Water resource optimal configuration method considering over-water-supply regulation and hierarchical constraint

Abstract

The invention provides a water resource optimal configuration method considering excess water supply regulation and control and hierarchical constraint, and the method comprises the steps: obtaining water resource configuration parameter data, constructing a basic water resource optimal configuration model, constructing a hierarchical constraint system, constructing a multi-target water resource optimal configuration model, and solving the water resource optimal configuration model. And obtaining an optimal water resource allocation scheme. According to the method, on the premise that regional water consumption red line constraints are guaranteed, collaborative optimization of economic benefits, water shortage control and water consumption rationality is achieved, scientificity, engineering performability and management adaptability of a configuration scheme are improved, and support is provided for actual water resource scheduling and management decision making.

Description

A method for optimal allocation of water resources considering excess water supply regulation and stratified constraints Technical Field

[0001] This invention belongs to the field of water resource optimization and scheduling decision-making technology, and specifically relates to a water resource optimization method that considers excess water supply regulation and hierarchical constraints. Background Technology

[0002] Optimal allocation of water resources is a key technology in regional water resource management, water resource scheduling decisions, and sustainable water resource utilization. Existing water resource allocation methods typically treat factors such as available water supply, regional total water consumption control targets, and water user demand as constraints. In some studies, water user demand is treated as a fixed value, suitable for scenarios with stable water demand structures. In other studies, water user demand is set as a demand range to reflect the uncertainty or flexibility of water demand, and the scale of water supply is limited by setting a maximum demand constraint.

[0003] However, existing methods still have certain shortcomings in situations involving multiple water sources, multiple water users, and flexible water demand regulation. In actual water resource management and scheduling, different types of constraints differ significantly in their management attributes and engineering significance. Constraints on available water supply and regional total water consumption control are typically rigid constraints; violations of these constraints directly impact regional water security or exceed water consumption limits. In contrast, the maximum water demand of water users is more of a reasonable upper limit for water use or absorption capacity, exhibiting a certain degree of regulatory flexibility under certain conditions. Treating these constraints of different natures together as rigid constraints can easily lead to a limited feasible solution space in the optimization model, and in some cases, even result in a problem with no feasible solution.

[0004] Furthermore, in the process of optimizing water resource allocation with the goal of maximizing economic benefits, even under the premise of meeting the constraints of water source supply capacity and regional total water consumption control, water supply schemes may still result in individual water users exceeding their reasonable water demand limits. Existing methods typically avoid this problem by directly limiting the maximum water demand. However, this approach only treats over-supply as a violation of constraints, lacking a quantitative characterization and control mechanism for the degree of over-supply. It is difficult to achieve a fine balance between economic benefits, water shortage, and the rationality of water use, thus affecting the engineering feasibility and management adaptability of the allocation results, making it difficult to directly apply the optimization results to actual scheduling and management decisions.

[0005] Therefore, there is an urgent need for a water resource optimization allocation method that can distinguish different types of constraints, quantitatively regulate the excess water supply of water users, and achieve multi-objective collaborative optimization under the premise of ensuring regional water use red line constraints, so as to improve the scientificity and practicality of water resource allocation schemes. Summary of the Invention

[0006] The purpose of this invention is to address the problems in existing water resource allocation methods, where rigid treatment of constraints of different properties leads to limited or even infeasible solution spaces, and the lack of quantitative characterization and control mechanisms for water users' excess water supply. This makes it difficult to achieve a fine balance between economic benefits, water shortage, and water use rationality. The invention provides a water resource optimization allocation method that considers excess water supply control and hierarchical constraints. Under the premise of ensuring regional water use red line constraints, it achieves synergistic optimization of economic benefits, water shortage control, and water use rationality, improves the scientific nature, engineering feasibility, and management adaptability of the allocation scheme, and provides support for actual water resource scheduling and management decisions.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] This invention provides a method for optimal allocation of water resources considering excess water supply regulation and stratified constraints, characterized in that the method includes the following steps:

[0009] Step 1, Obtain water resource allocation parameter data:

[0010] The study collected parameters on the water supply capacity of various water sources within the research area, the water demand range parameters of each water user, the total water consumption control indicators of the region, the economic benefits per unit volume of water supplied by each water source to each water user, and the total water demand parameters of each water user.

