Water volume scheduling risk decision-making method for cross-basin water transfer project

Abstract

The invention discloses a water volume scheduling risk decision-making method for a cross-basin water transfer project, and the method comprises the steps: constructing a cross-basin water transfer system ten-day optimization scheduling model, and generating a scheduling scheme by taking ten days as a scale; a tolerable unit water transfer energy consumption threshold value is calculated according to the ten-day optimization scheduling model, and when the unit water transfer energy consumption exceeds the threshold value, the unit water transfer energy consumption risk occurs; meanwhile, the water transfer task risk is considered, and a judgment standard of water transfer risk occurrence is established; based on an evaluation standard, improving a ten-day optimization scheduling model, considering the uncertainty of incoming water, providing a water level calculation boundary by using a water source incoming water sequence of lakes along a water transfer line and a water level sequence simulation value of each lake along the water transfer line generated by a ten-day water level stochastic simulation model, and constructing a cross-basin scheduling risk quantification and optimization decision model; and obtaining a cross-basin optimization scheduling scheme, and evaluating the risk of the scheduling scheme and the sensitivity of key risk factors. According to the method, benefit and risk changes in the cross-basin water transfer process are determined, and technical support is provided for safe and efficient operation of cross-basin water transfer.

Description

Technical Field

[0001] The present invention belongs to the research field of inter-basin water transfer, and more specifically, relates to a risk decision-making method for water volume scheduling of inter-basin water transfer projects. Background Art

[0002] At present, the research methods of inter-basin scheduling are mainly to generalize and reduce the dimension of the complex inter-basin scheduling system, with the goal of optimizing water resources allocation, including minimizing water transfer cost, maximizing water storage satisfaction, minimizing system pumping volume, etc., and using dynamic programming algorithms, genetic algorithms and improved particle swarm algorithms to solve the optimization scheme of inter-basin water scheduling. At the same time, the study uses risk assessment indicators such as water transfer guarantee rate, water supply reliability and comprehensive risk degree to conduct risk assessment on the obtained inter-basin water optimization scheduling scheme. However, these research methods still have the following two problems: (1) These studies are mostly based on the historical deterministic water inflow process, considering the adverse effects of water shortage in the receiving area or the impact of changes in the hydrological situation in the receiving area on the scheduling process during the inter-basin scheduling process, but ignoring the water supply capacity under the influence of water inflow uncertainty in the water source area. The water inflow situation in the water source area is an important determinant of the inter-basin water transfer plan. The uncertainty of water inflow will affect the stability of the inter-basin scheduling process and the feasibility of the scheduling plan. (2) The optimization target of inter-basin water scheduling does not take into account the risk value, that is, the current research method independently considers the optimization and risk assessment of inter-basin water scheduling. Due to the influence of uncertainty and complexity of hydrological processes, there may be a situation where the optimization scheme and scheduling risk are not coordinated. Therefore, the current research method of inter-basin scheduling still has great limitations in practical operation guidance. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to overcome the shortcomings of the prior art and provide a risk decision-making method for water scheduling of inter-basin water transfer projects. Based on this method, the changes in benefits and risks in the process of inter-basin water transfer are deduced, and a low-risk, optimized inter-basin water optimization scheduling plan is provided.

[0004] Technical solution: The water volume dispatch risk decision-making method for a cross-basin water diversion project described in the present invention comprises the following steps:

[0005] The relationship between the engineering units in the inter-basin water transfer system is spatially generalized, and the lakes are used as nodes to divide the sections; and the scheduling simulation models of each engineering unit are established respectively; the hydraulic connection between the engineering units of the water transfer system is established according to the scheduling simulation models of each engineering unit, with the goal of minimizing the total operating cost of the pump station of the water transfer system, and a ten-day optimization scheduling model for the inter-basin water transfer system is constructed. The actual water level of the lake is used to provide a deterministic water level calculation boundary for each section, and the ten-day scheduling plan is decided by selecting and switching water sources and routes;

[0006] The tolerable unit water transfer energy consumption threshold is calculated based on the ten-day optimization scheduling model. When the actual unit water transfer energy consumption exceeds the threshold, it is considered that the unit water transfer energy consumption risk occurs. At the same time, the water transfer task risk is considered, and the judgment criteria for the occurrence of water transfer risk are established;

[0007] Based on the evaluation criteria for water diversion risk, the decadal optimization scheduling model is improved, the uncertainty of water inflow is taken into account, the water source inflow sequence of lakes along the water diversion line and the simulated values ​​of the water level sequence of each lake along the water diversion line generated by the decadal water level random simulation model are used to provide the water level calculation boundary, and a cross-basin scheduling risk quantification and optimization decision-making model is constructed;

[0008] Based on the cross-basin scheduling risk quantification and optimization decision-making model, the risk decision-making scheduling plan of the cross-basin water transfer system is obtained, and the risk of the scheduling plan and the sensitivity of key risk factors are evaluated.

[0009] Furthermore, the objective function of the inter-basin water transfer system ten-day optimization scheduling model is:

[0010]

[0011] Among them, E year is the total cost of pump station operation; t is the time period number, T is the total number of time periods; i n is the pump station number, N 0 is the number of pumping stations; For number i n The power consumption of the pumping station in period t;

[0012] The constraints of the model include: total water transfer volume constraint, lake water balance constraint, pump station working capacity constraint, lake storage capacity constraint, pumping control water level constraint, river water transfer capacity constraint, river water level constraint, and river water balance constraint.

[0013] Furthermore, the criteria for judging the occurrence of water diversion risks are:

[0014] Based on the Copula function, a stochastic simulation model of the ten-day water level of the regulating lakes along the water diversion route is established. The simulated values ​​of the lake water level sequence during the scheduling period are simulated, and the values ​​and different total water diversion tasks are input into the ten-day optimization scheduling model of the inter-basin water diversion system. Multiple groups of scheduling processes are simulated to generate multiple groups of ten-day scheduling plans and their total unit water diversion energy consumption simulation values.

[0015] Determine the maximum water transfer capacity of the river and pumping station, and determine the ten-day operation time of each section of the water transfer system according to the ten-day dispatching plan; determine the actual time period water transfer volume of each section in different ten-day dispatching plans based on the operation time and the maximum water transfer capacity;

[0016] Fisher's optimal partitioning method is used to divide the simulated values ​​of different total unit water transfer energy consumption into acceptable areas, tolerable areas and unacceptable areas, and the upper and lower limits of each unit water transfer energy consumption area are calculated. The upper limit of the tolerable area is the tolerable unit water transfer energy consumption threshold.

[0017] When the actual water transfer volume in a period is less than the water transfer task volume in the period, it is deemed that a water transfer task risk has occurred; when the actual unit water transfer energy consumption is greater than the tolerable unit water transfer energy consumption threshold, it is deemed that a unit water transfer energy consumption risk has occurred; if either the water transfer task risk or the unit water transfer energy consumption risk occurs, it is deemed that a water transfer risk has occurred.

