first coverage robust curve after smoothing is differentiated to calculate the first-order difference And the second-order difference The calculation formula of the first-order difference , The calculation formula of the second-order difference , The first layer inflection point of the first coverage robust curve is defined as the position where the coverage improvement speed decreases significantly, that is, the inflection point appears when the second-order difference changes from positive to negative, that is, when The extreme point of the extreme point Is the first layer inflection point , which satisfies the condition: , Wherein is a threshold empirical parameter, Or , Indicates that it meets at the same time.

[0070] According to the identified first layer inflection point , the uncertainty interval of pump station scale optimization is constructed, and the expression of the uncertainty interval is: , Wherein is the lower limit of the uncertainty interval of the pump station scale optimization based on the first layer inflection point, is the upper limit of the uncertainty interval of the pump station scale optimization based on the first layer inflection point; And are empirical optimization coefficients, wherein , , ,​​ .

[0071] The second-layer inflection point identification module calculates the final uncertainty coverage within the uncertainty interval, forming a second coverage robust curve. After inflection point identification, the second-layer inflection point is obtained, which is the optimal pump station scale.

[0072] In the second-layer inflection point identification module, within the uncertainty range of pump station scale optimization based on the first-layer inflection point... Inside, there is a total of Candidate size , The smoothed initial uncertainty coverage for each candidate size is known to be... The initial uncertainty coverage after smoothing within the uncertainty interval As sample points, according to candidate size Sort the samples from smallest to largest to form an ordered set. : , For the sample set The empirical cumulative distribution function of the coverage is denoted as the final uncertainty coverage. ,in At any sample point The function value is defined as the value of a sample that is less than or equal to 0. The sum of the initial uncertainty coverage of the sample points, and the final uncertainty coverage. The calculation formula is: , Final Uncertainty Coverage A second coverage robustness curve is generated, and inflection points are identified on the second coverage robustness curve to obtain the second layer inflection points. The calculation formula is: , The final uncertainty coverage of the pump station size The first derivative, The final uncertainty coverage of the pump station size The second derivative, The curvature of the second coverage robust curve is the point where the maximum curvature indicates the most significant point where the growth rate slows down. The marginal increment of the uncertainty coverage shows a decreasing trend, which is used to eliminate local noise and lock in the true turning point of "rapid increase → slow increase". The marginal increment is the differential gain of the scale of adjacent pumping stations. The size of the pumping station to maximize the objective function ; To determine the condition, wherein means simultaneously satisfying, means the marginal increment or discrete difference of uncertainty coverage to the scale of pumping stations, if the scale of pumping stations is , means the total number of pumping stations in the uncertainty interval of the optimization of pumping stations, then: , represents that the scale of pumping stations is increased from to , how much does the coverage increase? represents a monotonic decrease or decreasing trend, which means that near the inflection point, especially after the inflection point, presents a trend from large to small, and the marginal gain is getting smaller and smaller; it is used to prevent mistaking noise points as inflection points only by "maximum curvature"; only when "the curvature is maximum at the scale of pumping stations " and "the marginal coverage continues to decline or no longer rises" after that, the corresponding scale of pumping stations is identified as the second layer of inflection point .

[0073] Embodiment 3: The electronic device disclosed by the application comprises one or more processors, one or more memories, and one or more programs, the program is stored in the memory and is configured to be executed by the processor, and the program is loaded into the processor to realize the steps of the uncertainty coverage-based optimization method for the scale of pumping stations in the regulation and storage zone of embodiment 1.

[0074] Embodiment 4: The computer readable storage medium disclosed by the application stores a computer program, the computer program comprises program instructions, and the program instructions make the processor execute the steps of the uncertainty coverage-based optimization method for the scale of pumping stations in the regulation and storage zone of embodiment 1 when the processor executes the program instructions.

