Cascade reservoir flood resource optimal utilization method and system

Abstract

The present application relates to water resource utilization technical field, disclose a kind of cascade reservoir flood resource optimization utilization method, comprising the following steps: constructing the objective function and constraint condition of cascade reservoir flood resource optimization utilization;Setting calculation parameter;With cascade reservoir flood limit water level as initial trajectory, obtain the initial trajectory of each reservoir each stage satisfying each constraint condition, form trajectory library;Execute routine DDDP algorithm iteration, the current optimal trajectory of each iteration is stored and updated in trajectory library;Continue iteration, trace back the trajectory of previous generation and previous two generations, execute the operation of convergence and divergence, and optimize the trajectory multiple times until the calculation is completed, output final trajectory.The present application also discloses a kind of cascade reservoir flood resource optimization utilization system.The cascade reservoir flood resource optimization utilization method and system of the present application introduce the characteristics of divergence or shrinkage with the number of iterations of convergence and divergence mechanism, have strong global search ability and stable local search precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water resource utilization, in particular to a method and system for optimizing utilization of flood resources of cascade reservoirs. BACKGROUND

[0002] After years of water conservancy construction, improvement of hydrological and meteorological prediction and forecasting level, and accumulation of flood control and drought resistance experience, human ability to control flood is continuously enhanced, and understanding of flood is gradually changed from passive defense to proper utilization while defense. Flood resource utilization has become a very potential water resource utilization method, and the demand for fine utilization of flood resources of cascade reservoirs in flood season is increasingly strong. Therefore, under the premise of ensuring the safety of reservoirs and upstream and downstream flood control, starting from the concept of flood resource utilization, optimizing utilization of flood resources of cascade reservoirs in flood season has important practical significance for improving power generation benefit of reservoir groups, reducing flood season water abandonment and power output obstruction, and improving flood season water resource utilization efficiency.

[0003] However, most of the dispatching rules or dispatching schemes for optimizing utilization of flood resources of cascade reservoirs are based on long series of inflow characteristics. Under the premise of ensuring flood control safety, the operating water level control range of flood resource utilization of cascade reservoirs or even the overall floating space of cascade reservoirs is explicitly proposed, but how to implement the optimization of flood resource utilization within this control range and utilization space to improve the comprehensive benefit of flood resource utilization of cascade reservoirs in flood season is still lacking of powerful calculation method.

[0004] From a mathematical point of view, the optimization of flood resources of cascade reservoirs is essentially a complex optimization problem of multi-reservoir and multi-stage water level control, involving multiple complex constraints. When the scale of reservoir groups and calculation stages increases, the calculation scale increases exponentially, and the optimal solution is difficult to obtain. The discrete differential dynamic programming method (DDDP) is an improved method of dynamic programming method (DP). Since DDDP only selects part of the discrete points for optimization, it avoids the problem of falling into dimension disaster caused by DP in the feasible region. However, DDDP also needs to combine all the different discrete states of all reservoirs in each stage, and research shows that it also has defects such as poor search ability and premature convergence. Therefore, when using DDDP to solve the problem of optimizing utilization of flood resources of cascade reservoirs, the calculation mechanism of full combination of discrete states needs to be effectively improved to effectively improve the global development and local exploration ability. SUMMARY

[0005] The purpose of the present application is to overcome the above technical deficiencies, and to provide a method and system for optimizing utilization of flood resources of cascade reservoirs, which introduces the characteristics of divergence or contraction with the number of iterations, and has strong global search ability and stable local search precision.