[0018] Furthermore, the method for constructing the cross-basin dispatch risk quantification and optimization decision model is as follows: according to the water transfer objectives and influencing conditions, the cross-basin water transfer system is spatially generalized and segmented; according to the dispatch operation rules and laws of lakes, rivers, pumping stations, and gates, the dispatch simulation model of each engineering unit is established; considering the uncertainty of water inflow, the dispatch period is divided into K 0 The n stages are generated by the stochastic simulation model of the ten-day water level. k The water source water level provides the water level calculation boundary for each section, takes the minimum water diversion risk rate of the water diversion system as the objective function, and constructs a cross-basin scheduling risk quantification and optimization decision-making model. The constraints of the model include: total water diversion volume constraint, lake water balance constraint, pumping station working capacity constraint, lake storage capacity constraint, pumping control water level constraint, river water delivery capacity constraint, river water level constraint, and river water balance constraint.

[0019] Furthermore, the solution method of the cross-basin scheduling risk quantification and optimization decision model is: adopt the reverse decision-making process, iteratively simulate the scheduling scenarios of each stage to solve the model, and take the last stage K in the scheduling period as the optimal solution. 0 As the first stage of decision making, the n generated by the stochastic simulation model of the ten-day water level is used. k The water level sequence simulation values ​​of each group of lakes are calculated, and the water diversion risk rate corresponding to each group of water level sequence simulation values ​​is calculated. The water diversion task volume when the water diversion risk rate is the lowest is selected as the stage water diversion volume, and the calculation is carried forward to the previous stage in turn to obtain the water diversion volume of each stage and the corresponding water diversion risk rate and benefit; the total water diversion risk rate Risk of the risk decision scheduling plan w The calculation formula is:

[0020]

[0021] in, For the water transfer system k i The water transfer risk rate in the current stage; P(n k ,W num ,W task ,C num ,C threshold) represents the probability function of water diversion risk; num represents the group number of the lake water level sequence simulation value used in the water level calculation boundary; W num is the actual water transfer volume when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; W task is the total water transfer task; C num is the actual unit water transfer energy consumption when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; C threshold is the tolerable unit water transfer energy consumption threshold.

[0022] Furthermore, the risk assessment method of the scheduling scheme is as follows: different total water transfer tasks, water transfer start times, and first-stage water transfer volumes are set as boundary conditions, and the optimal solution is obtained based on the cross-basin scheduling risk quantification and optimization decision model, generating water transfer costs and water transfer risk rates for different risk decision scheduling schemes, taking water transfer costs as benefits, and obtaining the water transfer risk rate and benefit change process; from the three perspectives of water transfer start time, first-stage water transfer volume, and main water source utilization of different risk decision scheduling schemes, analyze their impact on the relationship between water transfer risk rate and benefits, and provide a basis for weighing and allocating water transfer volumes in each period of the cross-basin water transfer system during scheduling and operation;

[0023] According to the historical scheduling situation, under a given total water diversion task volume, the actual historical scheduling plan is compared and analyzed with the cross-basin scheduling risk quantification and optimization decision-making model to obtain the scheduling risk rate and benefit change process of the risk decision scheduling plan, and analyze the impact of the previous decision on the subsequent process.

[0024] Furthermore, the sensitivity assessment method of key risk factors is as follows: firstly, a certain total water transfer task volume and the simulated values ​​of the water level series of lakes along the route are selected as the benchmark conditions, and the risk rate of the benchmark scheme is obtained by the cross-basin scheduling risk quantification and optimization decision model; then, according to the changes in the water transfer risk rate caused by the changes in each key risk factor, the sensitivity coefficient of each key risk factor is obtained;

[0025] Key risk factors include the total water transfer task, the dry and wet seasons of lake water, and the water level of the regulating lakes. The calculation formula for the sensitivity coefficient is:

[0026]

[0027] Among them, S is the sensitivity coefficient, △Risk w is the percentage change of risk rate, and △F is the percentage change of a key risk factor.

[0028] The system corresponding to the method includes:

[0029] The deca-scale dispatching scheme generation unit is used to spatially generalize the relationship between the engineering units in the inter-basin water transfer system, divide the sections with lakes as nodes, and establish dispatching simulation models for each engineering unit respectively; according to the dispatching simulation models of each engineering unit, the hydraulic connection between the engineering units of the water transfer system is established, with the goal of minimizing the total operating cost of the pump station of the water transfer system, and construct a deca-scale optimization dispatching model for the inter-basin water transfer system, using the actual water level of the lake as the deterministic water level calculation boundary for each section, and through the selection and switching of water sources and routes, the deca-scale dispatching scheme is decided;

[0030] The evaluation standard establishment unit is used to calculate the tolerable unit water transfer energy consumption threshold according to the ten-day optimization scheduling model. When the actual unit water transfer energy consumption exceeds the threshold, it is considered that the unit water transfer energy consumption risk occurs. At the same time, the water transfer task risk is considered, and the evaluation standard for the occurrence of water transfer risk is established;

[0031] The decision model building unit is used to improve the ten-day optimization scheduling model based on the evaluation criteria for water diversion risk, consider the uncertainty of water inflow, provide the water level calculation boundary with the water source inflow sequence of lakes along the water diversion line and the simulated values ​​of the water level sequence of each lake along the water diversion line generated by the ten-day water level random simulation model, and build a cross-basin scheduling risk quantification and optimization decision model;

[0032] The evaluation unit is used to obtain the risk decision-making scheduling plan of the inter-basin water transfer system based on the inter-basin scheduling risk quantification and optimization decision-making model, and to evaluate the scheduling plan risk and sensitivity of key risk factors.

[0033] An electronic device for storing and executing the method, the device comprising:

[0034] A memory storing executable program code;

[0035] a processor coupled to the memory;

[0036] The processor calls the executable program code stored in the memory to execute the steps of the water scheduling risk decision-making method based on the inter-basin water diversion project.

[0037] A computer-readable storage medium for storing and executing the method, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the steps of the risk decision-making method for water scheduling based on inter-basin water diversion projects.

[0038] Beneficial effects: Compared with the prior art, the present invention has the following significant technical effects: (1) It takes into account the uncertainty of water inflow in the water source area, evaluates the water diversion risk rate based on the completion of water diversion tasks and the actual unit water diversion energy consumption, and constructs a scheduling optimization decision model that comprehensively considers cross-basin water volume scheduling optimization and risk value. It can provide a low-risk, optimized cross-basin water volume optimization scheduling plan for practical operation guidance; (2) Based on the risk assessment method of cross-basin scheduling plan and the sensitivity assessment method of key risk factors, it analyzes the impact of key risk factors in the water diversion process, and based on this, it can propose the optimization scheduling plan preference under different water inflow and operating conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a flow chart of the method of the present invention;

[0040] Figure 2 It is a generalized schematic diagram of the water diversion system of the Jiangsu section of the East Route Project of the South-to-North Water Diversion Project in an embodiment of the present invention;

[0041] Figure 3 A risk level classification diagram of unit water transfer energy consumption in an embodiment of the present invention;

[0042] Figure 4 The actual scheduling plan for Jiangshui and Huaishui utilization process in 2018-2019 in the embodiment of the present invention;

[0043] Figure 5 The process of utilizing Jiangshui and Huaishui in the optimized scheduling scheme for 2018-2019 in the embodiment of the present invention;

[0044] Figure 6 This is the changing process of the water transfer risk rate under different water transfer schemes from 2018 to 2019 in the embodiments of the present invention. DETAILED DESCRIPTION

[0045] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and cannot be used to limit the protection scope of the present invention.