Claims

1. A method for optimizing the scale of water storage and regulation pumping stations based on uncertain coverage, characterized in that, Includes the following steps: (1) Collect historical hourly rainfall data from multiple rain gauge stations in the upstream water inflow area of ​​the target pumping station and expand the generation The system generates hourly rainfall scenarios throughout the year. Each rainfall scenario is input into a calibrated watershed hydrological model to calculate and output hourly time series of inflow boundary flow upstream of the storage zone. (2) Based on the minimum and maximum values ​​of the annual water-saving irrigation quota, the annual water-saving irrigation quota is divided into equal intervals. The water-saving annual irrigation quota for each level is obtained; then the hourly-scale irrigation demand of the upstream of the storage zone is calculated for each rainfall scenario and each level of the water-saving annual irrigation quota. (3) Combine any set of rainfall scenarios and any level of water-saving annual irrigation quota to form a joint scenario. These together form a set of uncertainty scenarios, where the total number of joint scenarios is... , ; (4) Set the optimization interval for the scale of the pumping station, and divide the optimization interval into K equal parts to obtain the set of candidate pumping station scales. Size of each candidate pumping station , ; (5) Based on the hourly time series of the inflow boundary flow upstream of the storage belt and the hourly irrigation water demand upstream of the storage belt, for each joint scenario and the size of each candidate pumping station A continuous simulation of the water volume conservation of the storage zone is conducted hourly throughout the year to obtain the overflow volume of the storage zone hourly throughout the year. (6) Calculate each combined scenario based on the hourly overflow volume of the storage belt throughout the year. and the size of each candidate pumping station The percentage of annual overflow and the initial uncertainty coverage, where the initial uncertainty coverage refers to the coverage at the candidate pumping station scale. All joint scenarios The proportion of scenarios that meet the condition that "the annual overflow percentage does not exceed the target threshold percentage"; (7) Based on all candidate pump station sizes and their corresponding initial uncertainty coverage, draw a relationship diagram between pump station size and initial uncertainty coverage to form the first coverage robust curve. After inflection point identification, obtain the first inflection point of pump station size and construct the uncertainty interval for pump station size optimization. (8) Calculate the final uncertainty coverage within the uncertainty interval to form the second coverage robust curve. After the inflection point is identified, the second inflection point is obtained. The second inflection point is the optimal pump station scale.

2. The method for optimizing the scale of a regulating and storage pumping station based on uncertain coverage as described in claim 1, characterized in that, Step (1) includes the following specific steps: Historical hourly rainfall data were collected from multiple rain gauge stations in the upstream water inflow area of ​​the target pumping station, lasting for [duration missing]. Year, The time step is 2~3, and the time step is... ; Based on the collected historical rainfall data, a rainfall generation model is used to generate... Hourly rainfall scenarios throughout the year The data should be expanded by at least 10 times, that is Each set of rainfall scenarios Input a calibrated watershed hydrological model, calculate and output the hourly time series of inflow boundary discharge upstream of the storage zone. Unit m 3 / h, Represents hourly sequences; records the annual rainfall under each rainfall scenario. Hourly water volume data; Hourly Time Series of Inflow Boundary Flow in the Regulating Belt The expression is: ， in For the parameters of the watershed hydrological model, This describes the calculation process of the watershed hydrological model, which is the LSPC model.

3. The method for optimizing the scale of a regulating and storage pumping station based on uncertain coverage as described in claim 2, characterized in that, Step (2) includes the following specific steps: Set a minimum annual irrigation quota for water conservation. and maximum value , with minimum value To the maximum value The gradations are equidistant from each other. class, Then the first Grade A water-saving annual irrigation quota The calculation formula is: ， The unit is ; Each rainfall scenario was obtained through simulation calculations using the LSPC model. Hourly irrigation water requirements Based on hourly irrigation water demand Calculate rainfall scenarios At any moment Hourly scale irrigation water demand weight The calculation formula is: ， in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is ; Set the area of ​​farmland upstream of the water storage belt that needs irrigation If the unit is mu (a Chinese unit of area), then each rainfall scenario... and the Hourly scale upstream irrigation water demand of water storage zone under the annual water-saving quota The calculation formula is: ， in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

