Water engineering ecological scheduling method, system, equipment and medium

Abstract

The invention discloses a water engineering ecological scheduling method, system, equipment and medium, and the method comprises the steps: obtaining an original scheduling rule of a water engineering, and water flux data and carbon flux data of the water engineering; constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data; performing parameter optimization on scheduling rule parameters in the original scheduling rule through the ecological optimization scheduling model to obtain optimal demodulation parameters; and according to the optimal demodulation parameter, performing parameter updating on a scheduling rule parameter in the original scheduling rule to obtain a target scheduling rule. The method can effectively improve the objective degree and rationality of ecological scheduling, and is beneficial to improving the health stability of the river ecological environment. The invention relates to the technical field of hydrology science.

Description

Technical Field

[0001] The present invention relates to the field of hydrological science and technology, and in particular to a method, system, equipment and medium for ecological dispatching of water projects. Background Art

[0002] The water flow in the river is the main carrier of river carbon transfer, and the river carbon flux is significantly correlated with the flow rate in the river. In the process of regulating the flow rate in the river through water projects such as reservoirs, humans not only affect the water ecological environment of the river, but also inevitably change the river carbon transfer amount, which in turn affects the carbon cycle process from land to ocean, affecting the stability of the ecological environment system on a larger scale.

[0003] At present, existing technologies usually consider rivers as an independent system, believing that the ecological flow of rivers is the amount of water required to maintain the healthy and stable development of the water ecology and water environment in the river, and dispatch water projects based on the ecological flow of the river to maintain the ecological environment of the river and its surrounding environment. This method will change the natural rhythm of the river's water carbon transfer process to a certain extent, which can easily destroy the health and stability of the river's ecological environment, and the objectivity and rationality of ecological dispatch are poor.

[0004] Therefore, the problems existing in the prior art still need to be solved and optimized. Summary of the invention

[0005] The purpose of the present invention is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, an object of an embodiment of the present invention is to provide a water project ecological scheduling method, system, equipment and medium, wherein the method can effectively improve the objectivity and rationality of ecological scheduling, which is conducive to improving the health and stability of the river ecological environment.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present application include:

[0008] In a first aspect, an embodiment of the present application provides a water project ecological scheduling method, including:

[0009] Obtaining original dispatching rules of a water project and water flux data and carbon flux data of the water project;

[0010] Constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data;

[0011] Optimizing the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain the optimal demodulation parameters;

[0012] According to the optimal demodulation parameters, the scheduling rule parameters in the original scheduling rule are updated to obtain the target scheduling rule.

[0013] In addition, the method according to the above embodiment of the present application may also have the following additional technical features:

[0014] Further, in one embodiment of the present application, constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data includes:

[0015] Obtaining a water supply objective function and a power generation objective function, as well as water project scheduling constraints, wherein the water project scheduling constraints include water volume balance constraints, water level constraints, output constraints, and downstream flow constraints;

[0016] constructing an ecological objective function according to the water flux data and the carbon flux data;

[0017] The ecological optimization scheduling model is constructed according to the ecological objective function, the water supply objective function, the power generation objective function and the water project scheduling constraints.

[0018] Furthermore, in one embodiment of the present application, constructing an ecological objective function according to the water flux data and the carbon flux data includes:

[0019] According to the water flux data, performing a joint probability distribution calculation on the carbon flux data to obtain a water-carbon flux joint probability distribution;

[0020] Performing distribution change analysis on the water-carbon flux joint probability distribution to obtain a water-carbon flux change index;

[0021] The ecological objective function is constructed by minimizing the water-carbon flux change index.

[0022] Further, in one embodiment of the present application, performing a joint probability distribution calculation on the carbon flux data according to the water flux data to obtain a water-carbon flux joint probability distribution includes:

[0023] Performing water flux distribution analysis on the water flux data to obtain water flux probability distribution;

[0024] Performing carbon flux distribution analysis on the carbon flux data to obtain a carbon flux probability distribution;

[0025] According to the water flux probability distribution, the carbon flux probability distribution is subjected to distribution association processing to obtain the water-carbon flux joint probability distribution.

