A method, system, device and medium for optimizing scale of a regulating and storage belt pumping station based on uncertainty coverage

Abstract

The application discloses a kind of based on uncertainty coverage's regulating and storing belt pump station scale optimization method, system, equipment and medium, including the following steps: generating multiple sets of annual hourly rainfall scenarios;Water-saving annual irrigation quota is equidistantly divided, and multiple levels of water-saving annual irrigation quota are obtained;Rainfall scenarios and multiple levels of water-saving annual irrigation quota are combined to form joint scenarios;Candidate pump station scale set is constructed;For each joint scenario and each candidate pump station scale, simulate to obtain regulating and storing belt overflow volume;Calculate initial uncertainty coverage under each joint scenario and each candidate pump station scale;Form first coverage robustness curve based on initial uncertainty coverage, identify to obtain the first layer inflection point of pump station scale, and construct uncertainty interval;Calculate final uncertainty coverage in uncertainty interval, form second coverage robustness curve, and obtain optimal pump station scale after identification.The application improves the scientificity, practicality and robustness of pump station scale selection.

Description

Technical Field

[0001] This invention relates to the technical field of pump station optimization, and in particular to a method, system, equipment, and medium for optimizing the scale of a regulating and storage pump station based on uncertain coverage. Background Technology

[0002] In engineering practices that use pumping stations to alleviate overflow from water storage tanks and reduce environmental pollution risks, the uncertainty of meteorological conditions makes it difficult to achieve synergistic optimization between environmental and economic benefits and determine the optimal pumping station size. Existing methods for determining pumping station size still have significant shortcomings in terms of both concepts and tools, which restrict their practical value and widespread application. Specifically, these shortcomings include the following:

[0003] (1) The "design storm method" replaces the continuous process over many years, thus ignoring the time sequence and the cumulative effect within the year. Currently, engineering projects often use single or a few typical storms, combined with IDF curves, Richardson's method or rational formulas, to determine reservoir capacity and capacity. This method is difficult to reflect the coupling effect between multi-peak rainfall, soil moisture memory effect, previous conditions and seasonal water demand, which can easily lead to conservative or mismatched schemes.

[0004] (2) Insufficient handling of rainfall input and model uncertainty, making the determination of pump station size prone to bias.

[0005] Existing methods often attribute errors to model parameters, ignoring rainfall estimation errors, which are a source of runoff uncertainty. As a result, they cannot comprehensively quantify input uncertainty and model structure / parameter uncertainty, and the resulting optimal pump station size will be highly sensitive to scenario selection and have poor stability.

[0006] (3) The uncertainty of irrigation water demand is roughly characterized.

[0007] The failure to fully reflect different irrigation quotas leads to a distorted supply-demand match, which in turn affects the judgment of the required pumping capacity;

[0008] (4) It emphasizes operation over planning and lacks robust selection methods for scale determination.

[0009] Existing technologies mostly focus on the scheduling and energy consumption control of existing pumping stations, lacking scientific decision-making methods for determining the optimal pumping station size in the early stages of a project (new construction / renovation and expansion). Therefore, when advancing from "operation optimization" to the strategic decision of "size selection", there is a lack of robust criteria and evidence chains that can be directly applied.

[0010] Therefore, it is urgent to solve the above problems. Summary of the Invention

[0011] Purpose of the invention: The first purpose of this invention is to provide a method for optimizing the scale of regulating and storage pumping stations based on uncertain coverage, thereby improving the scientificity, practicality and robustness of pumping station scale selection.

[0012] The second objective of this invention is to provide a system for optimizing the scale of storage and flood control pumping stations based on uncertain coverage.

[0013] A third objective of this invention is to provide an electronic device.

[0014] A fourth objective of this invention is to provide a computer-readable storage medium.

[0015] Technical Solution: To achieve the above objectives, this invention discloses a method for optimizing the scale of water storage pumping stations based on uncertain coverage, comprising the following steps:

[0016] (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.

[0017] (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.

[0018] (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... , ;

[0019] (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 , ;

[0020] (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.

[0021] (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";

[0022] (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.

[0023] (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.

[0024] Optionally, step (1) includes the following specific steps:

[0025] 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. It can display hourly water inflow data and draw time-series graphs of the water inflow data.