4. The method for optimizing the scale of a regulating and storage pumping station based on uncertain coverage as described in claim 3, characterized in that, The specific steps for the continuous calculation of water conservation in the storage zone on an hourly basis throughout the year in step (5) include: At every moment The decision to activate the pumping station is based on the current water level and the water demand. The station is activated if irrigation water demand is insufficient, pumping water until the demand is met or the rated capacity is reached; otherwise, it is shut down. Under the premise of no minimum start-stop constraints and no energy consumption limitations, the pumping station operates at any given time. Pumping capacity of the pumping station The calculation formula is: ， in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation; Storage belt Real-time water volume, in m³; For joint scenarios Hourly irrigation water requirements ; The overflow volume and water balance of the storage tank are calculated. First, the theoretical storage volume is calculated without considering the overflow. The calculation formula is as follows: ， in, Storage zone without considering overflow Water level at all times Storage belt Water level at all times For joint scenarios The upstream water inflow for the next hour, in cubic meters (m³). 3 / h, ; This represents the hourly pumping capacity of the pumping station, expressed in m³ / h. like Exceeding the fixed storage capacity of the storage belt If it overflows, then overflow occurs; otherwise, there is no overflow. The overflow volume is regulated by the storage system. The calculation formula is: ， in, The unit is m³ / h; The unit is m³; renew Regulate water storage volume at all times The calculation formula is: 。 5. The method for optimizing the scale of a regulating storage pumping station based on uncertain coverage as described in claim 4, characterized in that, Step (6) includes the following specific steps: Based on the hourly overflow volume of the storage belt throughout the year Calculate each joint scenario and the size of each candidate pumping station The annual overflow and inflow are summed to calculate the annual-scale percentage of overflow. The unit is %, and the percentage of annual overflow is %. The calculation formula is: ， Set the annual overflow volume target threshold percentage as The unit is % Size of each candidate pumping station Next, we will construct the characteristic function. Indicator function Indicate joint scenario In terms of pump station scale Whether the following condition is met is recorded as 1 if the condition is met, otherwise 0; Indicator function The expression is: ， Calculate the initial uncertainty coverage The unit is %, initial uncertainty coverage. The calculation formula is: 。 6. The method for optimizing the scale of a regulating and storage pumping station based on uncertain coverage as described in claim 5, characterized in that, Step (7) includes the following specific steps: Design the scale of the pumping station and initial uncertainty coverage The data points on the relationship diagram are The first coverage robust curve is generated by smoothing using the moving average method. The calculation formula is as follows: ， in, The width is half the width of the sliding window, where is an empirically chosen integer, and the window size is . , The first coverage robust curve after smoothing; The smoothed first coverage robust curve is subjected to difference processing to calculate the first-order difference. and second-order difference First-order difference The calculation formula is: ， Second-order difference The calculation formula is: ， The first inflection point of the first coverage robustness curve is defined as the position where the coverage improvement rate decreases significantly, that is, the inflection point occurs where the second difference changes from positive to negative. Extreme points that jump from positive to negative, and extreme points that satisfy the conditions. This is the first inflection point. The specific conditions to be met are as follows: ， in The threshold is set as an empirical parameter. This means that both conditions are met simultaneously; Based on the identified first inflection point The uncertainty interval for optimizing the scale of the pumping station is constructed, and the expression for the uncertainty interval is: ， in This is the lower bound of the uncertainty interval for optimizing the pump station size based on the first-level inflection point. The upper limit of the uncertainty interval for optimizing the pump station scale based on the first inflection point; and For the empirical optimization coefficients, where , .

