CN-121981004-A - Multi-model coupling simulation method, optimization method and computer equipment for water system

CN121981004ACN 121981004 ACN121981004 ACN 121981004ACN-121981004-A

Abstract

The application relates to the technical field of water system simulation, in particular to a water system multi-model coupling simulation method, a water system multi-objective optimization method and computer equipment. The multi-model coupling simulation method of the water system comprises the steps of obtaining water consumption data of a first simulation time scale output by a water consumption process model of a target water system and an input data format of a second simulation time scale required by a water network dynamics model, performing time scale conversion on the water consumption data to obtain a water taking time sequence and a water discharging time sequence matched with the second simulation time scale, performing physical constraint consistency verification, configuring the water taking time sequence and the water discharging time sequence as the input data of the water network dynamics model after verification is passed, driving the model to simulate, and calculating water safety indexes, water environment indexes and water ecology indexes. The technical problem of bidirectional fracturing of the water supply and drainage system and the engineering water network system model is solved, and multi-model deep coupling simulation is realized.

Inventors

ZHAO ZHONGNAN
JIANG DACHUAN
XU ZHEN
ZHANG YIQING
GENG XIAOJUN
CHEN YUNFEI
ZENG XIN
LI YUANYUAN
LIU ZHEN
LI YUNLING
YANG MENGQI
YUAN YONG
CHEN KANG
TIAN YING
LI GUANGXUAN

Assignees

水利部水利水电规划设计总院

Dates

Publication Date: 20260505
Application Date: 20260126

Claims (10)

1. The multi-model coupling simulation method for the water system is characterized by comprising the following steps of: acquiring water consumption data of a first simulation time scale output by a water consumption process model of a target water system and an input data format of a second simulation time scale required by a water network dynamics model of the target water system, wherein the second simulation time scale is smaller than the first simulation time scale; Performing time scale conversion on the water consumption data to obtain a water taking time sequence and a water discharging time sequence which are matched with the second simulation time scale; Performing physical constraint consistency check on the water taking time sequence and water supply capacity data of the target water system; If the verification is passed, configuring the water taking time sequence and the water discharging time sequence as input data of the water network dynamics model according to the input data format; Driving the configured water network dynamics model to simulate to obtain water network state variable data; and calculating at least one of a water safety index, a water environment index and a water ecology index based on the water network state variable data.
2. The method of claim 1, wherein, in the case where the first analog time scale is an annual scale and the second analog time scale is a daily scale, the time scale conversion comprises: Total annual water intake Total annual scale drainage Based on the daily allocation coefficient sequence respectively Decomposing to obtain a daily water intake time sequence And daily scale drainage time series ; The decomposition is realized by adopting the following formula: the daily allocation coefficient sequence satisfies 。
3. The method according to claim 1, wherein the physical constraint consistency check is a water resource supply-demand balance check, which is implemented by the following formula: ; Wherein, the Is the first Daily water intake of the individual water unit; Is the first Daily water supply amount of each water supply unit; For the total number of water-using units, Is the total number of water supply units.
4. A method according to any one of claims 1 to 3, wherein the water safety index comprises a flood risk index It is calculated according to the following formula: ; Wherein, the The liquid level of the river channel is the key section of the t day; A safety threshold for the critical section; to indicate the function if and only if The time value is 1, otherwise 0;N is the total days; And/or the water environment index comprises a comprehensive pollution index It is calculated according to the following formula: ; Wherein, the Is the measured concentration of the ith contaminant; an evaluation standard value of the i-th pollutant; the number of contaminant species; And/or the water ecological index comprises minimum ecological flow guarantee rate It is calculated according to the following formula: ; Wherein, the Average flow on day t; The minimum ecological flow is preset; to indicate the function if and only if The time value is 1, otherwise 0;T is the total number of days.
5. A multi-objective optimization method for a water system, comprising: S201, defining decision variable vectors, wherein each decision variable represents the adjustment quantity of controllable elements in a target water system, and the controllable elements comprise water network engineering operation parameters and/or water consumption parameters of a water main body; s202, executing the following substeps for each set of given values of the decision variable vector: generating water use configuration data and water network engineering configuration data based on the set of given values; inputting the water configuration data and the water network engineering configuration data into the multi-model coupling simulation method of the water system according to any one of claims 1 to 4 to obtain corresponding water safety indexes, water environment indexes and water ecology indexes; S203, generating an optimization target based on the water safety index, the water environment index and the water ecology index, and constructing a multi-target optimization problem by taking the decision variable vector as an optimization variable; S204, selecting optimal configuration parameters from the pareto optimal solution set based on an entropy method.
6. The method of claim 5, wherein the water network engineering operation parameters include at least one of a flood level, a profit level, and a discharge flow coefficient of the reservoir, an opening coefficient or an opening-time relationship function parameter of the gate, and a target flow value of the channel; And/or the water consumption parameters of the water consumption main bodies comprise activity level adjustment coefficients and/or water consumption efficiency adjustment coefficients of the water consumption main bodies.
7. The method of claim 5, wherein the optimization objective of the multi-objective optimization problem comprises: the flood risk index is minimized, the comprehensive pollution index is minimized and the ecological flow guarantee rate is maximized.
8. The method of claim 5, wherein the optimization solution using the multi-objective optimization algorithm comprises the steps of: s301, randomly generating a plurality of candidate decision variable vectors to form an initial population; s302, for each candidate decision variable vector in the current population, calculating corresponding water safety indexes, water environment indexes and water ecology indexes through the water system multi-model coupling simulation method to form objective function value vectors; S303, performing non-dominant sorting based on objective function value vectors of all candidate decision variable vectors, and dividing individuals of the current population into non-dominant fronts of different grades; s304, calculating the crowding degree distance of individuals in the same non-dominant front edge; S305, selecting an individual from the current population as a parent by adopting an elite selection strategy based on the non-dominant ranking and the crowding degree distance; s306, intersecting and mutating parent individuals to generate child populations; s307, combining the parent population and the offspring population, and selecting individuals with the same size as the initial population from the parent population and the offspring population to form a new generation population based on non-dominant sorting and crowding distance; s308, repeatedly executing S302 to S307 until a preset termination condition is satisfied, and taking the non-dominant solution set in the final population as the pareto optimal solution set.
9. The method according to claim 5, wherein the selecting the optimal parameter configuration based on the entropy method comprises the steps of: s401, performing standardization processing on the performance index values of all schemes in the pareto optimal solution set: ; Wherein, the An ith performance index value for the jth scenario; And Respectively the maximum value and the minimum value of the ith performance index in all schemes; and (3) the ith performance index value after the standardization of the jth scheme. S402, calculating information entropy of each performance index: ; Wherein, the Information entropy of the ith performance index value; Is the number of schemes; s403, calculating the weight of each performance index: ; Wherein, the The weight of the ith performance index value; Is the number of performance indexes; s404, calculating the comprehensive evaluation value of each scheme: ; Wherein, the The comprehensive evaluation value of the j-th scheme; s405, selecting a scheme with the optimal comprehensive evaluation value as an optimal parameter configuration.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 4 or of claims 5 to 9 when the computer program is executed.