[0026] Hourly Time Series of Inflow Boundary Flow in the Regulating Belt The expression is:

[0027] ,

[0028] in For the parameters of the watershed hydrological model, This describes the calculation process of the watershed hydrological model, which is the LSPC model.

[0029] Optionally, step (2) includes the following specific steps:

[0030] 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:

[0031] ,

[0032] The unit is ;

[0033] 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:

[0034] ,

[0035] in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is ;

[0036] 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:

[0037] ,

[0038] in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

[0039] 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:

[0040] 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:

[0041] ,

[0042] in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation; Storage and regulation zone Real-time water volume, in m³; For joint scenarios Hourly irrigation water requirements ;

[0043] 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:

[0044] ,

[0045] in, Storage zone without considering overflow Water level at all times Storage and regulation zone 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.

[0046] 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:

[0047] ,

[0048] in, The unit is m³ / h; The unit is m³;

[0049] renew Regulate water storage volume at all times The calculation formula is:

[0050] .

[0051] Optionally, step (6) includes the following specific steps:

[0052] 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:

[0053] ,

[0054] Set the annual overflow volume target threshold percentage as The unit is %

[0055] 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:

[0056] ,

[0057] Calculate the initial uncertainty coverage The unit is %, initial uncertainty coverage. The calculation formula is:

[0058] .

[0059] Optionally, step (7) includes the following specific steps:

[0060] 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:

[0061] ,

[0062] 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;

[0063] 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:

[0064] ,

[0065] Second-order difference The calculation formula is:

[0066] ,

[0067] 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:

[0068] ,

[0069] in The threshold is set as an empirical parameter. This indicates that both conditions are met simultaneously;

[0070] 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:

[0071] ,

[0072] 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 , .

[0073] Optionally, step (8) includes the following specific steps:

[0074] 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. :

[0075] ,

[0076] 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:

[0077] ,

[0078] 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:

[0079] ,

[0080] 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:

[0081] ,

[0082] 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.

[0083] 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:

[0084] 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.

[0085] 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.

[0086] 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... , ;

[0087] 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 , ;

[0088] 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.

[0089] 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 meet the condition that "the annual overflow percentage does not exceed the target threshold percentage";

[0090] 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.

[0091] 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.

[0092] Based on the same inventive concept, this invention discloses an electronic device including one or more processors, one or more memories, and one or more programs. The programs are stored in the memory and configured to be executed by the processor. When the programs are loaded onto the processor, they implement the steps of a method for optimizing the scale of a regulating and storage pumping station based on uncertainty coverage as described above.

[0093] Based on the same inventive concept, the present invention discloses a computer-readable storage medium storing 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 regulating storage pumping station based on uncertainty coverage as described above.

[0094] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0095] (1) This invention overcomes the problems of existing technologies in determining the scale of regulating and storage pumping stations, such as "using design rainstorms to replace continuous processes, insufficient characterization of uncertainties, and lack of coverage and robust selection", and improves the scientificity, practicality and robustness of pumping station scale selection.

[0096] (2) This invention constructs an integrated logic chain of annual scale and hourly step size for “rainfall scenario → watershed hydrological model → regulation and storage zone - pumping station linkage”, and adopts a unified pumping station activation logic of “pumping when there is water storage and water demand, and pumping does not exceed the pumping station scale”, which comprehensively characterizes the coupling effect of multi-peak rainfall, early bottom water and seasonal water demand, and provides interpretable whole-process evidence for pumping station scale selection.

[0097] (3) This invention addresses meteorological uncertainty and water use differences by constructing a multi-rainfall scenario database and forming a multi-level water demand time series based on LSPC; it combines different pump station scales to form a multi-level joint scenario, and uses uncertainty coverage to measure the reliability of the optimization results, thereby improving the robustness and reproducibility of the conclusions.

[0098] (4) This invention introduces water demand uncertainty based on LSPC. Based on the LSPC model, water demand uncertainty is constructed in intervals at equal levels. Combined with the hourly water demand sequence output by the model, the structural differences between different quotas and water demand time series are expressed in detail, the supply and demand mismatch is corrected, and the required pumping capacity is accurately defined and the scale is supported.