[0026] Further, in one embodiment of the present application, the carbon flux probability distribution is subjected to distribution association processing according to the water flux probability distribution to obtain the water-carbon flux joint probability distribution, including:

[0027] Obtaining a first marginal distribution function of the water flux data and a second marginal distribution function of the carbon flux data;

[0028] According to the first marginal distribution function, performing a link function screening on the second marginal distribution function to obtain a target link function;

[0029] According to the target link function, the water flux probability distribution and the carbon flux probability distribution are associated with each other to obtain the water-carbon flux joint probability distribution.

[0030] Further, in the embodiment of the present application, the step of performing a connection function screening on the second marginal distribution function according to the first marginal distribution function to obtain a target connection function includes:

[0031] Get several intermediate connection functions;

[0032] According to the first marginal distribution function and the second marginal distribution function, performing a fitting test on all the intermediate linking functions to obtain a fitting test result corresponding to each of the intermediate linking functions;

[0033] According to the first marginal distribution function and the second marginal distribution function, performing a goodness of fit analysis on all the intermediate linking functions to obtain a goodness of fit analysis result corresponding to each of the intermediate linking functions;

[0034] According to all the fitting test results and all the goodness of fit analysis results, all the intermediate link functions are screened to obtain the target link function.

[0035] Furthermore, in one embodiment of the present application, the water-carbon flux joint probability distribution is subjected to distribution change analysis to obtain a water-carbon flux change index, including:

[0036] Get the preset joint distribution change indicator function;

[0037] According to the water-carbon flux joint probability distribution, a first joint probability density function and a second joint probability density function are obtained, wherein the first joint probability density function is the water-carbon flux joint probability density function of the water project before scheduling, and the second joint probability density function is the water-carbon flux joint probability density function of the water project after scheduling;

[0038] According to the joint distribution change index function, a change index analysis is performed on the first joint probability density function and the second joint probability density function to obtain the water-carbon flux change index.

[0039] In a second aspect, the present application embodiment provides a water project ecological scheduling system, including:

[0040] A first processing unit is used to obtain an original dispatching rule of a water project and water flux data and carbon flux data of the water project;

[0041] A second processing unit is used to construct an ecological optimization scheduling model according to the water flux data and the carbon flux data;

[0042] A third processing unit is used to optimize the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain optimal demodulation parameters;

[0043] The fourth processing unit is used to update the scheduling rule parameters in the original scheduling rule according to the optimal demodulation parameters to obtain the target scheduling rule.

[0044] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0045] at least one processor;

[0046] at least one memory for storing at least one program;

[0047] When the at least one program is executed by the at least one processor, the at least one processor implements the method of the first aspect described above.

[0048] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor, and the program executable by the processor is used to implement the method of the first aspect when executed by the processor.

[0049] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0050] An ecological scheduling method for a water project disclosed in an embodiment of the present application, wherein the method obtains the original scheduling rules of the water project and the water flux data and carbon flux data of the water project; constructs an ecological optimization scheduling model based on the water flux data and the carbon flux data; optimizes the scheduling rule parameters in the original scheduling rules through the ecological optimization scheduling model to obtain the optimal demodulation parameters; and updates the scheduling rule parameters in the original scheduling rules based on the optimal demodulation parameters to obtain the target scheduling rules. This method optimizes the parameters in the original scheduling rules based on the ecological optimization scheduling model constructed based on the water flux data and the carbon flux data, and can obtain the target scheduling rules that fully consider the water and carbon transfer of the river, which can effectively improve the objectivity and rationality of ecological scheduling, and is conducive to improving the health and stability of the river's ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the embodiments of the present application or the drawings of the related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly expressing some embodiments of the technical solutions of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 A schematic diagram of a flow chart of a water project ecological scheduling method provided in an embodiment of the present application;

[0053] Figure 2 A schematic diagram of the structure of a water project ecological dispatching system provided in an embodiment of the present application;

[0054] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and are not to be construed as limitations on the present application. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0057] At present, existing technologies usually consider rivers as an independent system, believing that the ecological flow of rivers is the amount of water required to maintain the healthy and stable development of the water ecology and water environment in the river, and dispatch water projects (such as reservoirs, water conservancy hubs, sluice gates, etc.) based on the ecological flow of rivers to maintain the ecological environment of rivers and surrounding environments. However, this method will change the natural rhythm of the river water and carbon transfer process to a certain extent, which is easy to destroy the health and stability of the river's ecological environment (such as the river's own ecological environment, estuary and offshore ecological environment, etc.), and the objectivity and rationality of ecological dispatch are not good.

