Valley area wind-light-water energy development layout optimization method based on numerical simulation

Abstract

The invention discloses a river valley area wind-light-water energy development layout optimization method based on numerical simulation, and relates to the technical field of hydrology and water conservancy, and the method comprises the steps: calculating the river grades of all river reach in a river network through a Strahler method; setting a mapping table of the river grades and WRF-Hydro river channel confluence parameters according to the river grades obtained through calculation; simulating a plurality of sessions of flood according to the initial value of the river channel confluence parameter, and calculating a simulation performance evaluation index; and calibrating the river channel confluence parameters corresponding to different river grades in the mapping table by adopting a dynamic dimension search algorithm. By means of the method, the number of the river channel confluence parameters needing to be calibrated can be reduced to a large extent, so that the confluence parameters of different river grades in the WRF-Hydro mode are calibrated in an automatic adjusting mode, interference of human factors is reduced, the accuracy of river channel flow simulation is improved, and powerful technical support is provided for water resource management and flood early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrology and water conservancy, and specifically to an optimization method and system for the development layout of wind, light, and water energy in river valley areas based on numerical simulation. Background Technique

[0002] The WRF-Hydro model is a new generation of model system that can simulate various hydrological processes such as surface runoff and river network confluence. In recent years, it has had a wide influence in the fields of flood forecasting and water resource evaluation. The WRF-Hydro model designs a large number of parameters. Among them, parameters such as the cross-sectional shape and roughness of the river channel related to the river network confluence process have an important impact on the simulation of river channel water volume. These parameters lack direct observation and need to be determined by calibration methods. The river network consists of multiple river reaches. With the expansion of the spatial range and the improvement of the simulation fineness of the WRF-Hydro simulation, the number of river network reaches increases rapidly, reaching thousands to tens of thousands of river reaches. Each river reach has different cross-sectional shape parameters and roughness parameters to be calibrated. However, the existing model parameter calibration methods are difficult to automatically process thousands or even tens of thousands of parameters to be calibrated. Existing research generally uses empirically preset parameters or manually adjusts based on the values of preset parameters. The preset parameters or manually adjusted parameters cannot well describe the changes in the cross-sectional shape and roughness of the river network in the simulation area, which is one of the main reasons for the simulation error of the WRF-Hydro river channel flow. Summary of the Invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is: how to solve the problem of the lack of calibration of the river confluence parameters of large-scale river networks in the WRF-Hydro model

[0005] To solve the above technical problem, the present invention provides the following technical solution: an optimization method for the development layout of wind, light, and water energy in river valley areas based on numerical simulation, which includes the following steps

[0006] Use the Strahler method to calculate the river grading of all river reaches in the river network;

[0007] According to the calculated river grading, set up a mapping table between the river grading and the WRF-Hydro river confluence parameters;

[0008] According to the initial values of the river confluence parameters, simulate several flood events and calculate the simulation performance evaluation index;

[0009] Using the dynamic dimension search algorithm, with the observed flow at the outlet river reach of the river network as the reference value, within the value range of the river confluence parameters, use the dynamic dimension search algorithm to calibrate the river confluence parameters corresponding to different river gradings in the mapping table;

[0010] The mapping table contains the initial values and value ranges of different river classification setting parameters.

[0011] As a preferred embodiment of the method for optimizing the layout of wind, light and water energy development in a valley area based on numerical simulation according to the present invention, wherein: calculating the river classification of all river reaches in the river network using the Strahler method is to search all river reaches in the river network. If a river reach has no upstream, the current river reach is the uppermost river reach, and its river classification is set to 1;

[0012] Search for the remaining river reaches in the river network. If the river classifications of the upstream river reaches of a river reach have been determined, and the upstream is a single river reach or multiple river reaches with the same classification, then the classification of the current river reach is the classification of the current river reach's upstream plus one;

[0013] If the river classifications of the upstream river reaches of a river reach have been determined, but there are several upstream river reaches and their river classifications, then the river classification of the current river reach is equal to the maximum classification of the upstream river reaches of the current river reach;

[0014] If there is an upstream river reach without a set river classification for a river reach, then skip the current river reach;

[0015] Traverse all river reaches until the river classifications of all river reaches in the river network are completed.