[0006] In order to achieve the above-mentioned purpose, the cascade reservoir flood resource optimal utilization method designed by the application comprises the following steps:

[0007] 1) Collecting the basic data of cascade reservoir flood resource utilization, constructing the objective function and constraint condition of cascade reservoir flood resource optimal utilization according to the cascade reservoir regulation rules;

[0008] 2) Setting the calculation parameters;

[0009] 3) Taking the flood limit water level of the cascade reservoir as the initial trajectory, obtaining the initial trajectory of each reservoir in each stage that meets the constraint condition, and forming a trajectory library;

[0010] 4) Executing the iteration of the conventional DDDP algorithm, forming a search corridor in the feasible range of the current trajectory library, seeking the current optimal trajectory in the search corridor by using the conventional dynamic programming method, and storing and updating the current optimal trajectory of each iteration into the trajectory library;

[0011] 5) Continuing the iteration, tracing back the trajectories of the previous generation and the previous two generations on the basis of the current trajectory, performing the convergence and divergence optimization update operation, and optimizing the trajectory multiple times until the calculation is completed, outputting the final trajectory, and obtaining the optimal effect of cascade reservoir flood resource utilization.

[0012] Preferably, in the step 2), the calculation parameters comprise the number of reservoirs N, the total number of regulation period stages T, the maximum iteration number M, and the maximum convergence and divergence optimization calculation number K.

[0013] Preferably, in the step 3), the initial trajectory of the cascade reservoir flood limit water level is obtained, and the initial trajectory of each reservoir in each stage that meets the constraint condition is obtained. The trajectory library is formed Wherein represents the initial trajectory of the reservoir i in the stage j, that is, the water level value of the reservoir i in the stage j, and Ω0=Z 0 .

[0014] Preferably, in the step 4), the iteration of the conventional DDDP algorithm is executed Y times, 2≤Y≤M, a search corridor is formed in the feasible range of the current trajectory library, the current optimal trajectory is sought in the search corridor by using the conventional dynamic programming method , and the current optimal trajectory of each iteration is stored and updated into the trajectory library

[0015] Preferably, in the step 5), the following steps are included:

[0016] 51) Setting the iteration number m=Y+1;

[0017] 52) Setting the stage number j=1;

[0018] 53) Setting the current trajectory of each reservoir in the current stage

[0019] 54) Perform the collection and optimization calculation operation:

[0020] 54.1) Initialize the collection and optimization calculation number k = 1;

[0021] 54.2) Read the previous generation trajectory Ω m-1 and the second generation trajectory Ω m-2 from the trajectory library ;

[0022] 54.3) Based on the current trajectory , combine the previous generation trajectory of each reservoir at the current stage and the second generation trajectory of each reservoir at the current stage to perform the collection and optimization calculation operation, and calculate the new trajectory of the current trajectory of each reservoir at the current stage. The calculation formula is as follows:

[0023]

[0024] In the formula, λ is a random number with a value of 0 or 1, realizing the processing of subtraction and addition of the information of and , S is the collection and optimization calculation factor, and its calculation formula is as follows:

[0025]

[0026] In the formula, p is a random number between -2.8 and 2.8, and r is a random number between 0 and 1;

[0027] 54.4) Compare the new trajectory and the current trajectory . If is better than , then , otherwise, no processing is performed;

[0028] 54.5) Let k = k + 1, if k ≤ K, go to step 54.3), otherwise, go to step 55);

[0029] 55) Let j = j + 1, if j > T, go to step 56), otherwise, go to step 53) to continue the iteration operation;

[0030] 56) Let m = m + 1, if m > M, go to step 57); otherwise, go to step 52) to continue the iteration operation;

[0031] 57) Stop the calculation, output the final optimal trajectory library, and obtain the optimal effect of flood resource utilization of the stepped reservoir.

[0032] A cascade reservoir flood resource optimal utilization system for the cascade reservoir flood resource optimal utilization method, comprising:

[0033] An initialization module: for constructing a target function and constraint conditions of the cascade reservoir flood resource optimal utilization, and obtaining initial trajectories of each reservoir at each stage satisfying the constraint conditions with the cascade reservoir flood limit water level as the initial trajectory;

[0034] A discrete differential dynamic programming calculation module: for executing a conventional DDDP algorithm iteration, forming a search corridor in the feasible range of the current trajectory library, and seeking a current optimal trajectory in the search corridor using a conventional dynamic programming method;