[0058] In view of this, an embodiment of the present invention provides a water project ecological scheduling method, system, equipment and medium, wherein the method optimizes the parameters in the original scheduling rules based on an ecological optimization scheduling model constructed based on water flux data and carbon flux data, so that the obtained target scheduling rules not only consider the impact of water flux on the river ecological environment, but also consider the impact of carbon flux on the river ecological environment, effectively improve the objectivity and rationality of ecological scheduling based on the target scheduling rules, and are conducive to improving the health and stability of the river ecological environment.

[0059] Reference Figure 1 In an embodiment of the present application, a water project ecological scheduling method includes:

[0060] Step 110, obtaining the original dispatching rules of the water project and the water flux data and carbon flux data of the water project;

[0061] In an embodiment of the present application, the water project may be a reservoir, a water conservancy hub, a sluice gate, etc., and the original scheduling rule may be the initial ecological scheduling rule of the water project, which may include the outflow flow of the water project at each time point in a certain time sequence; or, the original scheduling rule may be a scheduling rule that does not take into account the ecological flow demand.

[0062] It can be understood that the water flux data can be the river flow of a water project at a certain river section, and the carbon flux data can be the carbon transfer per unit time of a water project at a certain river section. The embodiment of the present application takes the river section corresponding to the carbon flux data and the water flux data as an example.

[0063] For example, for water flux data, the first acquisition method can be based on long-sequence flow observation data collected from hydrological observation sites; or, in the second acquisition method, long-sequence data of river flow can also be generated based on hydrological models, such as the Xin'anjiang hydrological model, the SWAT (Soil and Water Assessment Tool) model, the VIC (Variable Infiltration Capacity) model, etc. Specifically, the river's meteorological, topographic, land cover, soil, flow and other data can be obtained first, and the acquired data can be simulated and calculated through the configured hydrological model to obtain the long-sequence flow data of the specified river section.

[0064] It should be noted that the method of obtaining carbon flux data is similar to the above content. The carbon flux data can be used to simulate the river carbon flux through any one of the MIKE hydrodynamic model, RAP (River Aquatic Productivity) model, etc., which will not be repeated in this application.

[0065] Step 120: constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data;

[0066] In an embodiment of the present application, an ecological target can be constructed based on water flux data and carbon flux data. The ecological target is used to maintain the ecological environment of the river. Then, an ecological optimization scheduling model is constructed based on the ecological target, so that the scheduling rules output by the ecological optimization scheduling model can take into account the joint impact of water flux and carbon flux on the river's ecological environment, reduce the impact on the natural rhythm of the river's water and carbon transfer process, and improve the health and stability of the river's ecological environment, thereby improving the objectivity and rationality of ecological scheduling.

[0067] In some embodiments, the step 120, constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data, includes:

[0068] A1. Obtaining a water supply objective function and a power generation objective function, as well as water project scheduling constraints, wherein the water project scheduling constraints include water volume balance constraints, water level constraints, output constraints, and downstream flow constraints;

[0069] In the embodiment of the present application, the water supply objective function is used to meet the water supply demand in the ecological scheduling of water projects. The water supply objective function includes minimizing the maximum damage depth and maximizing the water supply guarantee rate, wherein the maximum damage depth is used to characterize the proportion of the maximum water shortage in all time periods relative to the water supply target, and the water supply guarantee rate is used to characterize the proportion of the number of time periods that meet the water supply target in all time periods. Specifically, for the objective function of minimizing the maximum damage depth, it can be expressed as:

[0070]

[0071] Among them, H2 is the objective function of minimizing the maximum damage depth; min(·) is the minimum value function; D max is the maximum damage depth; W(t) is the average water supply of the water project in time period t; W obj The water supply target for water projects;

[0072] The objective function of maximizing the water supply guarantee rate can be expressed as:

[0073]

[0074] Among them, H3 is the objective function of maximizing the water supply guarantee rate; max(·) is the maximum value function; R is the water supply guarantee rate; N s is the number of time periods to meet the water supply target; T is the total number of time periods.

[0075] It can be understood that the power generation objective function is used to meet the power generation requirements in the ecological dispatch of water projects. The power generation objective function includes maximizing the power generation. The objective function of maximizing the power generation can be expressed as:

[0076]

[0077] Among them, H4 is the objective function of maximizing power generation; E is the total power generation of the water project in all time periods; is the output of the i-th water project in time period t, and n is the number of water projects.