[0046] like Figure 1 As shown, the water volume scheduling risk decision-making method for a cross-basin water diversion project described in the present invention specifically includes the following steps:

[0047] (1) Construct a ten-day optimization scheduling model for the inter-basin water transfer system and generate a ten-day scheduling plan based on the ten-day scale.

[0048] (1.1) Based on the water diversion objectives and influencing conditions, the engineering relationship between lakes, rivers, pumping stations and gates in the water diversion system is spatially generalized, and the system is divided into sections with lakes as nodes.

[0049] (1.2) According to the dispatching and operating rules and laws of lakes, rivers, pumping stations and gates, the dispatching simulation models of each engineering unit are established, including the following aspects:

[0050] (1.2.1) Based on the hydraulic characteristics and dispatching rules of the regulating lake, simulate its operation mode, simulate the regulating lake unit, and establish a lake dispatching simulation model.

[0051] (1.2.2) Taking water balance as the basic equation, considering the water exchange between the river and upstream and downstream pumping stations and the water loss of the river section, the river unit simulation is carried out to establish a river scheduling simulation model.

[0052] (1.2.3) Establish a pump station dispatch simulation model:

[0053] (1.2.3.1) The pumping capacity of each pumping station in a certain period of time is calculated based on its average pumping flow in that period of time. The formula is:

[0054]

[0055] in, For number i n The average pumping flow rate of the pumping station during this period; For number i n The total pumping volume of the pumping station in the tth period; △t is the length of the period.

[0056] (1.2.3.2) Pump station operation cost: The power consumption of each pump station is taken as the operation cost of each pump station. The formula is:

[0057]

[0058] in, For number i n The power consumption of the pumping station in period t; For number i n The total pumping capacity of the pumping station in time period t; For number i n The average pumping flow rate of the pump station is Energy consumption per hour of the pumping station.

[0059] (1.2.4) Based on the gate dispatching rules, simulate its operation mode, perform gate unit simulation, and establish a gate dispatching simulation model.

[0060] (1.3) The actual water level of the lake is used as the deterministic water level calculation boundary for each section, and the ten-day dispatching plan is decided by selecting and switching water sources and routes;

[0061] On the premise of completing the total water transfer task within the dispatching period, the hydraulic connection between the engineering units of the water transfer system is established according to the dispatching simulation model of each engineering unit, with the goal of minimizing the total operating cost of the pump station of the water transfer system. The objective function and constraint conditions of the ten-day optimal dispatching model of the inter-basin water transfer system are constructed. The ten-day water transfer volume of the sluice pumping stations at all levels in each period is taken as the decision variable, and the objective function of the ten-day optimal dispatching model of the inter-basin water transfer system is optimally solved based on the constraint conditions of the ten-day optimal dispatching model of the inter-basin water transfer system. The ten-day dispatching plan is generated to obtain the actual water transfer volume and unit water transfer energy consumption of the water transfer system in each period, where the value of the actual unit water transfer energy consumption is equal to the total operating cost E of the pump station. year The objective function of the inter-basin water transfer system decadal optimization scheduling model is:

[0062]

[0063] Among them, E year is the total cost of pump station operation; t is the time period number, T is the total number of time periods; i n is the pump station number, N 0 is the number of pumping stations; For number i n The power consumption of the pumping station in period t.

[0064] (1.4) The constraints of the model include total water transfer volume constraint, lake water balance constraint, pump station working capacity constraint, lake storage capacity constraint, pumping control water level constraint, river water transfer capacity constraint, river water level constraint, and river water balance constraint.

[0065] (1.5) The steps to solve the model are as follows:

[0066] (1.5.1) The scheduling period is divided into T time periods based on a ten-day scale, and the time period is numbered as t; initialize t = 1.

[0067] (1.5.2) Combined with the total water transfer constraint in the model constraint conditions, a certain step size is set within a certain range, and the remaining water transfer at the end of time period t is discretized into N points. The discrete points are numbered as n. 0 , initialize n 0 =1.

[0068] (1.5.3) Combining the deterministic water level prediction series of Lake C with the lake scheduling simulation model, we can deduce the 0 The amount of water W that needs to be pumped into Lake C at the discrete point rl (t,n 0 ).

[0069] (1.5.4) Assume that the amount of water pumped into Lake C is W rl (t,n 0), the proportion of water pumped into Lake C through water diversion line A is a (0≤a≤1), and the proportion of water pumped into Lake C through water diversion line B is 1-a. line Water diversion lines (n line ≥3), the proportion of water flowing through the first water diversion route is a 1 (0≤a 1 ≤1), the proportion of water flowing through the second water diversion line is a 2 (1-a 1 )(0≤a 1 ,a 2 ≤1), and so on, through the nth line The water volume of the water diversion lines accounts for For allocation ratios within the constraints, a certain step size is set to transfer the amount of water W pumped into Lake C. rl (t,n 0 ) is discretized into M points, and the number of the discrete points is m 0 .

[0070] (1.5.5) Combine the river channel dispatch simulation model and the pump station dispatch simulation model to reversely calculate the water volume of other pump stations along the water diversion route, as well as the water volume of the mth pump station. 0 The amount of water outflow W from Lake D (along the water diversion route, the upstream lake of Lake C) drawn from the discrete point ch (t,n 0 ,m 0 ).

[0071] (1.5.6) Combine the deterministic water level prediction sequence of lake D and the water source H river Inflow forecast sequence and lake operation simulation model, derive the 0 The amount of water W that needs to be pumped into Lake D at the discrete point rh (t,n 0 ,m 0 ) and H river Water utilization.

[0072] (1.5.7) Assume that the amount of water pumped into Lake D is W rh (t,n 0 ,m 0 ), the proportion of water pumped into Lake D through Line A is b (0≤b≤1), and the proportion of water pumped into Lake D through Line B is 1-b. line Water diversion lines (n line ≥3), the proportion of water flowing through the first water diversion line is b 1 (0≤b 1 ≤1), the proportion of water flowing through the second water diversion line is b 2 (1-b 1 )(0≤b1 ,b 2 ≤1), and so on, through the nth line The water volume of the water diversion lines accounts for For the allocation ratio within the constraint range, a certain step size is set to transfer the amount of water W pumped into Lake D. rh (t,n 0 ,m 0 ) is discretized into P points, and the number of the discrete points is denoted by p.

[0073] (1.5.8) Combine the river channel dispatch simulation model and the dispatch pump station simulation model to reversely calculate the water volume of other pump stations along the water diversion route, as well as the water volume W that needs to be pumped out of the river channel E (along the water diversion route, the upstream river channel of Lake D) at the pth discrete point. river1 (t,n 0 ,m 0 ,p).