[0011] Step 2, construct a basic water resource optimization allocation model:

[0012] Based on the parameters obtained in step 1, and with the water supply from each water source to each water user as the decision variable, a basic water resource optimization allocation model is constructed with the dual optimization objectives of maximizing economic benefits and minimizing the total regional water shortage.

[0013] Step 3, construct a hierarchical constraint system:

[0014] A hierarchical constraint system is constructed for the basic water resource optimization allocation model obtained in step 2. The constraints on the available water supply of each water source and the total water consumption control of the region are set as hard constraints, while the constraints on the maximum water demand planned by water users are set as soft constraints that allow for tolerable oversupply. This system is used to characterize the reasonable upper limit of water consumption or the absorption capacity of water users.

[0015] Step 4: Construct a multi-objective water resource optimization allocation model:

[0016] The violation of the soft constraints in step 3 is quantified, and an excess water supply regulation target is constructed to characterize the degree of excess water supply. The excess water supply regulation target, together with the economic benefit maximization target and the regional total water shortage minimization target in step 2, constitute a multi-objective water resource optimization allocation model.

[0017] Step 5: Solve the water resource optimization allocation model.

[0018] A multi-objective optimization algorithm is used to solve the multi-objective water resource optimization allocation model described in step 4 to obtain a non-dominated solution set that satisfies the hard constraints.

[0019] Step 6: Obtain the optimal water resource allocation plan

[0020] Based on the preset decision rules, water resource optimization allocation schemes that take into account water shortage, excess water supply and economic benefits are selected from the non-dominated solution set, thereby completing the water resource optimization allocation in the study area.

[0021] Furthermore, in step 2, the objective function for maximizing economic benefits is:

[0022]

[0023] The objective function for minimizing the total water shortage in the region is:

[0024]

[0025] The constraint functions include:

[0026]

[0027]

[0028]

[0029]

[0030] In the formula, This represents the economic benefit generated by a unit volume of water supplied from the i-th water source to the j-th water user. This represents the amount of water supplied from the i-th water source to the j-th water user. This represents the total water consumption of user j. This indicates the maximum available water volume of water source i. This represents the minimum water demand planned by water user j. This represents the maximum planned water demand of user j. Let n be the total water supply control value for the study area, n be the number of water sources, and m be the number of water users.

[0031] Furthermore, in step 3, the hard constraint includes:

[0032] The total water supply from each water source to all water users shall not exceed the corresponding water supply capacity, and the total water supply from all water sources within the study area shall not exceed the regional total water consumption control target.

[0033] Furthermore, in step 4, the violation of the soft constraint mentioned in step 3 is quantified. The quantification method is as follows: calculate the difference between the actual total water supply of a single water user and the planned maximum water demand of that water user. If the actual total water supply exceeds the planned maximum water demand, the excess part is the soft constraint violation amount of that water user; if it does not exceed, the soft constraint violation amount is zero.

[0034] The total amount of soft constraint violations by all water users is aggregated or weighted to quantify the overall situation of soft constraint violations, thereby determining the target for controlling excess water supply.

[0035] Furthermore, in step 4, the objective function for regulating excess water supply is:

[0036]

[0037] In the formula, This represents the amount of water supplied from the i-th water source to the j-th water user. This represents the maximum planned water demand of water user j, n is the number of water supply sources, and m is the number of water users.

[0038] Furthermore, in step 5, the multi-objective optimization algorithm prioritizes ensuring the satisfaction of hard constraints during the solution process, and performs coordinated optimization of the objectives of maximizing economic benefits, minimizing the total regional water shortage, and regulating excess water supply, provided that the hard constraints are satisfied.

[0039] Furthermore, in step 6, the decision rule includes:

[0040] Under the premise of meeting the hard constraints, the solution with the smaller excess water supply control target value is selected first. Then, in the solution set where the excess water supply control target value is within the preset tolerance range, the solution with the better economic benefit target is selected as the final water resource optimization allocation scheme.