[0016] As a preferred embodiment of the method for optimizing the layout of wind, light and water energy development in a valley area based on numerical simulation according to the present invention, wherein: setting the mapping table of river classification and WRF-Hydro channel confluence parameters according to the calculated river classification is to determine the hydraulic roughness parameter and the channel cross-section shape parameter according to the river classification and draw the mapping table;

[0017] The hydraulic roughness parameter includes the Manning coefficient;

[0018] The channel cross-section shape parameter includes the channel width and the slope gradient;

[0019] The mapping table includes river classification, initial value of Manning coefficient, maximum and minimum values of Manning coefficient, initial value of channel width, maximum and minimum values of channel width, initial value of slope gradient, maximum and minimum values of slope gradient.

[0020] As a preferred embodiment of the method for optimizing the layout of wind, light and water energy development in a valley area based on numerical simulation according to the present invention, wherein: simulating several flood events according to the initial values of the channel confluence parameters and calculating the simulation performance evaluation index is to use the flow observation data of the river reaches near the river network outlet as reference data and select several events arbitrarily during the flood process;

[0021] Based on the initial values of river confluence parameters in the mapping table, use WRF-Hydro to simulate the selected flood process and calculate the evaluation indicators for each flood process;

[0022] Set the passing criteria corresponding to the selected evaluation indicators. If all the evaluation indicators of a flood event are higher than the passing criteria of the corresponding indicators, then the current flood event is a passing event; where all the evaluation indicators are the indicators arbitrarily selected by the user from the selected evaluation indicators, and the passing criteria are the passing thresholds of the corresponding indicators;

[0023] The selected evaluation indicators include the Nash coefficient, the relative deviation of flood volume, and the error of peak occurrence time;

[0024] The passing rate is equal to the proportion of the number of passing events in the total number of selected events.

[0025] As a preferred scheme of a method for optimizing the layout of wind-solar-hydro energy development in a valley area based on numerical simulation according to the present invention, wherein: using the dynamic dimension search algorithm, taking the observed flow at the outlet section of the river network as a reference value, within the value range of the river confluence parameters, using the dynamic dimension search algorithm to calibrate the river confluence parameters corresponding to different river classifications in the mapping table includes,

[0026] Set the parameters of the dynamic dimension search algorithm. For all the parameters to be calibrated in the river confluence parameter classification mapping table, generate a random number p in sequence, where p takes the value of 0 or 1, and the probability of taking 1 is where i is the current search times;

[0027] If the random number p takes the value of 1, then select the current parameter. If no parameter is selected, randomly select one from all the parameters to be calibrated, and the probability of each parameter being selected is equal;

[0028] For each selected parameter, generate a random number σ, calculate the perturbation amount of each selected parameter, where σ conforms to a normal distribution with a mean of 0 and a standard deviation of 1, and the perturbation amount is equal to the product of the random number σ and the difference between the maximum value and the minimum value of the value range;

[0029] For each selected parameter, on the basis of the current value, add the perturbation amount as a guessed value, and establish a river confluence parameter classification guessed mapping table;

[0030] If the guessed value is greater than the maximum value of the parameter, then update the guessed value to 2 times the maximum value minus the guessed value;

[0031] If the updated guessed value is less than the minimum value of the parameter, then update the guessed value to the minimum value of the parameter again;

[0032] If the guessed value is less than the minimum value of the parameter, then update the guessed value to 2 times the minimum value minus the guessed value;

[0033] If the updated guessed value is greater than the maximum value of the parameter, the guessed value is updated again to the maximum value of the parameter.

[0034] As a preferred solution of a method for optimizing the layout of wind, light and water energy development in a river valley area based on numerical simulation according to the present invention, wherein: the use of the dynamic dimension search algorithm, with the observed flow at the outlet section of the river network as the reference value, within the value range of the river channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table further includes

[0035] According to the river channel confluence parameter classification guess mapping table, the perturbation amount of each selected parameter is recalculated, and the qualification rate is calculated;

[0036] If the qualification rate of the river channel confluence parameter classification guess mapping table is better than the qualification rate of the current mapping table, the parameters in the updated river channel confluence parameter classification mapping table are taken, and the guessed value is used as the new value.

[0037] As a preferred solution of a method for optimizing the layout of wind, light and water energy development in a river valley area based on numerical simulation according to the present invention, wherein: the use of the dynamic dimension search algorithm, with the observed flow at the outlet section of the river network as the reference value, within the value range of the river channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table further includes

[0038] The dynamic dimension search algorithm is used to repeat the calibration of the river channel confluence parameters corresponding to different river classifications in the mapping table several times, and the final value of the river channel confluence parameter classification mapping table is used as the calibrated value of the river channel confluence parameters.

[0039] A computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of a method for optimizing the layout of wind, light and water energy development in a river valley area based on numerical simulation as described above are implemented.