[0074] (1.5.9) Combined with the river dispatch simulation model of river E, the amount of water W that needs to be pumped into river E at the pth discrete point is deduced. river2 (t,n 0 ,m 0 ,p).

[0075] (1.5.10) Assume that the amount of water pumped into river E is W river2 (t,n 0 ,m 0 ,p), the proportion of water pumped into river E through line A is c (0≤c≤1), and the proportion of water pumped into river E through line B is 1-c. line Water diversion lines (n line ≥3), the proportion of water flowing through the first water diversion line is c 1 (0≤c 1 ≤1), the proportion of water flowing through the second water diversion line is c 2 (1-c 1 )(0≤c 1 ,c 2 ≤1), and so on, through the nth line The water volume of the water diversion lines accounts for For the allocation ratio within the constraint range, a certain step size is set to transfer the water volume W into river E. river2 (t,n 0 ,m 0 ,p) is discretized into R points.

[0076] (1.5.11) Combine the river channel dispatch simulation model and the pump station dispatch simulation model to reversely calculate the water volume of other pump stations along the water diversion route, as well as the water volume from the water source C. river The amount of water used.

[0077] (1.5.12) Calculate the above n 0 ×M×P×R discrete points of system cost, take the smallest one for storage.

[0078] (1.5.13) When there are multiple lakes upstream of Lake E along the water diversion route, the above steps (1.5.3)-(1.5.6) can be used to add sections to calculate the amount of water transferred out and into the lakes, the amount of water used to divert water from the lakes, and the amount of water pumped by the pumping stations along the route.

[0079] (1.5.14) If n 0 =N, then go to step (1.5.15); otherwise let n 0 =n 0 +1, return to step (1.5.3).

[0080] (1.5.15) If t = T, then end the operation and output a set of ten-day scheduling plans; otherwise, take the remaining water transfer task volume at the end of period t as the remaining water transfer task volume at period t+1, set t = t+1, and return to step (1.5.2).

[0081] (2) The tolerable unit water transfer energy consumption threshold is calculated based on the ten-day optimization scheduling model. When the actual unit water transfer energy consumption exceeds the threshold, it is considered that a unit water transfer energy consumption risk occurs. At the same time, the risk of water transfer tasks is taken into account, and the judgment criteria for the occurrence of water transfer risks are established.

[0082] (2.1) A ten-day water level random simulation model is established based on the Copula function to simulate different water level sequence simulation values ​​of the regulating lakes during the scheduling period, and input them and different total water transfer task amounts into the ten-day optimization scheduling model of the inter-basin water transfer system to simulate multiple groups of scheduling processes. The dynamic programming method is used to change the deterministic water level prediction sequences in (1.5.3) and (1.5.6) into different water level sequence simulation values ​​for solution according to the model solving steps described in step (1.5). The ten-day water withdrawal of the main rivers and pumping stations during the scheduling period is decided, and multiple groups of ten-day scheduling plans and their total unit water transfer energy consumption simulation values ​​are generated.

[0083] (2.1.1) The algorithm of the stochastic simulation model of the ten-day water level established based on the Copula function includes the following steps:

[0084] (2.1.2) The measured lake water level data series {x t} Fit the marginal distribution function of the water level value in each period to obtain the marginal distribution function F t (x t ), where x t is the lake water level in the tth period; according to the measured lake water level data and the lake water level x in two adjacent periods t and x t-1The marginal distribution function value z t and z t-1 , fitting the Copula joint distribution function of two adjacent time periods, and obtaining x according to the selected Copula function by formula (4) t The conditional distribution function of According to formula (5), the uniformly distributed random number ε t and z t-1 Substitution Get z t , and then we get x t The value of the lake water level sequence is calculated backward in sequence. When solving, given z t The initial value z 0 ∈(0,1), the randomly generated uniformly distributed random number ε 1 Substituting the first equation into equation (5) yields the marginal distribution function value z of the water level in the first period: 1 , put z 1 Substituting into the second equation of (5) we can get the simulated lake water level value x in the first period: 1 ; Similarly, z 1 and a randomly generated uniformly distributed random number ε 2 Substituting into formula (5) we can get the marginal distribution function value z of the water level in the second period: 2 and the simulated lake level x 2 ; Calculate the marginal distribution function value z of each subsequent period in sequence 3 , z 4 , …, z m And its corresponding water level simulation value x 3 , x 4 , …, x m .

[0085] (2.1.3) Water level value x at each time period t The conditional distribution function of is:

[0086]

[0087] Among them, z t and z t-1 x t and x t-1 The marginal distribution function value of t (x t ) and F t-1 (x t-1 ); is the selected Copula function.

[0088] (2.1.4) The formula for calculating the marginal distribution function and the water level simulation value is:

[0089]

[0090] Where t is the time period number, t=1,2,…,m length , m length is the length of the lake water level sequence; ε t is a randomly generated random number that follows a (0,1) uniform distribution in the tth period.

[0091] (2.2) To determine whether the risk of water diversion task occurs, the main steps are as follows:

[0092] (2.2.1) Determine the maximum water delivery capacity of the river and pumping station based on the construction conditions;

[0093] (2.2.2) Determine the ten-day operation time of each section of the water diversion system according to the ten-day dispatching plan; determine the actual water diversion volume of each section in different ten-day dispatching plans based on the operation time and the maximum water transfer capacity;

[0094] (2.2.3) In different ten-day dispatching plans, when the actual water transfer volume in a period is less than the water transfer task volume in the period, it is considered that a water transfer task risk occurs.

[0095] (2.3) To determine whether the unit water transfer energy consumption risk occurs, the main steps are as follows:

[0096] (2.3.1) Using the Fisher optimal partitioning method, the different total unit water transfer energy consumption simulation values ​​generated in step (2.1) are divided into acceptable areas, tolerable areas, and unacceptable areas, and the upper and lower limits of the unit water transfer energy consumption corresponding to each area are calculated (see Appendix Figure 3 ), the upper limit of the tolerable zone is the tolerable unit water transfer energy consumption threshold;

[0097] (2.3.2) Fisher's optimal segmentation method includes the following steps:

[0098] (2.3.3) Suppose there are n samples arranged in a certain order to form a sequence {x n}, each sample is measured with m indicators, and the sample sequence {x n} is divided into k categories: where i 1 ,i 2 ,…,i k is the split point, whose subscript satisfies 1=i 1 2 <… k ≤i k+1 -1=n; use the intra-segment class diameter to measure the degree of difference between samples within a class, assuming that class P={x i ,x i+1 ,x i+2 ,…,x j ​​}(i, j are sample numbers, j>i), the intra-segment class diameter of this class is recorded as D(i,j), and the mean is The smaller the intra-segment class diameter is, the smaller the difference between samples within the class is. The classification loss function e[P(n,k)] is calculated to find a set of segmentation points that minimize the e[P(n,k)] value. The corresponding segmentation is the optimal segmentation. The rationality of the optimal segmentation is tested by the F test method.