[0078] It should be noted that the water project scheduling constraints include water balance constraints, water level constraints, output constraints and downstream flow constraints. Specifically, the water balance constraints can be expressed as:

[0079] V i (t+1)=V i (t)+(Ii(t)-Q i (t))Δt

[0080] Among them, V i (t) is the water storage capacity of the i-th water project at the beginning of period t; V i (t+1) is the water storage capacity of the i-th water project at the beginning of the t+1 period, that is, the water storage capacity of the i-th water project at the end of the t period; I i (t) is the inflow flow of the i-th water project in period t; Q i (t) is the discharge flow of the ith water project in period t; Δt is the time step of period t.

[0081] The water level constraint can be expressed as:

[0082] Z i，min ≤Z i (t)≤Z i，max

[0083] Among them, Z i，min is the minimum water level allowed for the ith water project in all time periods; Z i，max is the maximum water level allowed for the ith water project in all time periods; Z i (t) is the water level of the ith water project in time period t.

[0084] The output constraint can be expressed as:

[0085] P i，min ≤P i (t)≤P i，max

[0086] Among them, P i，min is the minimum output allowed for the ith water project in all time periods; P i，max is the maximum output allowed for the ith water project in all time periods; P i (t) is the output of the i-th water project in time period t.

[0087] The downstream flow constraint can be expressed as:

[0088] Q i (t)≤q max (Z i (t))

[0089] Among them, q max (Z i (t)) is the water level of the i-th water project in time period t and Z i Maximum discharge capacity at time (t).

[0090] A2. constructing an ecological objective function according to the water flux data and the carbon flux data;

[0091] Furthermore, the step A2, constructing an ecological objective function according to the water flux data and the carbon flux data, comprises:

[0092] B1. performing a joint probability distribution calculation on the carbon flux data according to the water flux data to obtain a water-carbon flux joint probability distribution;

[0093] Further, the step B1, performing a joint probability distribution calculation on the carbon flux data according to the water flux data to obtain a water-carbon flux joint probability distribution, comprises:

[0094] C1. performing water flux distribution analysis on the water flux data to obtain water flux probability distribution;

[0095] C2. performing carbon flux distribution analysis on the carbon flux data to obtain a carbon flux probability distribution;

[0096] In the embodiment of the present application, the ecological objective function of the ecological optimization scheduling model can be obtained based on the acquired water flux data and carbon flux data. Specifically, the water flux distribution analysis in step C1 can first be to perform statistical analysis on the water flux data in the form of a long sequence, so as to obtain statistical parameters such as the mean, coefficient of variation and skewness coefficient of the water flux data; then, based on the obtained statistical parameters, the water flux probability distribution of the water flux data is calculated by Pearson type distribution, which can be specifically achieved by Pearson type III distribution.

[0097] It can be understood that for carbon flux data, we can first perform statistical analysis on the carbon flux data in the form of a long sequence to determine the distribution characteristics of the carbon flux data, such as the mean, variance, skewness and kurtosis; then use a probability distribution model (such as a normal distribution model, a lognormal distribution model or a gamma distribution model) to fit these distribution characteristics to obtain the carbon flux probability distribution of the carbon flux data.

[0098] C3. According to the water flux probability distribution, the carbon flux probability distribution is subjected to distribution association processing to obtain the water-carbon flux joint probability distribution.

[0099] Furthermore, the step C3, performing distribution association processing on the carbon flux probability distribution according to the water flux probability distribution to obtain the water-carbon flux joint probability distribution, includes:

[0100] D1, obtaining a first marginal distribution function of the water flux data and a second marginal distribution function of the carbon flux data;

[0101] In the embodiment of the present application, the ecological flow provided by the ecological scheduling of the water project needs to consider the water and carbon flux at the same time. Therefore, a joint probability distribution of water and carbon flux can be constructed based on the water flux probability distribution and the carbon flux probability distribution, which is conducive to fully considering the correlation between water flux and carbon flux.

[0102] It can be understood that step D1 can be a first marginal distribution function for obtaining water flux data and a second marginal distribution function for carbon flux data. The first marginal distribution function can be obtained by statistically analyzing the water flux data, or it can be obtained by simply transforming the above-mentioned water flux probability distribution. The second marginal distribution function is similar to the aforementioned first marginal distribution function and can be simply inferred, so this application will not go into details here.