[0035] A trajectory library module for storing and reading trajectories in the iteration process, and updating in combination with the optimal trajectories of each iteration;

[0036] A convergence and divergence optimization calculation module: for performing convergence and divergence optimization calculation, reading trajectories from the trajectory library module, and combining the trajectories and convergence and divergence optimization calculation factors to perform combination transformation on the current trajectory to obtain an optimal trajectory to replace the current trajectory, and storing the optimal trajectory generated in the current iteration to the trajectory library module;

[0037] An output module: for repeatedly executing the trajectory library module and the convergence and divergence optimization calculation module until a preset iteration stopping condition is met, and finally outputting an optimal trajectory to obtain an optimal effect of cascade reservoir flood resource utilization.

[0038] Preferably, it further comprises a flood resource utilization benefit analysis module, which calculates a flood resource utilization target value based on the optimal trajectory, and gives the benefit compared with not implementing flood resource optimal utilization.

[0039] Compared with the prior art, the present application has the following advantages:

[0040] 1. The convergence and divergence optimization calculation operation is introduced in the DDDP method, which efficiently solves the cascade reservoir flood resource optimal utilization problem, and fully utilizes the double characteristics of "convergence" (i.e. contraction) and "divergence" (i.e. diffusion) of the convergence and divergence optimization calculation operation;

[0041] 2. In the optimization process at each stage, optimization is directly performed according to the convergence and divergence optimization calculation factor, and through the setting of three parameters of positive exponential, negative exponential and square root number, the search step length is flexibly changed, and strong global search ability and stable local search precision are possessed;

[0042] 3. The principle is clear, the control parameters are few, and the calculation is simple, and the cascade reservoir flood resource utilization comprehensive benefit maximization is realized. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1The flow chart of the method for optimal utilization of flood resources of cascade reservoirs according to the present application;

[0044] Figure 2 is the water level process of reservoir A in the process of optimal utilization of flood resources of cascade reservoirs in a dry year in the embodiment;

[0045] Figure 3 is the water level process of reservoir B in the process of optimal utilization of flood resources of cascade reservoirs in a dry year in the embodiment;

[0046] Figure 4 is the water level process of reservoir C in the process of optimal utilization of flood resources of cascade reservoirs in a dry year in the embodiment;

[0047] Figure 5 is the water level process of reservoir D in the process of optimal utilization of flood resources of cascade reservoirs in a dry year in the embodiment. DETAILED DESCRIPTION

[0048] The present application will be further described in detail below in combination with the drawings and specific embodiments.

[0049] As shown in the drawings, Figure 1 a method for optimal utilization of flood resources of cascade reservoirs, comprising the following steps:

[0050] 1) Collecting basic data for utilization of flood resources of cascade reservoirs, constructing an objective function and constraint conditions for optimal utilization of flood resources of cascade reservoirs according to the dispatching rules of cascade reservoirs, in the embodiment, in combination with the dispatching rules or dispatching scheme of cascade reservoirs, on the premise that the operation water level control range of utilization of flood resources of cascade reservoirs and the overall floating space of cascade reservoirs are known, in order to coordinate the utilization process of flood resources of each reservoir, improve the power generation benefit of cascade reservoirs, reduce flood season water abandonment and power output obstruction, and improve the utilization efficiency of water resources in flood season, the mathematical model for optimal utilization of flood resources of cascade reservoirs can be described as: on the basis of known inflow runoff process and interval runoff process of each reservoir in flood season dispatching period, in combination with the operation water level control range of utilization of flood resources of each reservoir and the overall floating space of cascade reservoirs, the maximum power generation in the process of utilization of flood resources of cascade reservoirs is realized on the basis of satisfying the water level, flow and other complex constraints of comprehensive utilization needs such as flood control, navigation and ecology of each reservoir, for this purpose, the objective function of the mathematical model for optimal utilization of flood resources of cascade reservoirs is as follows:

[0051]