[0099] (2.3.4) According to the sample eigenvalues, the relationship matrix X can be constructed as follows:

[0100]

[0101] Among them, x nm Indicates the value of the mth indicator of the nth sample.

[0102] (2.3.5) The calculation formula for class diameter and eigenvalue mean is:

[0103]

[0104] Among them, D(i,j) is the class {x i ,x i+1 ,x i+2 ,…,x j}'s intra-segment class diameter; For the rth 0 (i≤r 0 ≤j) sample characteristic value of the sample; Represents the mean of the eigenvalues ​​from the i-th sample to the j-th sample.

[0105] (2.3.6) The calculation formula of the classification loss function is:

[0106]

[0107] Among them, D(i r ,i r+1 -1) for class The diameter of the class within the segment; r is the class number (r=1~k).

[0108] (2.3.7) The recursive formula for optimal segmentation is:

[0109]

[0110] where e[P(i-1,k-1)] is the loss function corresponding to the optimal segmentation of i-1 samples into k-1 classes; D(i,n) is the loss function of class {x i ,x i+1 ,x i+2 ,…,x n} of the intra-segment class diameter.

[0111] (2.3.8) The F test formula is:

[0112]

[0113] Among them, n r is the number of samples in the r-th sample sequence; is the sample mean of the r-th sample sequence; is the mean of all samples; is the inter-segment class diameter; s is the sample number in the r-th class sample sequence; n rs is the value of the sth sample in the rth class sample sequence.

[0114] (2.3.9) In different ten-day dispatching plans, when the actual unit water transfer energy consumption exceeds the tolerable unit water transfer energy consumption threshold, it is considered that a unit water transfer energy consumption risk occurs.

[0115] (2.4) If either the water transfer task risk or the unit water transfer energy consumption risk occurs, it is considered as the occurrence of water transfer risk. The frequency of water transfer risk in different ten-day dispatching plans is counted as the probability value, and the water transfer risk rate is obtained. The calculation formula is:

[0116]

[0117] in, For the water transfer system k i The water transfer risk rate in the current stage; P(n k ,W num ,W task ,C num ,C threshold ) represents the probability function of water diversion risk; num represents the group number of the lake water level sequence simulation value used in the water level calculation boundary; W num is the actual water transfer volume when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; W task is the total water transfer task; C num is the actual unit water transfer energy consumption when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; C threshold is the tolerable unit water transfer energy consumption threshold.

[0118] (3) Based on the established criteria for judging the occurrence of water diversion risks, the ten-day optimization scheduling model is improved, and then a cross-basin scheduling risk quantification and optimization decision-making model is constructed.

[0119] On the basis of the inter-basin water transfer system's ten-day optimization scheduling model, considering the uncertainty of water inflow, the water source inflow sequence of lakes along the water transfer line and the simulated values ​​of the water level sequence of each lake along the water transfer line generated by the ten-day water level random simulation model in step (2.1) provide the water level calculation boundary, and construct an inter-basin scheduling risk quantification and optimization decision model. By measuring the water transfer risk rate caused by uncertainty and coordinating the contradiction between economic benefits and risks, under the premise of ensuring the safe operation of the water transfer system, while completing the total water transfer task, the water transfer cost can be effectively reduced. The main steps are as follows:

[0120] (3.1) According to the water transfer objectives and influencing conditions, the water transfer system is spatially generalized and divided into sections, the same as step (1.1);

[0121] (3.2) According to the dispatching and operating rules and laws of lakes, rivers, pumping stations and gates, establish dispatching simulation models for each engineering unit respectively, the same as step (1.2);

[0122] (3.3) Considering the uncertainty of water inflow, the dispatch period is divided into K 0 The water source sequence of the lakes along the water diversion route and the n generated by the stochastic simulation model of the ten-day water level in step (2.1) are used as the basis for the k The simulated values ​​of the water level series of each lake along the water diversion line provide the water level calculation boundary for each section, with the objective function of minimizing the water diversion risk rate of the water diversion system. The constraints are the same as (1.4). A risk quantification and optimization decision-making model for cross-basin scheduling is constructed. Through the selection and switching of water sources and routes, the risk decision scheduling plan of the cross-basin water diversion system at the ten-day scale is decided, including the water diversion volume of each level of sluice and pumping station in the period, water diversion risk rate and benefit calculation.

[0123] (3.4) When solving the cross-basin dispatch risk quantification and optimization decision model, the dispatch period is divided into K 0 The model is solved by iteratively simulating the scheduling scenarios of each stage using the reverse decision-making process. 0 As the first stage of decision making, the random simulation model of water level is used to generate n k The water level sequence simulation values ​​of each group of lakes are calculated, and the water diversion risk rate corresponding to each group of water level sequence simulation values ​​is calculated. The water diversion task volume when the water diversion risk rate is the lowest is selected as the stage water diversion volume, and then the calculation is made to the previous stage in turn to obtain the water diversion volume of each stage and the corresponding water diversion risk rate and benefit.

[0124] In this embodiment, the Kth 0 The last stage of the scheduling period (late March to late May) is taken as the first stage of calculation and is calculated in sequence. The specific steps are as follows:

[0125] (3.4.1) Determine the kth iThe water transfer task volume W in the stage (late March to late May) task,4 (W min <W task,4 <W max , W min is the minimum water transfer task requirement, W max is the maximum water transfer volume, which is affected by the water transfer capacity of the pumping station. First, the random simulation model of the water level in ten days is used to generate n k Group k i The simulated value of the lake water level sequence at the kth stage is calculated according to the water diversion risk rate quantification method described in step (2.4). i The water diversion risk rate corresponding to each stage of the water level sequence simulation value is selected, and the water diversion task with the lowest stage water diversion risk rate is selected as W for this stage. task,4 .

[0126] (3.4.2) Determine the kth 0 -1 stage (late March to late May) water transfer task volume W task,3 , generate n k Group (k i -1)-k i The simulated values ​​of the lake water level series in the stage are used to calculate W task,3 The risk rate of stage water diversion under each group of water level series simulation values.

[0127] (3.4.3) Determine (k i -2) stage to (k i -1) stage, until the lowest stage water transfer risk rate of the first stage is determined, using the same method as step (3.4.2).

[0128] (3.4.4) Calculate the total water diversion risk rate Risk of the risk decision scheduling plan w , and its calculation formula is:

[0129]

[0130] (4) Evaluate the risk rate and sensitivity of key risk factors of cross-basin risk decision-making scheduling plans.

[0131] (4.1) Set different total water transfer tasks, water transfer start time, and first-stage water transfer volume as boundary conditions, obtain the optimal solution based on the cross-basin scheduling risk quantification and optimization decision model, generate water transfer costs and water transfer risk rates for different risk decision scheduling plans, consider water transfer costs as benefits, and obtain the change process of water transfer risk rate and benefits; analyze their impact on the relationship between water transfer risk rate and benefits from three perspectives: water transfer start time, first-stage water transfer volume, and main water source utilization of different risk decision scheduling plans, and provide a basis for weighing and allocating water transfer volumes in different time periods during scheduling and operation of the cross-basin water transfer system. The specific steps are as follows:

[0132] (4.1.1) Calculate the water diversion risk rate by time period. Divide the scheduling period into multiple time periods. Assume that the water diversion starts in the first time period. According to the total water diversion task volume, input the n generated by random simulation. k After the lake water level sequence simulation value is set, the water diversion risk rate at this time is calculated; the water diversion task volume for the next period is updated, and its value is equal to the total water diversion task volume minus the total water diversion volume before this period, and then the n generated by random simulation is input. k The lake water level sequence is formed and the water diversion risk rate at that time is calculated; the risk of each subsequent period is calculated in turn.