[0099] (5) This invention proposes an integrated selection framework of "pump station size - uncertainty coverage - inflection point". First, the first inflection point is identified on the robust curve of "overflow percentage - pump station size" and then the second inflection point is identified on the robust curve of "uncertainty coverage - pump station size". Within the budget and technical boundaries, the minimum pump station size that meets the target coverage is given, so as to achieve the synergistic optimization of overflow reduction / environmental benefits and investment utilization / economic benefits, and improve the scientificity, practicality and scalability of the scheme. Attached Figure Description

[0100] Figure 1 This is a schematic diagram of the process of the present invention;

[0101] Figure 2 This is a schematic diagram of the system framework of the present invention;

[0102] Figure 3 This is a time-series diagram of the water inflow data in this invention;

[0103] Figure 4 This is a time-series diagram of the pumping volume of the pumping station throughout the year, hourly, in this invention;

[0104] Figure 5 This is a time-series diagram of the overflow of the storage belt throughout the year in this invention;

[0105] Figure 6 This is a time-series diagram of the hourly water storage capacity of the regulating reservoir throughout the year in this invention;

[0106] Figure 7 This is the first coverage robustness curve in this invention;

[0107] Figure 8 This is the second coverage robustness curve in this invention. Detailed Implementation

[0108] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0109] It should be understood that the invention can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In the drawings, for clarity, the dimensions and relative dimensions of the parts may be exaggerated. The same reference numerals denote the same parts throughout.

[0110] Example 1: As Figure 1 As shown, this invention discloses a method for optimizing the scale of water storage pumping stations based on uncertain coverage, comprising the following steps:

[0111] (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.

[0112] Step (1) includes the following specific steps:

[0113] 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. 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. Record the annual water inflow data for 8760 hours under each rainfall scenario, and draw a time series graph of the water inflow data;

[0114] Hourly Time Series of Inflow Boundary Flow in the Regulating Belt The expression is:

[0115] ,

[0116] in For the parameters of the watershed hydrological model, This describes the calculation process of the watershed hydrological model, which is the LSPC model.

[0117] (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 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.

[0118] Step (2) includes the following specific steps:

[0119] Set a minimum annual irrigation quota for water conservation. 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:

[0120] ,

[0121] The unit is .

[0122] 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:

[0123] ,

[0124] in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is .

[0125] 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:

[0126] ,

[0127] in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

[0128] (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.

[0129] (4) Based on the project investment and operation requirements, determine the upper and lower limits of the scale of the pumping station to be optimized, and obtain the optimization range of the pumping station scale. Pump station scale refers to the rated pumping flow rate of the pump station under design operating conditions. Pump station scale is expressed on an hourly basis, with units of [missing information]. The design operating condition refers to the design head, design speed, rated unit configuration, and parallel system configuration. The optimization range for the pump station scale is divided into K equal parts, where K = 10~50. The optimization step size is calculated using the following formula:

[0130] ,

[0131] Obtain the set of candidate pump station sizes , The size of the candidate pumping station Each For a candidate size.

[0132] (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 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.

[0133] Step (5) includes the following specific steps:

[0134] For each joint scenario in the set of uncertainty scenarios and the size of each candidate pumping station A continuous simulation of the water volume conservation in the reservoir was conducted hourly throughout the year, simulating the hourly pumping volume of the pumping station throughout the year. Regulating the overflow volume of the storage belt and water storage capacity of the regulating belt And corresponding hourly time-series diagrams of pumping volume, overflow of storage tank, and water storage of storage tank are drawn throughout the year.

[0135] The specific steps for continuous calculation of water conservation in the reservoir area on an hourly basis throughout the year include:

[0136] 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:

[0137] ,

[0138] in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation. Storage and regulation zone 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.

[0139] 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:

[0140] ,

[0141] 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.

[0142] 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:

[0143] ,

[0144] in, The unit is m³ / h; The unit is m³;

[0145] Update the water storage capacity of the regulating reservoir at time t+1. The calculation formula is:

[0146] .