Description

Multi-model coupling simulation method, optimization method and computer equipment for water system Technical Field The application relates to the technical field of water system simulation, in particular to a water system multi-model coupling simulation method, a water system multi-objective optimization method and computer equipment. Background The water system water consumption dynamic simulation method is used for simulating the water consumption dynamic process and the water consumption dynamic process of a water system, and is generally composed of two models, namely a water consumption dynamic process model and a water network dynamic model, wherein the water consumption dynamic process model is used for simulating water taking, water consumption and water discharging activities of various water consumption main bodies such as agriculture, industry, towns and the like in an area, and the water consumption dynamic process model is used for simulating migration and transformation processes of water in river channels, reservoirs and soil in a daily or even hour step. When the overall simulation and optimization application of the water system is constructed, the coupling process of the two models faces at least the following technical problems: Firstly, the space-time scale and the data format among the models are different, specifically, the output of the water using process model comprises but is not limited to the total annual water consumption and the spatial distribution thereof, and the input of the water network dynamics model comprises but is not limited to the daily water intake flow time sequence of a water intake, and the water intake flow time sequence, the space-time scale, the data dimension and the data format are not directly compatible. In practice, a technician is mostly required to manually perform complex data extraction, summarization, downscaling conversion, and format conversion and rewriting of a model input file. The process has low efficiency, long time consumption and low accuracy, so that the simulation result is easy to distort. Secondly, at present, an automatic verification mechanism of a water system simulation model is lacking, for example, the water taking requirement simulated by a water process model should not exceed the actual water supply capacity of a water network system. However, at present, two models often operate independently or operate after simple splicing, and constraint conditions such as water supply capacity of a water network model cannot be fed back to water process simulation automatically in real time, so that invalid simulation of the model is easy to cause, and a large amount of simulation calculation resources are consumed and wasted. Finally, in water systems, water usage affects water network conditions, and changes in water network conditions are constrained to affect water usage. At present, the coupling of the two models is mainly manual coupling, so that real-time bidirectional interaction simulation is difficult to support, and the dynamic response of a simulation system is insufficient. Therefore, a technical scheme for deep coupling of a water process model and a water network dynamics model is needed, so as to solve the technical problems of difficult data butt joint, low simulation efficiency and lack of constraint real-time verification and bidirectional feedback mechanism caused by multimode isomerism. Disclosure of Invention In view of the foregoing, it is necessary to provide a water system multi-model coupling simulation method, a water system multi-objective optimization method, and a computer device. In a first aspect, the present application provides a water system multi-model coupling simulation method, the method comprising: acquiring water consumption data of a first simulation time scale output by a water consumption process model of a target water system and an input data format of a second simulation time scale required by a water network dynamics model of the target water system, wherein the second simulation time scale is smaller than the first simulation time scale; Performing time scale conversion on the water consumption data to obtain a water taking time sequence and a water discharging time sequence which are matched with the second simulation time scale; Performing physical constraint consistency check on the water taking time sequence and water supply capacity data of the target water system; If the verification is passed, configuring the water taking time sequence and the water discharging time sequence as input data of the water network dynamics model according to the input data format; Driving the configured water network dynamics model to simulate to obtain water network state variable data; and calculating at least one of a water safety index, a water environment index and a water ecology index based on the water network state variable data. In some embodiments, where the first analog time scale is an annua