[0041] The advantages of this invention compared to the prior art are as follows:

[0042] 1. This invention treats water resource allocation constraints in a hierarchical manner, treating the constraints on available water supply and regional water consumption control as hard constraints that must be strictly met, while setting the constraint on the maximum water demand of water users as a soft constraint that can be adjusted within a preset range. By distinguishing the constraint strength of different constraints from the perspectives of management attributes and engineering significance, this invention effectively avoids the problem of limited or infeasible solution space caused by rigidly treating constraints of different natures together, thereby improving the stability and applicability of the water resource optimization allocation model.

[0043] 2. By introducing the target of excess water supply regulation, this invention transforms the over-supply behavior of water users from a simple constraint judgment into a quantifiable and weighable optimization target. This allows the degree of over-supply to be synergistically optimized with economic benefit targets and water shortage targets within a multi-objective optimization framework. Thus, under the premise of meeting the regional water use red line constraints, a fine balance is achieved between economic benefits, water shortage control and water use rationality.

[0044] 3. Based on the above-mentioned hierarchical constraints and excess water supply regulation mechanism, this invention can obtain a water resource optimization scheme that takes into account economic benefits, water shortage and excess supply control in complex situations with multiple water sources, multiple water users and water demand with regulatory flexibility. This improves the engineering feasibility and management adaptability of the allocation results, making the optimization results easier to apply directly to actual water resource scheduling and management decisions. Attached Figure Description

[0045] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0046] Figure 1 illustrates three representative water resource allocation schemes described in the application examples;

[0047] Figure 2 is a comparison of the objective function values ​​of economic benefits, water shortage, and excess water supply under different water resource allocation schemes. Detailed Implementation

[0048] The embodiments described are provided to better illustrate the present invention, but are not intended to limit the scope of the invention to the embodiments described. Therefore, non-essential improvements and adjustments made to the embodiments by those skilled in the art based on the above description are still within the scope of protection of the present invention.

[0049] The endpoints and any values ​​of the ranges disclosed herein are not limited to the precise ranges or values, and these ranges or values ​​should be understood to include values ​​close to these ranges or values. For numerical ranges, the endpoint values ​​of the various ranges, the endpoint values ​​of the various ranges and individual point values, and individual point values ​​can be combined with each other to obtain one or more new numerical ranges, which should be considered as specifically disclosed herein.

[0050] The present invention will be described in detail below through embodiments. It should be understood that the following embodiments are only used to exemplify and further explain and illustrate the content of the present invention, and are not intended to limit the present invention.

[0051] Example 1

[0052] This embodiment provides a method for optimizing water resource allocation that considers excess water supply regulation and stratified constraints, including the following steps:

[0053] Step 1, Obtain water resource allocation parameter data:

[0054] The study collected parameters on the water supply capacity of various water sources within the research area, the water demand range parameters of each water user, the total water consumption control indicators for the region, the economic benefits per unit volume of water supplied by each water source to each water user, and the total water demand parameters of each water user.

[0055] Step 2, construct a basic water resource optimization allocation model:

[0056] Based on the parameters obtained in step 1, and taking the water supply from each water source to each water user as the decision variable, a basic water resource optimization allocation model is constructed with the dual optimization objectives of maximizing economic benefits and minimizing the total regional water shortage.

[0057] The objective function for maximizing economic benefits is:

[0058]

[0059] The objective function for minimizing the total water shortage in the region is:

[0060]

[0061] The constraint functions include:

[0062]

[0063]

[0064]

[0065]

[0066] In the formula, This represents the economic benefit generated by a unit volume of water supplied from the i-th water source to the j-th water user, expressed in yuan / ; This represents the water supply from the i-th water source to the j-th water user, in ten thousand units. ; This represents the total water consumption of user j, in ten thousands. ; This represents the maximum available water volume of water source i, in ten thousand units. ; This represents the minimum planned water demand for user j, in ten thousand units. ; This represents the maximum planned water demand of user j, in ten thousand units. ; The total water supply control value for the study area is 10,000. n represents the number of water sources, and m represents the number of water users.