7. The method for optimizing the scale of a regulating storage pumping station based on uncertain coverage as described in claim 6, characterized in that, Step (8) includes the following specific steps: Uncertainty range for pump station size optimization based on the first inflection point Inside, there is a total of Candidate size , The smoothed initial uncertainty coverage for each candidate size is known to be... The initial uncertainty coverage after smoothing within the uncertainty interval As sample points, according to candidate size Sort the samples from smallest to largest to form an ordered set. : ， For the sample set The empirical cumulative distribution function of the coverage is denoted as the final uncertainty coverage. ,in At any sample point The function value is defined as the value of a sample that is less than or equal to 0. The sum of the initial uncertainty coverage of the sample points, and the final uncertainty coverage. The calculation formula is: ， Final Uncertainty Coverage A second coverage robustness curve is generated, and inflection points are identified on the second coverage robustness curve to obtain the second layer inflection points. The calculation formula is: ， The final uncertainty coverage of the pump station size The first derivative, The final uncertainty coverage of the pump station size The second derivative, The curvature of the second coverage robust curve is the point where the maximum curvature indicates the most significant point where the growth rate slows down. The marginal increment of the uncertain coverage shows a decreasing trend, and the marginal increment is the differential gain of the scale of adjacent pumping stations; The size of the pumping station to maximize the objective function ; As the determination condition, where This means simultaneously satisfying, This refers to the marginal increment or discrete difference of the uncertainty coverage with respect to the pump station size. If the pump station size level is... , This refers to the total number of pump station sizes within the uncertainty interval of pump station size optimization. Then: ， This indicates that the scale of the pumping station has been increased from... Increase to How much has the coverage improved? It indicates a monotonically decreasing or diminishing trend.

8. A system for optimizing the scale of water storage and storage pumping stations based on uncertain coverage, characterized in that, include: The upstream inflow calculation module is used to collect historical hourly rainfall data from multiple rain gauge stations in the upstream inflow area of ​​the target pumping station, and expand the generation... The system generates hourly rainfall scenarios throughout the year. Each rainfall scenario is input into a calibrated watershed hydrological model to calculate and output hourly time series of inflow boundary flow upstream of the storage zone. The upstream irrigation water demand calculation module is used to divide the annual water-saving irrigation quota into equal intervals based on the minimum and maximum values ​​of the annual water-saving irrigation quota. The water-saving annual irrigation quota for each level is obtained; then the hourly-scale irrigation demand of the upstream of the storage zone is calculated for each rainfall scenario and each level of the water-saving annual irrigation quota. The uncertainty scenario set module is used to combine any set of rainfall scenarios and any level of annual water-saving irrigation quota to form a joint scenario. These together form a set of uncertainty scenarios, where the total number of joint scenarios is... , ; The candidate pump station size set module is used to define the optimization interval for pump station size, divide the optimization interval into K equal parts, and obtain the candidate pump station size set. Size of each candidate pumping station , ; The water conservation continuous simulation module is used to perform simulations for each joint scenario based on the hourly time series of the inflow boundary flow upstream of the storage zone and the hourly-scale irrigation water demand upstream of the storage zone. and the size of each candidate pumping station A continuous simulation of the water volume conservation of the storage zone is conducted hourly throughout the year to obtain the overflow volume of the storage zone hourly throughout the year. The initial uncertainty coverage calculation module calculates each joint scenario based on the hourly overflow volume of the storage zone throughout the year. and the size of each candidate pumping station The percentage of annual overflow and the initial uncertainty coverage, where the initial uncertainty coverage refers to the coverage at the candidate pumping station scale. All joint scenarios The proportion of scenarios that meet the condition that "the annual overflow percentage does not exceed the target threshold percentage"; The first-layer inflection point identification module is used to draw a relationship diagram between pump station size and initial uncertainty coverage based on all candidate pump station sizes and corresponding initial uncertainty coverage, form the first coverage robust curve, obtain the first-layer inflection point of pump station size after inflection point identification, and construct the uncertainty interval for pump station size optimization. The second-layer inflection point identification module calculates the final uncertainty coverage within the uncertainty interval, forming a second coverage robust curve. After inflection point identification, the second-layer inflection point is obtained, which is the optimal pump station scale.

9. An electronic device, characterized in that: It includes one or more processors, one or more memories, and one or more programs, the programs being stored in the memory and configured to be executed by the processor, the programs being loaded onto the processor to implement the steps of the method for optimizing the scale of a regulating storage pumping station based on uncertainty coverage as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the steps of a method for optimizing the scale of a storage and regulation pumping station based on uncertainty coverage according to any one of claims 1 to 7.

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