[0040] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of a method for optimizing the layout of wind, light and water energy development in a river valley area based on numerical simulation as described above are implemented.

[0041] Advantages of the present invention: The method of the present invention can greatly reduce the number of river channel confluence parameters to be calibrated, thereby automatically adjusting and calibrating the confluence parameters of different river classifications in the WRF-Hydro model, reducing the interference of human factors, improving the accuracy of river channel flow simulation, and providing strong technical support for water resource management and flood warning. Description of the Drawings

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0043] Figure 1 It is the overall flowchart of an optimization method for the development layout of wind, light, and water energy in a river valley area based on numerical simulation provided by the first embodiment of the present invention.

[0044] Figure 2 It is the schematic diagram of Strahler river classification for all river reaches in the Yangtze River Basin in an optimization method for the development layout of wind, light, and water energy in a river valley area based on numerical simulation provided by the third embodiment of the present invention. Detailed implementation manners

[0045] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific implementation manners of the present invention with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment 1, refer to Figure 1 For an embodiment of the present invention, an optimization method for the development layout of wind, light, and water energy in a river valley area based on numerical simulation is provided, including:

[0047] Use the Strahler method to calculate the river classification of all river reaches in the river network.

[0048] According to the calculated river classification, set a mapping table between the river classification and the WRF-Hydro channel confluence parameters, and the mapping table includes the initial values and value ranges of the set parameters for different river classifications.

[0049] According to the initial values of the channel confluence parameters, simulate several flood events and calculate the simulation performance evaluation indicators.

[0050] Using the dynamic dimension search algorithm, with the observed flow at the outlet reach of the river network as the reference value, within the value range of the channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the channel confluence parameters corresponding to different river classifications in the mapping table.

[0051] Specifically, step 1 includes:

[0052] Search all river reaches in the river network. If a river reach has no upstream, it is the uppermost river reach, and its river order is set to 1.

[0053] Search the remaining river reaches in the river network. If the river orders of the upstream river reaches of a river reach have been determined, and the upstream is a single river reach or multiple river reaches with the same river order, then the river order of this river reach is one more than its upstream river order; if the river orders of the upstream river reaches of a river reach have been determined, but there are multiple upstream river reaches and they have different river orders, then the river order of this river reach is equal to the maximum river order of its upstream river reaches; if there are river reaches with undetermined river orders upstream of a river reach, then skip this river reach.

[0054] Repeat the previous step until the river orders of all river reaches in the river network have been set. Figure 1 It is a schematic diagram of the Strahler river order for the Chinese region.

[0055] Furthermore, it should be noted that:

[0056] As the resolution of the river network increases, the number of river reaches increases significantly. If each river reach has completely independent hydraulic parameters, the computational effort required to calibrate the hydraulic parameters of more than 10,000 river reaches will exceed the current development level of computers. Based on the understanding that "river reaches with the same Strahler order have similar hydraulic properties", the present invention establishes a method for calibrating river hydraulic parameters based on Strahler river reach order, which greatly reduces the computational effort required for calibration.

[0057] Specifically, step 2 includes:

[0058] The WRF-Hydro model channel routing parameters in the mapping table include the hydraulic roughness parameter and the channel cross-section shape parameter. The hydraulic roughness parameter is the Manning coefficient N, and the channel cross-section shape parameters include the bottom width Bw and the side slope gradient Z.

[0059] Set the initial values and value ranges of the routing parameters for each level of the river channels. One setting is as shown in the appendix Figure 2 as shown.

[0060] Specifically, step 3 includes:

[0061] Use the flow observation data of the river reaches near the river network outlet as the reference data.

[0062] Select several flood processes according to the flow observation data.

[0063] Based on the initial values of the channel routing parameters set in step 2, use WRF-Hydro to simulate the selected flood processes and calculate the evaluation indicators for each flood process.

[0064] Evaluation indicators can be selected according to needs. Commonly used indicators include Nash-Sutcliffe Efficiency (NSE), relative deviation of flood volume (Pb), and error of peak time (Pb).

[0065] Calculate the pass rate or average evaluation indicator. Set the pass criteria corresponding to the selected indicators. If all evaluation indicators of a flood event are higher than the pass criteria of the corresponding indicators, then the simulation of this flood event is qualified. The pass rate is equal to the ratio of the number of qualified flood events to the total number of flood events. If the total number of flood events is small, you can also select one evaluation indicator and calculate the average value of the evaluation indicators of all flood events.