[0103] D2. According to the first marginal distribution function, performing a copula function screening on the second marginal distribution function to obtain a target copula function;

[0104] Furthermore, the step D2, performing a copula function screening on the second marginal distribution function according to the first marginal distribution function to obtain a target copula function, includes:

[0105] E1. Obtain several intermediate connection functions;

[0106] E2. performing a fitting test on all the intermediate linking functions according to the first marginal distribution function and the second marginal distribution function, and obtaining a fitting test result corresponding to each of the intermediate linking functions;

[0107] E3. Performing a goodness of fit analysis on all the intermediate linking functions according to the first marginal distribution function and the second marginal distribution function to obtain a goodness of fit analysis result corresponding to each of the intermediate linking functions;

[0108] E4. Perform link function screening on all the intermediate link functions according to all the fitting test results and all the goodness of fit analysis results to obtain the target link function.

[0109] In an embodiment of the present application, the intermediate linking functions may be different types of Copula functions. In the embodiment of the present application, the number of intermediate linking functions is 3 as an example. The first intermediate linking function may be a Gumbell-Houggard (GH) type Copula function; the second intermediate linking function may be a Clayton type Copula function; and the third intermediate linking function may be a Frank type Copula function.

[0110] It can be understood that the first intermediate link function, the second intermediate link function and the third intermediate link function all contain a parameter θ, and the parameter θ can be estimated by the correlation index method, for example, it can be calculated by the relationship between the Kendall rank correlation coefficient τ and the parameter θ, and the Kendall rank correlation coefficient τ can be calculated based on the various water flux values ​​in the water flux data and the various carbon flux values ​​in the carbon flux data, which will not be repeated in this application.

[0111] It should be noted that after obtaining all the intermediate link functions, the first marginal distribution function and the second marginal distribution function can be respectively input into the theoretical function model corresponding to each intermediate link function, and the fitting test result corresponding to each intermediate link function can be obtained by the Kolmogorov-Smirnov (KS) test of the Copula function. At the same time, the first marginal distribution function and the second marginal distribution function are respectively input into the theoretical function model corresponding to each intermediate link function, and the minimum sum of squares of deviations (OLS) criterion is used to evaluate the effectiveness of each intermediate link function, so as to complete the goodness of fit analysis and obtain the goodness of fit analysis result corresponding to each intermediate link function.

[0112] It is worth mentioning that after obtaining all the fitting test results and all the goodness of fit analysis results, the target linkage function can be selected from all the intermediate linkage functions. There are many specific screening methods. For example, the intermediate linkage function with the smallest goodness of fit analysis result and the best fitting test result can be determined as the target linkage function. The example in this application is for illustration only.

[0113] D3. According to the target link function, the water flux probability distribution and the carbon flux probability distribution are associated with each other to obtain the water-carbon flux joint probability distribution.

[0114] In an embodiment of the present application, step D3 may be to input the water flux probability distribution and the carbon flux probability distribution into the target link function for correlation calculation, so as to obtain the water-carbon flux joint probability distribution.

[0115] B2. performing distribution change analysis on the water-carbon flux joint probability distribution to obtain a water-carbon flux change index;

[0116] Furthermore, the step B2, performing distribution change analysis on the water-carbon flux joint probability distribution to obtain a water-carbon flux change index, includes:

[0117] F1. Get the preset joint distribution change indicator function;

[0118] F2. According to the water-carbon flux joint probability distribution, a first joint probability density function and a second joint probability density function are obtained, wherein the first joint probability density function is the water-carbon flux joint probability density function of the water project before scheduling, and the second joint probability density function is the water-carbon flux joint probability density function of the water project after scheduling;

[0119] F3. According to the joint distribution change index function, a change index analysis is performed on the first joint probability density function and the second joint probability density function to obtain the water-carbon flux change index.

[0120] In the embodiment of the present application, the joint distribution change index function is used to evaluate the change in water and carbon flux in the river channel during the scheduling of the natural water flow process by the water project. Step F2 can be based on the joint probability distribution of water and carbon flux to obtain the joint probability density function of water and carbon flux of the water project before and after scheduling. Specifically, it can be based on the functional form of the joint probability distribution of water and carbon flux of the water project before scheduling, and the first joint probability density function can be obtained by derivative transformation; and for the second joint probability density function, the joint probability distribution of water and carbon flux after simulated scheduling can be obtained based on the simulation generation method, and then the second joint probability density function can be obtained based on the functional form of the joint probability distribution of water and carbon flux after the simulated scheduling.