[0052] In the formula, F is the total power generation in the process of utilization of flood resources of cascade reservoirs, N is the number of reservoirs, i is the reservoir serial number, and i = 1, 2, …, N, T is the total number of stages of flood resource utilization dispatching period, j is the stage serial number, and j = 1, 2, …, T; A i is the power output coefficient of reservoir i, Q i,jThe power generation flow (m³) of reservoir i in stage j 3 / s), H i,j Let Δj be the average power generation head (m) of reservoir i during stage j after deducting head loss, and let Δj be the stage duration (h). The constraints that the utilization of flood resources in cascade reservoirs must meet mainly include:

[0053] Water balance constraints:

[0054]

[0055] In the formula, V i,j Let m be the reservoir capacity of reservoir i at the end of stage j. 3 );I i,j Let m be the inflow rate of reservoir i at stage j. 3 / s);

[0056] Hydraulic constraints:

[0057]

[0058] In the formula, R i,j Let m be the interval flow rate of reservoir i in stage j. 3 / s); U i Let O be the number of upstream reservoirs of reservoir i. u,j The outflow from upstream reservoir i at stage j (m 3 / s);

[0059] Water level constraints:

[0060]

[0061] In the formula, Z i,j Let be the water level (m) in front of the dam of reservoir i at stage j. and These represent the minimum and maximum water level control values ​​(m) for flood resource utilization of reservoir i during stage j;

[0062] Outbound flow constraints:

[0063]

[0064] In the formula, and These represent the minimum outflow (m³) of reservoir i at stage j. 3 / s) and maximum outflow (m 3 / s);

[0065] Reservoir output constraints:

[0066]

[0067] In the formula, Pi,j is the output of reservoir i in stage j (kW), and is the minimum output of reservoir i in stage j (kW) and the maximum output of reservoir i in stage j (kW), respectively;

[0068] Overall floating space constraint of cascade reservoirs:

[0069]

[0070] wherein V i,j is the storage value of reservoir i at the end of stage j (m 3 ), SP j is the maximum value of the overall floating space of the cascade reservoirs in stage j (m 3 );

[0071] System output constraint:

[0072]

[0073] wherein NP j is the minimum value of the total output of the reservoir group in stage j (kW);

[0074] Non-negative constraint: all variables are non-negative values;

[0075] 2) Setting calculation parameters;

[0076] 3) Taking the flood control water level of the cascade reservoirs as the initial trajectory, obtaining the initial trajectory of each reservoir in each stage that satisfies each constraint condition, and forming a trajectory library;

[0077] 4) Executing the iteration of the conventional DDDP algorithm, forming a search corridor in the feasible range of the current trajectory library, seeking the current optimal trajectory in the search corridor using the conventional dynamic programming method, and storing and updating the current optimal trajectory of each iteration into the trajectory library;

[0078] 5) Continuing the iteration, tracing back the trajectories of the previous generation and the previous two generations on the basis of the current trajectory, performing the converging and diverging optimization update operation, and optimizing the trajectory multiple times until the calculation is completed, outputting the final trajectory, and obtaining the optimal effect of the utilization of flood resources of the cascade reservoirs.

[0079] Specifically, in step 2), the calculation parameters include the number of reservoirs N, the total number of stages T, the maximum number of iterations M, and the maximum number of converging and diverging optimization calculations K.

[0080] In step 3), taking the flood control water level of the cascade reservoirs as the initial trajectory, obtaining the initial trajectory of each reservoir in each stage that satisfies each constraint condition forms a trajectory library wherein Z0= Z represents the initial trajectory of reservoir i at stage j, i.e. the water level value of reservoir i at stage j, Ω0= Z 0 .