[0066] Specifically, step 4 includes:

[0067] First, set the parameters of the dynamic dimension search algorithm, including the perturbation size r and the maximum number of searches m. Among them, the perturbation size is generally set to 0.2, and the maximum number of searches can be set to 2000.

[0068] Second, for all the parameters to be calibrated in the river confluence parameter classification mapping table, generate a random number p in sequence. The value of p is 0 or 1, and the probability of taking the value 1 is where i is the current search number. If p takes the value 1, then select this parameter. If no parameter is selected, randomly select one from all the parameters to be calibrated, and the probability of each parameter being selected is equal.

[0069] Third, for each selected parameter, generate a random number σ that follows a normal distribution with a mean of 0 and a standard deviation of 1, and calculate the perturbation amount of each selected parameter. The perturbation amount is equal to the product of the random number σ and the value range (maximum value minus minimum value).

[0070] Fourth, for each selected parameter, on the basis of the current value, add the perturbation amount as the guessed value, and establish a river confluence parameter classification guessed mapping table. If the guessed value is greater than the maximum value of the parameter, update the guessed value to 2 times the maximum value minus the guessed value; if the updated guessed value is less than the minimum value of the parameter, update the guessed value to the minimum value of the parameter again. If the guessed value is less than the minimum value of the parameter, update the guessed value to 2 times the minimum value minus the guessed value; if the updated guessed value is greater than the maximum value of the parameter, update the guessed value to the maximum value of the parameter again.

[0071] Fifth, according to the river confluence parameter classification guessed mapping table, repeat step 3 to calculate the simulation performance evaluation indicator.

[0072] Sixth, if the simulation performance of the river confluence parameter classification guessed mapping table is better than that of the current mapping table, update the parameters in the river confluence parameter classification mapping table with the guessed value as the new value.

[0073] Repeat steps two to six several times, and use the final value of the river confluence parameter classification mapping table as the calibrated value of the river confluence parameter.

[0074] Embodiment 2 is an embodiment of the present invention.

[0075] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., which can store program codes.

[0076] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0077] More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), fiber optic devices, and portable compact disc read-only memories (CDROMs). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then stored in a computer memory.

[0078] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above 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, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0079] Example 3. In this example, in order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. In this example, experiments are respectively conducted on the existing traditional method and the method of this example.

[0080] Refer to Figure 2 As shown, the Yangtze River Basin includes approximately 50,000 river reaches, and each river reach has three parameters to be calibrated, namely N, Bw, and Z, with a total of approximately 150,000 parameters to be determined. The traditional calibration method cannot calibrate these parameters. The present invention combines Strahler river classification to calibrate the three parameters to be determined at different levels from 1 to 8, with a total of 24 parameters, greatly reducing the number of parameters to be calibrated, so that an automated parameter calibration can be performed using a dynamic dimension search algorithm.

[0081] Table 1 Example of mapping between river grades and WRF-Hydro model parameters

[0082]

[0083]

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. An optimization method for the development layout of river valley area wind-solar-hydro energy based on numerical simulation, characterized in that, Including: Calculating the river classification of all river reaches in the river network using the Strahler method; Setting up a mapping table between river classification and WRF-Hydro channel confluence parameters according to the calculated river classification; Simulating several flood events based on the initial values of the channel confluence parameters and calculating the simulation performance evaluation indicators; Using the dynamic dimension search algorithm, with the observed flow at the outlet reach of the river network as the reference value, within the value range of the channel confluence parameters, calibrating the channel confluence parameters corresponding to different river classifications in the mapping table using the dynamic dimension search algorithm; The mapping table contains the initial values and value ranges of the set parameters for different river classifications.

2. The optimization method for the development layout of river valley area's wind-solar-hydro energy based on numerical simulation as claimed in claim 1, wherein: The calculating the river classification of all river reaches in the river network using the Strahler method is to search all river reaches in the river network. If a river reach has no upstream, the current reach is the uppermost reach and its river classification is set to 1; Searching the remaining river reaches in the river network. If the river classifications of the upstream reaches of a river reach have been determined and the upstream is a single reach or multiple reaches with the same classification, the classification of the current reach is the classification of the upstream reach of the current reach plus one; If the river classifications of the upstream reaches of a river reach have been determined, but there are several upstream reaches and different river classifications, the river classification of the current reach is equal to the maximum classification of the upstream reaches of the current reach; If there is an upstream reach of a river reach whose river classification has not been set, skip the current reach; Traversing all river reaches until the river classifications of all river reaches in the river network are completed.