[0121] It is understandable that the first joint probability density function can also be calculated based on the target linkage function corresponding to the joint probability distribution of water-carbon flux, as well as the inverse of the first marginal distribution function and the inverse of the second marginal distribution function, which will not be repeated in this application.

[0122] It should be noted that step F3 can be to perform change index analysis on the first joint probability density function and the second joint probability density function input value joint distribution transformation index function, so as to obtain the water-carbon flux change index. Specifically, the water-carbon flux change index can be expressed as:

[0123] I=∫∫|f X，Y (x, y)-f′ X，Y (x,y)|dxdy

[0124] Where I is the water-carbon flux change index; f X，Y (x, y) is the first joint probability density function; f′ X，Y (x, y) is the second joint probability density function; X is the water flux data; Y is the carbon flux data; x is the water flux value in the water flux data; y is the carbon flux value in the water flux data.

[0125] B3. Construct the ecological objective function by minimizing the water-carbon flux change index.

[0126] In the embodiment of the present application, the water carbon flux change index can be minimized as the ecological goal of water project scheduling, thereby obtaining an ecological objective function, which can be expressed as:

[0127] H1=min(I)

[0128] Among them, H1 is the ecological objective function.

[0129] A3. Constructing the ecological optimization scheduling model according to the ecological objective function, the water supply objective function, the power generation objective function and the water project scheduling constraints

[0130] In an embodiment of the present application, a multi-objective and multi-constraint optimization scheduling model can be constructed based on the ecological objective function, water supply objective function, power generation objective function and water project scheduling constraints to obtain an ecological optimization scheduling model.

[0131] Step 130: Optimize the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain optimal demodulation parameters;

[0132] In an embodiment of the present application, a multi-objective optimization algorithm can be used, such as any one of the multi-objective particle swarm optimization algorithm (MOPSO), the non-dominated sorting genetic optimization algorithm (NSGA-II), etc., with the ecological objective function, the water supply objective function and the power generation objective function as the optimization objectives, and the scheduling rule parameters in the original scheduling rules are iteratively optimized to obtain a multi-objective non-inferior solution set, and then, combined with the competitive relationship and guarantee requirements between different optimization objectives, the best solution is selected from the non-inferior solution set, and the best solution is determined as the optimal demodulation parameter.

[0133] It should be noted that the original scheduling rule can generally be in the form of a scheduling function or a scheduling graph. The function form of the original scheduling rule can be expressed as:

[0134] Q i (t) = f(I i (t), V i (t), t; θ r )

[0135] Among them, θ r It is the scheduling rule parameter in the original scheduling rule.

[0136] Step 140: Update the scheduling rule parameters in the original scheduling rule according to the optimal demodulation parameters to obtain the target scheduling rule.

[0137] In an embodiment of the present application, after obtaining the optimal demodulation parameters, the optimal demodulation parameters can be substituted into the original scheduling rules to obtain the water project scheduling rules (ie, target scheduling rules) that take into account the water and carbon transfer amount.

[0138] A water project ecological scheduling system proposed according to an embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0139] Reference Figure 2 , a water project ecological dispatching system proposed in the embodiment of the present application includes:

[0140] The first processing unit 101 is used to obtain the original dispatching rules of the water project and the water flux data and carbon flux data of the water project;

[0141] The second processing unit 102 is used to construct an ecological optimization scheduling model according to the water flux data and the carbon flux data;

[0142] The third processing unit 103 is used to optimize the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain the optimal demodulation parameters;

[0143] The fourth processing unit 104 is used to update the scheduling rule parameters in the original scheduling rule according to the optimal demodulation parameters to obtain the target scheduling rule.

[0144] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0145] Reference Figure 3 , the embodiment of the present application further provides an electronic device, including:

[0146] at least one processor 201;

[0147] At least one memory 202, used to store at least one program;

[0148] When the at least one program is executed by the at least one processor 201, the at least one processor 201 implements the above method embodiment.

[0149] Similarly, it can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0150] The embodiment of the present application further provides a computer-readable storage medium, in which a program executable by the processor 201 is stored. The program executable by the processor 201 is used to implement the above-mentioned method embodiment when executed by the processor 201.