[0081] In step 4), the conventional DDDP algorithm is iterated Y times, 2≤Y≤M, to form a search corridor within the feasible range of the current trajectory library, and the conventional dynamic programming method is used in the search corridor to seek the current optimal trajectory and the current optimal trajectory of each iteration is stored and updated in the trajectory library

[0082] In step 5), the following steps are included:

[0083] 51) Set iteration number m = Y + 1;

[0084] 52) Set stage number j = 1;

[0085] 53) Set the current trajectory of each reservoir at the current stage

[0086] 54) Perform the convergence and optimization calculation operation:

[0087] 54.1) Initialize the convergence and optimization calculation number k = 1;

[0088] 54.2) Read the previous generation trajectory Ω and the second previous generation trajectory Ω m-1 from the trajectory library m-2 ;

[0089] 54.3) Based on the current trajectory Ω , combine the previous generation trajectory Ω at the current stage of each reservoir and the second previous generation trajectory Ω at the current stage of each reservoir to perform the convergence and optimization calculation operation, and calculate the convergence and optimization new trajectory Ω of the current trajectory at the current stage of each reservoir The calculation formula is as follows:

[0090]

[0091] In the formula, λ is a random number with a value of 0 or 1, realizing the processing of subtraction and addition of the information of and , S is the convergence and optimization calculation factor, and its calculation formula is as follows:

[0092]

[0093] In the formula, p is a random number between -2.8 and 2.8, and r is a random number between 0 and 1. With the continuous increase of the iteration number m and the random action of p and r, the fluctuation range of S gradually increases, specifically:

[0094] When r≤0.7 and p≥0, S is a positive exponential, promoting individual diffusion movement, preventing and improving the diversity of optimization to promote jumping out of local optimum;

[0095] When r≤0.7 and p<0, S is a negative exponential, controlling the fine contraction of individuals to improve search accuracy;

[0096] When r>0.7, S is a square root number, gradually decreasing from 1 to 0 with iteration, to provide a continuously stable decreasing step size, ensuring stable convergence ability;

[0097] In combination with the above parameter setting scheme, in the converging optimization calculation operation, through the organic cooperation of the positive exponential, the negative exponential and the square root number, a search step size that varies flexibly with the iteration number m is provided, which can ensure that the method has both strong global search ability and stable local search accuracy, and converges to the global optimal value with high precision;

[0098] 54.4) Compare the new trajectory of converging optimization and the current trajectory If is better than Let Otherwise, do nothing;

[0099] 54.5) Let k=k+1, if k≤K, go to step 54.3), otherwise, go to step 55);

[0100] 55) Let j=j+1, if j>T, go to step 56), otherwise go to step 53) to continue the iteration operation;

[0101] 56) Let m=m+1, if m>M, go to step 57); otherwise go to step 52) to continue the iteration operation;

[0102] 57) Stop calculation, output the final optimal trajectory library, and obtain the optimal effect of flood resource utilization of the cascade reservoir.

[0103] A cascade reservoir flood resource optimization utilization system for a cascade reservoir flood resource optimization utilization method, comprising:

[0104] An initialization module: for constructing the objective function and constraint conditions of cascade reservoir flood resource optimization utilization, and taking the flood limited water level of the cascade reservoir as the initial trajectory to obtain the initial trajectory of each reservoir at each stage that meets the constraint conditions;

[0105] A discrete differential dynamic programming calculation module: for executing the iteration of the conventional DDDP algorithm, forming a search corridor within the feasible range of the current trajectory library, and using the conventional dynamic programming method to seek the current optimal trajectory in the search corridor;

[0106] a trajectory library module for storing and reading trajectories in an iteration process, and updating in combination with optimal trajectories of each iteration;

[0107] a collection and optimization calculation module for performing collection and optimization calculation, reading trajectories from the trajectory library module, and combining the trajectories and collection and optimization calculation factors to perform combined transformation on a current trajectory to obtain an optimized trajectory to replace the current trajectory, and storing the optimized trajectory generated in the current iteration to the trajectory library module;

[0108] an output module for repeatedly performing the trajectory library module and the collection and optimization calculation module until a preset iteration stopping condition is met, and finally outputting an optimal trajectory to obtain an optimal effect of flood resource utilization of a cascade reservoir.

[0109] In addition, a flood resource utilization benefit analysis module can also be included, which calculates a flood resource utilization target value based on the optimal trajectory, and gives a benefit compared with not implementing flood resource optimization utilization.