3. The optimization method for the development layout of river valley area wind-solar-hydro energy based on numerical simulation according to claim 2, characterized in that: The setting up a mapping table between river classification and WRF-Hydro channel confluence parameters according to the calculated river classification is to determine the hydraulic roughness parameter and the channel cross-section shape parameter according to the river classification and draw the mapping table; The hydraulic roughness parameter includes the Manning coefficient; The channel cross-section shape parameter includes the channel width and the side slope gradient; The mapping table includes river classification, initial value of Manning coefficient, maximum and minimum values of Manning coefficient, initial value of channel width, maximum and minimum values of channel width, initial value of side slope gradient, maximum and minimum values of side slope gradient.

4. The optimization method for the development layout of river valley area wind-solar-hydro energy based on numerical simulation according to claim 3, characterized in that: The simulating several flood events based on the initial values of the channel confluence parameters and calculating the simulation performance evaluation indicators is to use the flow observation data at the reach near the outlet of the river network as the reference data and arbitrarily select several events during the flood process; Based on the initial values of the channel confluence parameters in the mapping table, using WRF-Hydro to simulate the selected flood process and calculate the evaluation indicators for each flood event; Setting the qualified standard corresponding to the selected evaluation indicators. If all the evaluation indicators of a flood event are higher than the qualified standard of the corresponding indicators, the current event is a qualified event; where all the evaluation indicators are arbitrarily selected by the user from the selected evaluation indicators, and the qualified standard is the qualified threshold of the corresponding indicators; The selected evaluation indicators include the Nash coefficient, relative deviation of flood volume, and peak time error; The qualified rate is equal to the proportion of the number of qualified events in the total number of selected events.

5. The optimization method for the development layout of river valley area wind-solar-hydro energy based on numerical simulation according to claim 4, characterized in that: Using the dynamic dimension search algorithm, with the observed flow at the outlet reach of the river network as the reference value, within the value range of the river channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table, including Set the parameters of the dynamic dimension search algorithm. For all the parameters to be calibrated in the river confluence parameter classification mapping table, a random number p is generated in sequence. The value of p is 0 or 1, and the probability of taking 1 is where i is the current number of searches; If the random number p takes the value of 1, the current parameter is selected; if no parameter is selected, a parameter is randomly selected from all the parameters to be calibrated, and the probability of each parameter being selected is equal. For each selected parameter, a random number σ is generated, and the perturbation amount of each selected parameter is calculated, where σ follows a normal distribution with a mean of 0 and a standard deviation of 1, and the perturbation amount is equal to the product of the random number σ and the difference between the maximum value and the minimum value of the value range. For each selected parameter, on the basis of the current value, the perturbation amount is added as the guessed value, and a river channel confluence parameter classification guessed mapping table is established. If the guessed value is greater than the maximum value of the parameter, update the guessed value to 2 times the maximum value minus the guessed value. If the updated guessed value is less than the minimum value of the parameter, update the guessed value to the minimum value of the parameter again. If the guessed value is less than the minimum value of the parameter, update the guessed value to 2 times the minimum value minus the guessed value. If the updated guessed value is greater than the maximum value of the parameter, update the guessed value to the maximum value of the parameter again.

6. The optimization method for the development layout of river valley area wind-solar-hydro energy based on numerical simulation according to claim 5, characterized in that: Using the dynamic dimension search algorithm, with the observed flow at the outlet reach of the river network as the reference value, within the value range of the river channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table also includes According to the river channel confluence parameter classification guessed mapping table, the perturbation amount of each selected parameter is recalculated, and the qualification rate is calculated. If the qualification rate of the river channel confluence parameter classification guessed mapping table is better than that of the current mapping table, update the parameters in the river channel confluence parameter classification mapping table, and use the guessed value as the new value.

7. The optimization method for the development layout of river valley area's wind-solar-hydro energy based on numerical simulation according to claim 6, characterized in that: Using the dynamic dimension search algorithm, with the observed flow at the outlet reach of the river network as the reference value, within the value range of the river channel confluence parameters, the dynamic dimension search algorithm is used to calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table also includes Use the dynamic dimension search algorithm to repeatedly calibrate the river channel confluence parameters corresponding to different river classifications in the mapping table for several times, and use the final value of the river channel confluence parameter classification mapping table as the calibrated value of the river channel confluence parameters.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for optimizing the layout of wind, light and water energy development in the valley area based on numerical simulation according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for optimizing the layout of wind, light and water energy development in the valley area based on numerical simulation according to any one of claims 1 to 6.

Images