[0147] In one embodiment, under the given conditions of "a certain joint scenario + a certain pumping station scale", the annual-scale continuous simulation results of the regulation and storage belt linkage are as follows: Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown, the horizontal axis represents the month Jan–Dec, and the data is displayed cumulatively hourly. Figure 3 , Figure 4 , Figure 5 and Figure 6 The mechanism chain unfolds sequentially: inflow → overflow → pumping water into the irrigation area → water storage in the regulation zone. For example... Figure 3 As shown, the annual inflow exhibits a multi-peak pattern, with a high-frequency period of heavy rainfall from late spring to early autumn (approximately April–September), resulting in several short-duration peaks, the highest of which is significantly higher than in other periods. Winter inflow is low and stable; this indicates that under this combined scenario, the rainfall-confluence process concentrates runoff release during the flood season. Figure 4 As shown, the overflow curve is strongly correlated with the inflow peak: whenever the inflow suddenly increases in a short period of time and the superimposed regulating storage zone is close to full, a peak-shaped overflow occurs; during the flood season, there are multiple overflow waves, and the peak size is synchronized with the inflow peak, indicating that under the current pumping station scale and reservoir capacity configuration, extreme water inflow periods will still trigger over-limit water release. Figure 5 As shown, the pumping process is mainly constrained by two factors: the upper limit of the pumping station's rated capacity and the current irrigation water demand. The curve fluctuates frequently during the peak growing season of spring and summer crops, reaching a plateau locally, close to the pumping station's capacity limit, and then drops significantly in winter. This indicates that during peak water demand seasons, the pumping station operates in a "supply-by-capacity" state for most of the time; when water demand is weak or water storage is insufficient, pumping drops to a lower level. Figure 6 As shown, the water level rose rapidly at the beginning of the year due to the accumulation of inflow, reaching its peak around the second quarter and remaining there for a long period, subsequently maintaining a high level. This indicates that under this scenario, the effective storage capacity of the regulating reservoir was filled relatively early. Later, when the inflow continued but the pumping stations and downstream absorption capacity were insufficient, Figure 6 The water level was observed to overflow multiple times; during certain periods when pumping was increased or the inflow was reduced, the water volume was slightly reduced, but overall it remained close to the upper limit. Figure 3 , Figure 4 , Figure 5 and Figure 6The combined results show that under this combined scenario and the current pumping station scale, reservoir capacity utilization is approaching saturation and repeated overflows occur during the flood season. The pumping curve shows multiple plateaus, indicating that pumping station capacity is a constraint rather than water demand or inflow, suggesting potential benefits from expanding the scale or optimizing operation (in conjunction with the water distribution side). If the robust curve of "overflow-scale" is used to identify the first inflection point, this scenario is a typical manifestation to the left and near the inflection point: increasing the scale of the pumping station is expected to significantly reduce peak overflows during the flood season. The long-term top-level water storage also suggests that, under the same reservoir capacity, increasing the scale of the pumping station or reserving capacity before the flood season (operational strategy) can reduce the overflow risk of extreme events.

[0148] (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 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 meet the condition that "the annual overflow percentage does not exceed the target threshold percentage".

[0149] Step (6) includes the following specific steps:

[0150] Based on hourly overflow data 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:

[0151] ,

[0152] Set the annual overflow volume target threshold percentage as The unit is %.

[0153] 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:

[0154] .

[0155] Calculate the initial uncertainty coverage The unit is %, and the initial uncertainty coverage refers to the coverage of pump stations with a scale of %. At that time, all joint scenarios The proportion of scenarios that meet the condition of "annual overflow percentage not exceeding the target threshold percentage", and the initial uncertainty coverage. The calculation formula is:

[0156] .

[0157] (7) Based on the scale of all candidate pumping stations and the corresponding initial uncertainty coverage, plot the scale of the pumping stations. and initial uncertainty coverage The relationship diagram was constructed using a histogram format and smoothed to reduce fluctuations, resulting in the first coverage robust curve. After inflection point identification, the first layer of inflection points for the pump station scale was obtained. And construct the uncertainty range for optimizing the scale of the pumping station.

[0158] Step (7) includes the following specific steps:

[0159] Design the scale of the pumping station and initial uncertainty coverage The data points on the relationship diagram are The first coverage robust curve can be formed by smoothing using the moving average method. The calculation formula is as follows:

[0160] ,

[0161] in, Half the width of the sliding window, and an integer chosen empirically. Window size is , This is the first coverage robust curve after smoothing.

[0162] 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:

[0163] ,

[0164] Second-order difference The calculation formula is:

[0165] .