[0133] (4.1.2) Taking different total water transfer task volumes as boundary conditions, analyze the impact of water transfer start time in different time periods on water transfer risk rate;

[0134] (4.1.3) Using different first-stage water transfer volumes as boundary conditions, analyze and compare the water transfer risk rates corresponding to different water transfer start times, and analyze the impact of the first-stage water transfer volume on the water transfer risk rate;

[0135] (4.1.4) During the dispatching process, due to the existence of multiple water sources, under the same total water transfer task volume, there are differences in the utilization of the main water sources in different dispatching schemes. Based on the different selected main water source utilization, a comparative analysis is conducted on the impact of different water source utilization on the water transfer risk rate.

[0136] (4.2) Based on the historical scheduling situation, under a given total water diversion task volume, the historical actual scheduling plan is compared and analyzed with the cross-basin scheduling risk quantification and optimization decision-making model to obtain the scheduling risk rate and benefit change process of the risk decision scheduling plan, and analyze the impact of the previous decision on the subsequent process.

[0137] Among them, the water transfer risk rate of the historical actual scheduling scheme is calculated based on the actual water transfer process of the project every ten days and the simulated values ​​of different lake water level sequences generated based on the Copula function, and is generated by the simulation scheme generated by the inter-basin water transfer system ten-day optimization scheduling model. The actual water transfer volume and total water transfer task volume in the historical actual scheduling scheme are fixed values, and the tolerable unit water transfer energy consumption threshold is consistent with that in the risk decision scheduling scheme. The water transfer risk rate of the historical actual scheduling scheme is calculated based on the different actual unit water transfer energy consumption statistics under different lake water level sequence simulation values ​​by formula (12) and formula (13).

[0138] (4.3) The sensitivity assessment method of key risk factors is as follows: First, a certain total water transfer task volume and the simulated values ​​of the water level series of lakes along the route are selected as the benchmark conditions, and the risk rate of the benchmark scheme is obtained by the cross-basin scheduling risk quantification and optimization decision model. Then, according to the changes in the water transfer risk rate caused by the changes in each key risk factor, the sensitivity coefficient of each key risk factor is obtained.

[0139] (4.3.1) Key risk factors include the total water transfer task, the dry and wet seasons of lake water inflow, and the water level control of regulated lakes.

[0140] (4.3.2) The calculation formula of the sensitivity coefficient is:

[0141]

[0142] Among them, S is the sensitivity coefficient, △Risk w is the percentage of risk change, and △F is the percentage of change of a key risk factor.

[0143] Example verification:

[0144] The embodiment of the present invention is specifically described by taking the dispatching of the Jiangsu section of the first phase of the East Route of the South-to-North Water Diversion Project.

[0145] The Jiangsu section of the first phase of the East Route of the South-to-North Water Diversion Project uses the Jiangsu Province Jiangshuibei Project to expand its scale and extend northward. Among them, the Jiangsu section of the East Route Project is based on the original Beijing-Hangzhou Grand Canal as the main water transmission line, through the construction, expansion, reinforcement and transformation of pump stations, forming a dual-line water transmission pattern in Jiangsu. The project uses the Yangtze River and Huaihe River as the main water sources, and there are regulating lakes such as Hongze Lake and Luoma Lake along the route. The Jiangsu section of the East Route Project spans multiple river basins such as the Jianghuai, Yishu and Si, and is a giant inter-basin water diversion project with a beneficiary population of over 100 million. It is responsible for transmitting water to Shandong Province and meeting the water demand of the receiving areas along the route in Jiangsu. The specific steps of the scheduling risk identification and optimization decision-making method of the Jiangsu section of the first phase of the East Route of the South-to-North Water Diversion Project are as follows:

[0146] (1) Establish a ten-day optimization dispatching model for the Jiangsu section of the first phase of the South-to-North Water Diversion Project, and generate dispatching plans based on the ten-day scale, such as Figure 2, the engineering relationship between lakes, rivers, pumping stations and gates in the Jiangsu section of the first phase of the East Route of the South-to-North Water Diversion Project was generalized. Taking Hongze Lake and Luoma Lake as nodes, the water diversion project was divided into three sections: Yangtze River-Hongze Lake, Hongze Lake-Luoma Lake, and Luoma Lake to the section out of the province. Each section includes two water transmission trunk lines, the Yunxi Line and the Grand Canal Line. The water transmission line in each section is further divided into several rivers by three cascade pumping stations. According to the dispatching and operating rules and laws of lakes, rivers, pumping stations and gates, the dispatching simulation models of each engineering unit were established respectively. The objective function of the model is to minimize the operating cost of the pumping station. The total water diversion task, lake water balance, pumping station working capacity, lake storage capacity, pumping control water level, river water transmission capacity, river water level, and river water balance are used as model constraints. The real-time water levels of Hongze Lake and Luoma Lake are used to provide water level calculation boundaries for each section, and the water source and route are selected for switching, and the scheduling plan is decided on a ten-day scale to obtain the water transfer volume in each period and the actual unit water transfer energy consumption.

[0147] (2) The tolerable unit water transfer energy consumption threshold is calculated based on the ten-day optimization scheduling model. When the actual unit water transfer energy consumption exceeds the threshold, it is considered that a unit water transfer energy consumption risk occurs. At the same time, the risk of water transfer tasks is taken into account, and the judgment criteria for the occurrence of water transfer risks are established.

[0148] The 20-year average water level data from 2000 to 2020 were selected, and a random simulation model of the 10-day water level was established based on the Copula function to simulate the 10-day water level series of Hongze Lake and Luoma Lake. The RMSE values ​​of the mean, variance and coefficient of variation of the historical water level and the simulated water level were compared. When the simulation effect of the water level series is good, it can be used as the water level input of the cross-basin scheduling risk quantification and optimization decision-making model.

[0149] The different water level sequence simulation values ​​of Hongze Lake and Luoma Lake and the different total water transfer tasks (W task =703, 844, 884 million m 3 ), input the inter-basin water transfer system ten-day optimization scheduling model, and run the simulation to obtain 300 sets of ten-day scheduling plans.

[0150] According to the working conditions, determine the maximum water transfer capacity of the river and pump station; determine the operation time of each section of the water transfer system according to the 300-day scheduling plan; and determine the actual water transfer volume of each section in the 300-day scheduling plan based on the operation time and the maximum water transfer capacity. When the actual water transfer volume is less than the water transfer task volume, it is considered that the water transfer task risk occurs.