[0151] Similarly, the contents of the above method embodiments are all applicable to the computer-readable storage medium embodiments. The functions specifically implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0152] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part described as a larger operation is performed independently.

[0153] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0154] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method of the embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0155] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0156] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0157] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0158] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0159] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0160] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Technical personnel familiar with the field can make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A water project ecological scheduling method, characterized in that: include: Obtaining original dispatching rules of a water project and water flux data and carbon flux data of the water project; Constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data; Optimizing the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain the optimal demodulation parameters; According to the optimal demodulation parameters, the scheduling rule parameters in the original scheduling rule are updated to obtain the target scheduling rule.

2. The method according to claim 1, characterized in that The step of constructing an ecological optimization scheduling model according to the water flux data and the carbon flux data comprises: Obtaining a water supply objective function and a power generation objective function, as well as water project scheduling constraints, wherein the water project scheduling constraints include water volume balance constraints, water level constraints, output constraints, and downstream flow constraints; constructing an ecological objective function according to the water flux data and the carbon flux data; The ecological optimization scheduling model is constructed according to the ecological objective function, the water supply objective function, the power generation objective function and the water project scheduling constraints.

3. The method according to claim 2, characterized in that The step of constructing an ecological objective function based on the water flux data and the carbon flux data comprises: According to the water flux data, performing a joint probability distribution calculation on the carbon flux data to obtain a water-carbon flux joint probability distribution; Performing distribution change analysis on the water-carbon flux joint probability distribution to obtain a water-carbon flux change index; The ecological objective function is constructed by minimizing the water-carbon flux change index.

4. The method according to claim 3, characterized in that The step of performing a joint probability distribution calculation on the carbon flux data according to the water flux data to obtain a water-carbon flux joint probability distribution comprises: Performing water flux distribution analysis on the water flux data to obtain water flux probability distribution; Performing carbon flux distribution analysis on the carbon flux data to obtain a carbon flux probability distribution; According to the water flux probability distribution, the carbon flux probability distribution is subjected to distribution association processing to obtain the water-carbon flux joint probability distribution.

5. The method according to claim 4, characterized in that The step of performing distribution association processing on the carbon flux probability distribution according to the water flux probability distribution to obtain the water-carbon flux joint probability distribution includes: Obtaining a first marginal distribution function of the water flux data and a second marginal distribution function of the carbon flux data; According to the first marginal distribution function, performing a link function screening on the second marginal distribution function to obtain a target link function; According to the target link function, the water flux probability distribution and the carbon flux probability distribution are associated with each other to obtain the water-carbon flux joint probability distribution.

6. The method according to claim 5, characterized in that The step of performing a connection function screening on the second marginal distribution function according to the first marginal distribution function to obtain a target connection function includes: Get several intermediate connection functions; According to the first marginal distribution function and the second marginal distribution function, performing a fitting test on all the intermediate linking functions to obtain a fitting test result corresponding to each of the intermediate linking functions; According to the first marginal distribution function and the second marginal distribution function, performing a goodness of fit analysis on all the intermediate linking functions to obtain a goodness of fit analysis result corresponding to each of the intermediate linking functions; According to all the fitting test results and all the goodness of fit analysis results, all the intermediate link functions are screened to obtain the target link function.

7. The method according to claim 3, characterized in that The distribution change analysis of the water-carbon flux joint probability distribution is performed to obtain a water-carbon flux change index, including: Get the preset joint distribution change indicator function; According to the water-carbon flux joint probability distribution, a first joint probability density function and a second joint probability density function are obtained, wherein the first joint probability density function is the water-carbon flux joint probability density function of the water project before scheduling, and the second joint probability density function is the water-carbon flux joint probability density function of the water project after scheduling; According to the joint distribution change index function, a change index analysis is performed on the first joint probability density function and the second joint probability density function to obtain the water-carbon flux change index.

8. A water project ecological dispatching system, characterized in that: include: A first processing unit is used to obtain an original dispatching rule of a water project and water flux data and carbon flux data of the water project; A second processing unit is used to construct an ecological optimization scheduling model according to the water flux data and the carbon flux data; A third processing unit is used to optimize the dispatch rule parameters in the original dispatch rule by using the ecological optimization dispatch model to obtain optimal demodulation parameters; The fourth processing unit is used to update the scheduling rule parameters in the original scheduling rule according to the optimal demodulation parameters to obtain the target scheduling rule.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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