[0110] Taking the flood resource utilization optimization scheduling problem of a cascade reservoir in a river of the Yangtze River during the flood season as an example, there are four cascade reservoirs A, B, C and D. Practice shows that if the flood control water level is controlled for a long time during the flood season of the cascade reservoir, the power output of the power station during the flood season is blocked with a higher probability, and the water cannot be fully utilized, which affects the comprehensive benefit. Therefore, it is necessary to carry out flood resource optimization utilization of the cascade reservoir during the flood season under the premise of ensuring flood control safety.

[0111] During a certain flood season, according to the relevant joint scheduling scheme, the four reservoirs implement flood resource utilization during this period, and the upper limit of the operating water level during the flood season can be generally 2.5m, 2.5m, 2m and 2.5m respectively. The inflow frequencies of 15%, 30%, 50%, 70% and 90% are selected as the typical inflow of the wet year, the partial wet year, the normal year, the partial dry year and the dry year respectively. A total of five different typical inflows are selected. The method of the application and the DDDP are used to carry out cascade reservoir flood resource utilization optimization calculation, and the benefits of implementing flood resource optimization utilization are compared with not implementing flood resource utilization. Table 1 lists the comparison of the calculation results of the method of the application and the DDDP in different level years:

[0112] Table 1 Comparison of calculation results of the method of the application and the DDDP

[0113]

[0114]

[0115] From Table 1, it can be seen that the method of the application has the following advantages compared with the DDDP:

[0116] 1、The method of the present application is consistent with DDDP, and continuously approaches the global optimal solution with the iterative calculation, and the power generation of the method of the present application is greater than that of DDDP, which indicates that the calculation accuracy is greatly improved, and the utilization efficiency of flood resources of cascade reservoirs is further improved.

[0117] 2、The calculation time of the method of the present application is only about 20% of the calculation time of DDDP, and with the further increase of the reservoir scale and the calculation stage, the operation speed of the method of the present application will be more prominent.

[0118] It should be further pointed out that compared with not implementing the utilization of flood resources, the power generation of cascade reservoirs can be improved to different degrees in different water years when the optimal utilization of flood resources of cascade reservoirs is implemented, and the comprehensive benefits of the utilization of flood resources of cascade reservoirs are improved.

[0119] In addition, Figures 2 to 5 The water level change of each reservoir under the condition of partial dry year water is listed, and the scheduling results meet the constraint conditions of water level, storage capacity and flow rate.

[0120] The method and system for optimal utilization of flood resources of cascade reservoirs of the present application introduce the convergence and divergence optimization calculation operation in the DDDP method, efficiently solve the optimal utilization problem of flood resources of cascade reservoirs, fully utilize the double characteristics of convergence (i.e. contraction) and divergence (i.e. diffusion) of the convergence and divergence optimization calculation operation, directly optimize according to the convergence and divergence optimization calculation factor in each stage, and change the search step by setting three parameters of positive index, negative index and square root number, so as to have strong global search ability and stable local search precision.