[0166] 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:

[0167] ,

[0168] in The threshold is set as an empirical parameter. or , This means that both conditions are met simultaneously.

[0169] 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:

[0170] ,

[0171] 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 , , , .

[0172] 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.

[0173] (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.

[0174] Step (8) includes the following specific steps:

[0175] 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. :

[0176] ,

[0177] 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:

[0178] ,

[0179] 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:

[0180] ,

[0181] 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 ; 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:

[0182] ,

[0183] This indicates that the scale of the pumping station has been increased from... Increase to How much has the coverage improved? This indicates a monotonically decreasing or diminishing trend, meaning it is near an inflection point, especially after the inflection point. The marginal gain decreases as it decreases from large to small; this is used to prevent mistaking the noise point as an inflection point based solely on "maximum curvature"; only when "curvature is within the pump station scale" "At the maximum" and "then the marginal coverage" Only when the water level continues to drop or stops rising should the corresponding pumping station scale be adjusted. Identified as the second inflection point .

[0184] like Figure 8 As shown, with the increase in pump station size, its coverage of scenarios considering various uncertainties also increases; that is, a larger pump station size can meet the requirement of minimizing the overflow of the storage tank in more situations. The uncertainty coverage of a certain pump station size characterizes the applicability of that pump station size, so a higher coverage indicates that this pump station size is applicable to more situations. From Figure 7 It can be seen that there is a very strong nonlinearity between the increase in pump station size and the coverage of uncertain scenarios. After the pump station size increases to a certain extent, the benefits of further increasing the pump station size gradually decrease. Therefore, a second-level inflection point identification of the critical pump station size is performed, and the optimal pump station size for regulating storage zone A is found to be 7000 cubic meters / day. Under this pump station size, the overflow of the regulating storage zone can be kept within the overflow percentage target in approximately 95% of the scenarios.

[0185] 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.

[0186] Example 2: Figure 2 As shown, this invention discloses a system for optimizing the scale of water storage pumping stations based on uncertain coverage, comprising:

[0187] 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.

[0188] 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.

[0189] Hourly Time Series of Inflow Boundary Flow in the Regulating Belt The expression is:

[0190] ,

[0191] in For the parameters of the watershed hydrological model, This describes the calculation process of the watershed hydrological model, which is the LSPC model.

[0192] 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.

[0193] 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:

[0194] ,

[0195] The unit is .

[0196] 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:

[0197] ,

[0198] in, Since it is dimensionless, the unit of the molecule in the calculation formula is . The unit of the denominator is .

[0199] 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:

[0200] ,

[0201] in, Units are , For the first Annual irrigation quota, The water demand weight for irrigation on an hourly scale.

[0202] 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... , .

[0203] The candidate pump station size aggregation module determines the upper and lower limits of the pump station size to be optimized based on project investment and operational requirements, thus obtaining the optimization range for the pump station size. Pump station scale refers to the rated pumping flow rate of the pump station under design operating conditions. Pump station scale is expressed on an hourly basis, with units of [missing information]. The design operating condition refers to the design head, design speed, rated unit configuration, and parallel system configuration. The optimization range for the pump station scale is divided into K equal parts, where K = 10~50. The optimization step size is calculated using the following formula:

[0204] ,

[0205] Obtain the set of candidate pump station sizes , The size of the candidate pumping station Each For a candidate size.

[0206] 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.

[0207] In the continuous simulation module for water conservation, each joint scenario in the set of uncertain scenarios... and the size of each candidate pumping station A continuous simulation of the water volume conservation in the reservoir was conducted hourly throughout the year, simulating the hourly pumping volume of the pumping station throughout the year. Regulating the overflow volume of the storage belt and water storage capacity of the regulating belt And corresponding hourly time-series diagrams of pumping volume, overflow of storage tank, and water storage of storage tank are drawn throughout the year.

[0208] The specific steps for continuous calculation of water conservation in the reservoir area on an hourly basis throughout the year include:

[0209] 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:

[0210] ,

[0211] in, The candidate size represents the rated pumping capacity of the pumping station currently under investigation. Storage and regulation zone 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.

[0212] 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:

[0213] ,

[0214] 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.

[0215] 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:

[0216] ,

[0217] in, The unit is m³ / h; The unit is m³;

[0218] Update the water storage capacity of the regulating reservoir at time t+1. The calculation formula is:

[0219] .