[0151] The frequency analysis of 300 groups of dispatch results was carried out, and the Fisher optimal segmentation method was used to divide the unit water transfer energy consumption simulation value into acceptable area, tolerable area and unacceptable area. The upper and lower limits of each area of ​​unit water transfer energy consumption were obtained: the acceptable area (0.0467 kWh / m 3 ,0.0603kWh / m3 ], Tolerable zone (0.0603kWh / m 3 ,0.1015kWh / m 3 ) and unacceptable area [0.1015kWh / m 3 ,0.1126kWh / m 3 ). When the actual unit water transfer energy consumption is greater than 0.1015kWh / m 3 When the risk of unit water transfer energy consumption occurs, it is deemed that the risk of unit water transfer energy consumption occurs.

[0152] (3) Construct a risk quantification and optimization decision-making model for the dispatching of the Jiangsu section of the East Route of the South-to-North Water Diversion Project. According to the water diversion objectives and influencing conditions, the Jiangsu section of the East Route of the South-to-North Water Diversion Project is generalized and divided into sections. According to the dispatching operation rules and laws of lakes, rivers, pumping stations, and gates along the route, a dispatching simulation model for each engineering unit is established. The method is the same as the ten-day optimization dispatching model for the Jiangsu section of the East Route of the South-to-North Water Diversion Project. Considering the uncertainty of water inflow, the dispatching period is divided into K 0 In this stage, 300 sets of lake water level sequence simulation values ​​are generated to provide water level calculation boundaries for each section. The total water diversion task volume, lake water balance, pumping station working capacity, lake storage capacity, pumping control water level, river water delivery capacity, river water level and river water balance are used as model constraints to construct a cross-basin scheduling risk quantification and optimization decision-making model, decide on the system's ten-day scheduling plan, and calculate the water diversion risk rate and benefits.

[0153] The objective function of the cross-basin scheduling risk quantification and optimization decision-making model is the above formula (14).

[0154] (4) Assess the risks of cross-basin dispatching schemes, the main contents are as follows:

[0155] Different total water transfer tasks are used as boundary conditions. The Jiangsu section of the first phase of the South-to-North Water Diversion Project usually starts water transfer in early December. When the water conditions are good in November, pre-water transfer will be carried out in November. Therefore, the start time of water transfer is divided into three stages: early November to late November; early December to late January; early February to early March, and the impact of water transfer start time at different stages on water transfer risk rate is analyzed.

[0156] The water transfer volume in the first stage (early November to late November) is taken as the initial water transfer volume. Different initial water transfer volumes are set as boundary conditions. The corresponding water transfer risk rates at different start times are compared, and the impact of the initial water transfer volume on the water transfer risk rate is analyzed.

[0157] Two scheduling schemes are set with a specific total water transfer task as the input condition. The water sources for the Jiangsu section of the first phase of the South-to-North Water Diversion Project include the Yangtze River and the Huaihe River (referred to as the Yangtze River and the Huaihe River). Therefore, Scheme 1 is mainly based on the Yangtze River water, and Scheme 2 is mainly based on the Huaihe River water. The impact of the Yangtze River and Huaihe River water utilization on the water diversion risk rate is compared.

[0158] Taking the water transfer in 2018-2019 as an example, the total water transfer task volume is 844 million m 3 As the input condition, the cross-basin dispatch risk is quantified and the decision-making model is optimized to obtain the risk decision dispatch plan (see Appendix Figure 4 ) and the actual scheduling plan (Appendix Figure 5 ) to compare and analyze the dynamic change process of water diversion risk rate (Appendix Figure 6 ), and the impact of early water transfer decisions on subsequent processes.

[0159] (5) Evaluate the sensitivity of key risk factors and propose scheduling scheme preferences under different water inflow and operating conditions. Set the key risk factors as the total water transfer task, the water level of Hongze Lake and Luoma Lake, and the controlled water level of Luoma Lake. Determine the parameter values ​​corresponding to the sensitivity analysis benchmark scheme: Total water transfer task W task =884 million m 3 The benchmark for lake water inflow is the result of statistical analysis from 2000 to 2020, and the controlled water level of Luomahu Lake is 23.0m. The water diversion risk rate corresponding to the benchmark scheme is calculated, among which the start time of the first stage is selected as early November, the start time of the second stage is selected as early December, and the start time of the third stage is selected as early March. Given the change percentage of the four key risk factors of total water diversion task volume, water inflow in Hongze Lake, water inflow in Luomahu Lake, and controlled water level of Luomahu Lake, the water diversion risk rate and sensitivity coefficient under different scheduling conditions caused by changes in key risk factors are calculated, thereby establishing a typical scheduling scenario and operating condition set, and proposing scheduling scheme preferences under different water inflow and operating conditions.

[0160] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A risk decision-making method for water scheduling of inter-basin water diversion projects, characterized in that: The following steps are involved: The relationship between the engineering units in the inter-basin water transfer system is spatially generalized, and the lakes are used as nodes to divide the sections; and the scheduling simulation models of each engineering unit are established respectively; the hydraulic connection between the engineering units of the water transfer system is established according to the scheduling simulation models of each engineering unit, with the goal of minimizing the total operating cost of the pump station of the water transfer system, and a ten-day optimization scheduling model for the inter-basin water transfer system is constructed. The actual water level of the lake is used to provide a deterministic water level calculation boundary for each section, and the ten-day scheduling plan is decided by selecting and switching water sources and routes; The tolerable unit water transfer energy consumption threshold is calculated based on the ten-day optimization scheduling model. When the unit water transfer energy consumption exceeds the threshold, it is considered that the unit water transfer energy consumption risk occurs. At the same time, the water transfer task risk is considered, and the judgment criteria for the occurrence of water transfer risk are established; Based on the evaluation criteria for water diversion risk, the decadal optimization scheduling model is improved, the uncertainty of water inflow is taken into account, the water source inflow sequence of lakes along the water diversion line and the simulated values ​​of the water level sequence of each lake along the water diversion line generated by the decadal water level random simulation model are used to provide the water level calculation boundary, and a cross-basin scheduling risk quantification and optimization decision-making model is constructed; Based on the cross-basin scheduling risk quantification and optimization decision-making model, the risk decision-making scheduling plan of the cross-basin water transfer system is obtained, and the risk of the scheduling plan and the sensitivity of key risk factors are evaluated.

2. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The objective function of the inter-basin water transfer system ten-day optimization scheduling model is: Among them, E year is the total cost of pump station operation; t is the time period number, T is the total number of time periods; i n is the pump station number, N0 is the number of pump stations; For number i n The power consumption of the pumping station in period t; The constraints of the model include: total water transfer volume constraint, lake water balance constraint, pump station working capacity constraint, lake storage capacity constraint, pumping control water level constraint, river water transfer capacity constraint, river water level constraint, and river water balance constraint.

3. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The criteria for judging the occurrence of water diversion risks are: Based on the Copula function, a stochastic simulation model of the ten-day water level of the regulating lakes along the water diversion route is established. The simulated values ​​of the lake water level sequence during the scheduling period are simulated, and the values ​​and different total water diversion tasks are input into the ten-day optimization scheduling model of the inter-basin water diversion system. Multiple groups of scheduling processes are simulated to generate multiple groups of ten-day scheduling plans and their total unit water diversion energy consumption simulation values. Determine the maximum water transfer capacity of the river and pumping station, and determine the ten-day operation time of each section of the water transfer system according to the ten-day dispatching plan; determine the actual time period water transfer volume of each section in different ten-day dispatching plans based on the operation time and the maximum water transfer capacity; Fisher's optimal partitioning method is used to divide the simulated values ​​of different total unit water transfer energy consumption into acceptable areas, tolerable areas and unacceptable areas, and the upper and lower limits of each unit water transfer energy consumption area are calculated. The upper limit of the tolerable area is the tolerable unit water transfer energy consumption threshold. When the actual water transfer volume in a period is less than the water transfer task volume in the period, it is deemed that a water transfer task risk has occurred; when the actual unit water transfer energy consumption is greater than the tolerable unit water transfer energy consumption threshold, it is deemed that a unit water transfer energy consumption risk has occurred; if either the water transfer task risk or the unit water transfer energy consumption risk occurs, it is deemed that a water transfer risk has occurred.

4. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The method for constructing the cross-basin dispatching risk quantification and optimization decision model is as follows: according to the water diversion objectives and influencing conditions, the cross-basin water diversion system is spatially generalized and segmented; according to the dispatching operation rules and laws of lakes, rivers, pumping stations, and gates, the dispatching simulation model of each engineering unit is established respectively; considering the uncertainty of water inflow, the dispatching period is divided into K0 stages, and the n stages generated by the ten-day water level random simulation model are used. k The water source water level provides the water level calculation boundary for each section, takes the minimum water diversion risk rate of the water diversion system as the objective function, and constructs a cross-basin scheduling risk quantification and optimization decision-making model. The constraints of the model include: total water diversion volume constraint, lake water balance constraint, pumping station working capacity constraint, lake storage capacity constraint, pumping control water level constraint, river water delivery capacity constraint, river water level constraint, and river water balance constraint.

5. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The solution method of the cross-basin scheduling risk quantification and optimization decision model is as follows: adopt the reverse decision-making process, iteratively simulate the scheduling scenarios of each stage to solve the model, take the last stage K0 in the scheduling period as the first stage of decision-making, and use the n generated by the ten-day water level random simulation model. k The water level sequence simulation values ​​of each group of lakes are calculated, and the water diversion risk rate corresponding to each group of water level sequence simulation values ​​is calculated. The water diversion task volume when the water diversion risk rate is the lowest is selected as the stage water diversion volume, and the calculation is carried forward to the previous stage in turn to obtain the water diversion volume of each stage and the corresponding water diversion risk rate and benefit; the total water diversion risk rate Risk of the risk decision scheduling plan w The calculation formula is: in, For the water transfer system k i The water transfer risk rate in the current stage; P(n k ,W num ,W task ,C num ,C threshold ) represents the probability function of water diversion risk; num represents the group number of the lake water level sequence simulation value used in the water level calculation boundary; W num is the actual water transfer volume when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; W task is the total water transfer task; C num is the actual unit water transfer energy consumption when the simulated value of the lake water level sequence of group num is used as the water level calculation boundary; C threshold is the tolerable unit water transfer energy consumption threshold.

6. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The risk assessment method for the scheduling scheme is as follows: different total water transfer tasks, water transfer start times, and first-stage water transfer volumes are set as boundary conditions, and the optimal solution is obtained based on the cross-basin scheduling risk quantification and optimization decision-making model, generating water transfer costs and water transfer risk rates for different risk decision scheduling schemes, taking water transfer costs as benefits, and obtaining the water transfer risk rate and benefit change process; from the three perspectives of water transfer start time, first-stage water transfer volume, and main water source utilization of different risk decision scheduling schemes, analyze their impact on the relationship between water transfer risk rate and benefits, and provide a basis for weighing and allocating water transfer volumes in each period of the cross-basin water transfer system during scheduling and operation; According to the historical scheduling situation, under a given total water diversion task volume, the actual historical scheduling plan is compared and analyzed with the cross-basin scheduling risk quantification and optimization decision-making model to obtain the scheduling risk rate and benefit change process of the risk decision scheduling plan, and analyze the impact of the previous decision on the subsequent process.

7. The water volume dispatch risk decision-making method for inter-basin water diversion projects according to claim 1 is characterized in that: The sensitivity assessment method of key risk factors is as follows: firstly, a certain total water transfer task volume and the simulated values ​​of the water level series of lakes along the route are selected as the benchmark conditions, and the risk rate of the benchmark scheme is obtained by the cross-basin scheduling risk quantification and optimization decision model; then, according to the changes in the water transfer risk rate caused by the changes in each key risk factor, the sensitivity coefficient of each key risk factor is obtained; Key risk factors include the total water transfer task, the dry and wet seasons of lake water, and the water level of the regulating lakes. The calculation formula for the sensitivity coefficient is: Among them, S is the sensitivity coefficient, △Risk w is the percentage change of risk rate, and △F is the percentage change of a key risk factor.

8. A water dispatch risk decision-making system based on inter-basin water diversion projects, characterized in that: include: The deca-scale dispatching scheme generation unit is used to spatially generalize the relationship between the engineering units in the inter-basin water transfer system, divide the sections with lakes as nodes, and establish dispatching simulation models for each engineering unit respectively; according to the dispatching simulation models of each engineering unit, the hydraulic connection between the engineering units of the water transfer system is established, with the goal of minimizing the total operating cost of the pump station of the water transfer system, and construct a deca-scale optimization dispatching model for the inter-basin water transfer system, using the actual water level of the lake as the deterministic water level calculation boundary for each section, and through the selection and switching of water sources and routes, the deca-scale dispatching scheme is decided; The evaluation standard establishment unit is used to calculate the tolerable unit water transfer energy consumption threshold according to the ten-day optimization scheduling model. When the actual unit water transfer energy consumption exceeds the threshold, it is considered that the unit water transfer energy consumption risk occurs. At the same time, the water transfer task risk is considered, and the evaluation standard for the occurrence of water transfer risk is established; The decision model building unit is used to improve the ten-day optimization scheduling model based on the evaluation criteria for water diversion risk, consider the uncertainty of water inflow, provide the water level calculation boundary with the water source inflow sequence of lakes along the water diversion line and the simulated values ​​of the water level sequence of each lake along the water diversion line generated by the ten-day water level random simulation model, and build a cross-basin scheduling risk quantification and optimization decision model; The evaluation unit is used to obtain the risk decision-making scheduling plan of the inter-basin water transfer system based on the inter-basin scheduling risk quantification and optimization decision-making model, and to evaluate the scheduling plan risk and sensitivity of key risk factors.

9. An electronic device, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps of the water scheduling risk decision-making method based on the inter-basin water diversion project 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 computer instructions, which, when called, are used to execute the steps of the water scheduling risk decision-making method based on the inter-basin water diversion project as described in any one of claims 1-7.

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