[0121] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present application, and is not used to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for optimizing the utilization of flood resources in cascade reservoirs, characterized in that: Includes the following steps: 1) Collect basic data on the utilization of flood resources in cascade reservoirs, and construct the objective function and constraints for the optimal utilization of flood resources in cascade reservoirs in accordance with the cascade reservoir operation regulations; 2) Set the calculation parameters, including the number of reservoirs N, the total number of stages during the scheduling period T, the maximum number of iterations M, and the maximum number of calculations for collection, dispersion, and optimization K; 3) Using the flood control limit water level of the cascade reservoirs as the initial trajectory, the initial trajectories of each reservoir at each stage that satisfy all constraints are obtained, forming a trajectory database. Forming a trajectory database in This represents the initial trajectory of reservoir i in stage j, i.e., the water level value of reservoir i in stage j, Ω0 = Z 0 ; 4) Perform the standard DDDP algorithm iterations to form a search corridor within the feasible range of the current trajectory database. Within the search corridor, use the standard dynamic programming method to find the current optimal trajectory, and store the current optimal trajectory of each iteration to update the trajectory database. Perform the standard DDDP algorithm iterations Y times, 2≤Y≤M, to form a search corridor within the feasible range of the current trajectory database, and use the standard dynamic programming method to find the current optimal trajectory within the search corridor. The current optimal trajectory for each iteration is stored and the trajectory database is updated. 5) Continue iterating, tracing back the trajectories of the previous generation and the two generations before that based on the current trajectory, performing convergence and optimization update operations, repeatedly optimizing the trajectory until the calculation is complete, outputting the final trajectory, and obtaining the optimal effect of flood resource utilization in cascade reservoirs, including the following steps: 51) Set the iteration count m = Y + 1; 52) Set the stage number j = 1; 53) Set the current trajectory of each reservoir at the current stage. 54) Perform the calculation operation for collection and optimization: 54.1) Initialize the number of calculations for collection, dispersion, and optimization to k = 1; 54.2) From the trajectory database In the middle, read the trajectory of the previous generation Ω m-1 and the previous two generations of trajectory Ω m-2 ; 54.3) Based on the current trajectory Based on this, and combined with the previous generation's trajectory at the current stage of each reservoir... and the trajectory of the first two generations of each reservoir in the current stage Perform the collection and optimization calculation operation to calculate the current trajectory of each reservoir at the current stage. The new trajectory of convergence and optimization The calculation formula is as follows: In the formula, λ is a random number that takes the value 0 or 1, to achieve... and The subtraction and addition of information from both sources are handled by S, which is the factor for convergence and optimization. The formula for S is as follows: In the formula, p is a random number between -2.8 and 2.8, and r is a random number between 0 and 1; 54.4) Comparison of divergent and convergent new trajectories and current trajectory if Superior Then let Otherwise, no action will be taken; 54.5) Let k = k + 1. If k ≤ K, go to step 54.3); otherwise, go to step 55. 55) Let j = j + 1. If j > T, then go to step 56); otherwise, go to step 53) and continue the iteration operation. 56) Let m = m + 1. If m > M, then go to step 57). Otherwise, proceed to step 52) and continue the iterative operation; 57) Stop the calculation, output the final optimal trajectory library, and obtain the optimal effect of flood resource utilization of cascade reservoirs.

2. A cascade reservoir flood resource optimization and utilization system, characterized in that: The method for optimizing the utilization of flood resources in cascade reservoirs as described in claim 1 includes: Initialization module: Used to construct the objective function and constraints for the optimal utilization of flood resources in cascade reservoirs, and to obtain the initial trajectories of each reservoir at each stage that satisfy each constraint condition, using the flood control limit water level of the cascade reservoirs as the initial trajectory. Discrete Differential Dynamic Programming Module: Used to perform the conventional DDDP algorithm iteration, form a search corridor within the feasible range of the current trajectory library, and use conventional dynamic programming methods to find the current optimal trajectory within the search corridor; The trajectory library module is used to store and retrieve trajectories during the iteration process, and update them by combining the optimal trajectory of each iteration; The convergence and optimization calculation module is used to perform convergence and optimization calculations. It reads the trajectory from the trajectory library module, combines the trajectory with the convergence and optimization calculation factors, performs a combination transformation on the current trajectory to obtain an optimized trajectory to replace the current trajectory, and stores the optimized trajectory generated in the current iteration into the trajectory library module. The output module is used to repeatedly execute the trajectory library module and the convergence and optimization calculation module until the preset iteration stopping condition is met, and finally output the optimal trajectory to obtain the optimal effect of flood resource utilization in cascade reservoirs.

3. The cascade reservoir flood resource optimization and utilization system as described in claim 2, characterized in that: It also includes a flood resource utilization benefit analysis module, which calculates the target value of flood resource utilization based on the optimal trajectory and gives the benefits compared to not implementing flood resource optimization.

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