[0220] 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 meet the condition that "the annual overflow percentage does not exceed the target threshold percentage".

[0221] The initial uncertainty coverage calculation module is based on hourly overflow data of the storage tank 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:

[0222] ,

[0223] Set the annual overflow volume target threshold percentage as The unit is %.

[0224] 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:

[0225] ,

[0226] Calculate the initial uncertainty coverage The unit is %, and the initial uncertainty coverage refers to the coverage of pump stations with a scale of %. At that time, all joint scenarios The proportion of scenarios that meet the condition of "annual overflow percentage not exceeding the target threshold percentage", and the initial uncertainty coverage. The calculation formula is:

[0227] .

[0228] 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, forming a first coverage robust curve. After inflection point identification, the first-layer inflection point of pump station size is obtained, and the uncertainty interval for pump station size optimization is constructed.

[0229] The first-level inflection point identification module sets the scale of the pumping station. and initial uncertainty coverage The data points on the relationship diagram are The first coverage robust curve can be formed by smoothing using the moving average method. The calculation formula is as follows:

[0230] ,

[0231] in, Half the width of the sliding window, and an integer chosen empirically. Window size is , This is the first coverage robust curve after smoothing.

[0232] 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:

[0233] ,

[0234] Second-order difference The calculation formula is:

[0235] ,

[0236] 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:

[0237] ,

[0238] in The threshold is set as an empirical parameter. or , This means that both conditions are met simultaneously.

[0239] 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:

[0240] ,

[0241] 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 , , , .

[0242] 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.

[0243] 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. :

[0244] ,

[0245] 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:

[0246] ,

[0247] 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:

[0248] ,

[0249] 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 ; 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:

[0250] ,

[0251] This indicates that the scale of the pumping station has been increased from... Increase to How much has the coverage improved? This indicates a monotonically decreasing or diminishing trend, meaning it is near an inflection point, especially after the inflection point. The marginal gain decreases as it decreases from large to small; this is used to prevent mistaking the noise point as an inflection point based solely on "maximum curvature"; only when "curvature is within the pump station scale" "At the maximum" and "then the marginal coverage" Only when the water level continues to drop or stops rising should the corresponding pumping station scale be adjusted. Identified as the second inflection point .

[0252] Example 3: An electronic device disclosed in this invention includes one or more processors, one or more memories, and one or more programs. The programs are stored in the memory and configured to be executed by the processor. When the programs are loaded onto the processor, they implement the steps of the method for optimizing the scale of a storage and flood control pumping station based on uncertainty coverage as described in Example 1.

[0253] Example 4: The present invention discloses a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the steps of the method for optimizing the scale of a storage and flood control pumping station based on uncertainty coverage in Example 1.

Claims

1. A method for optimizing the scale of a regulating and storage belt pumping station based on uncertainty coverage degree, characterized in that, Includes the following steps: (1) Collect the historical hourly rainfall data of multiple rainfall stations in the upstream inflow area of the target pumping station, expand to generate hourly rainfall scenarios throughout the year, input each rainfall scenario into the calibrated watershed hydrological model, calculate and output the hourly time series of the upstream inflow boundary flow of the regulation and storage zone; (2) According to the minimum and maximum of the water-saving annual irrigation quota, the water-saving annual irrigation quota is equally divided into level, and the water-saving annual irrigation quota of each level is obtained; the upstream irrigation water demand of the hour-scale regulation and storage zone under each rainfall scenario and water-saving annual irrigation quota is calculated; (3) Any one set of rainfall scenarios and any one level of water-saving irrigation quota are combined to form a joint scenario , and form an uncertainty scenario set, where the total number of joint scenarios is , ; (4) Set the optimization interval of pump station scale, divide the optimization interval into K parts to obtain a candidate pump station scale set Each candidate pump station scale , ; (5) According to the hourly time series of the boundary flow of the regulating and storage zone upstream and the hourly irrigation water requirement of the regulating and storage zone upstream, the annual hourly water conservation continuous simulation of each joint scenario and each candidate pump station scale is carried out to obtain the annual hourly overflow volume of the regulating and storage zone. (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 and regulation zone 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 and regulation zone 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 indicates that both conditions are met simultaneously; 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 , .

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: ， 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 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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