[0067] Step 3, construct a hierarchical constraint system:

[0068] A hierarchical constraint system is constructed for the basic water resource optimization allocation model obtained in step 2. The constraints on the available water supply of each water source and the total regional water consumption control are set as hard constraints, while the constraints on the maximum water demand planned by water users are set as soft constraints that allow for tolerable oversupply. This system is used to characterize the reasonable upper limit of water consumption or the absorption capacity of water users.

[0069] The hard constraints include: the total water supply from each water source to all water users shall not exceed the corresponding water supply capacity, and the total water supply from all water sources within the study area shall not exceed the regional water consumption control target.

[0070] Step 4: Construct a multi-objective water resource optimization allocation model:

[0071] The violation of the soft constraint described in step 3 is quantified by calculating the difference between the actual total water supply of a single water user and the planned maximum water demand of that user. If the actual total water supply exceeds the planned maximum water demand, the excess is the soft constraint violation amount of that water user; if it does not exceed the planned maximum water demand, the soft constraint violation amount is zero.

[0072] The soft constraint violations of all water users are summarized or weighted, with the weighting coefficient set according to the type of water user, water source type, or regional management requirements. This completes the overall quantification of soft constraint violations, thereby constructing an oversupply volume control target to characterize the degree of oversupply. The oversupply volume control target, together with the economic benefit maximization target and the regional total water shortage minimization target mentioned in step 2, constitute a multi-objective water resource optimization allocation model.

[0073] The objective function for regulating excess water supply is:

[0074]

[0075] In the formula, This represents the water supply from the i-th water source to the j-th water user, in ten thousand units. ; This represents the maximum planned water demand of user j, in ten thousand units. n represents the number of water sources, and m represents the number of water users.

[0076] Step 5: Solve the water resource optimization allocation model.

[0077] A multi-objective optimization algorithm is used to solve the multi-objective water resource optimization allocation model described in step 4 to obtain a non-dominated solution set that satisfies the hard constraints.

[0078] Specifically, the multi-objective optimization algorithm prioritizes satisfying hard constraints during the solution process, and then performs coordinated optimization of the objectives of maximizing economic benefits, minimizing total regional water shortage, and regulating excess water supply, all while ensuring that the hard constraints are met.

[0079] Step 6: Obtain the optimal water resource allocation plan

[0080] Based on the preset decision rules, water resource optimization allocation schemes that take into account water shortage, excess water supply and economic benefits are selected from the non-dominated solution set, thereby completing the water resource optimization allocation in the study area.

[0081] The decision-making rules include: under the premise of meeting hard constraints, prioritizing the selection of solutions with smaller excess water supply control target values, and selecting the solution with better economic benefit as the final water resource optimization allocation scheme from the solution set where the excess water supply control target value is within the preset tolerance range.

[0082] In one embodiment of the method described in this example, the water demand of a user is set to a fixed value, and no maximum water demand constraint is set for the user in this embodiment. In another embodiment of the method, the water demand of a user is set as a water demand range, and the excess water supply is regulated by setting the maximum water demand of the user as a soft constraint that can tolerate oversupply.

[0083] Application Examples

[0084] This application example selects a water-scarce region in northern China as the research area and uses the method described in Example 1 to optimize water resource allocation.

[0085] The study area is located in the arid inland hinterland of northern my country, characterized by drought and low rainfall, and is considered one of the most water-scarce regions. With the continuous population growth, rapid economic development, and accelerating urbanization, coupled with rising living standards and improved ecological environment, water demand is constantly increasing, exacerbating the water supply-demand imbalance. The study area comprises seven irrigation districts, each with a water use structure consisting of residential water use, agricultural water use (including poultry water use), industrial water use, construction water use, tertiary sector water use, and urban environmental water use. Water sources include both surface water and groundwater. This application example uses 2020 water supply and demand data and water use efficiency data for this region to calculate the optimal allocation of water resources from both sources to the seven irrigation districts, specifically including:

[0086] Step 1: Obtain water resource allocation parameter data: Collect the total water consumption control index for the study area in 2020, the water demand range data for each irrigation district, the water supply capacity data of each water source, the economic benefit parameters of each water source supplying water to each irrigation district, and the total water demand parameters of each irrigation district.

[0087] Step 2: Construct a basic water resource optimization allocation model: With the dual optimization objectives of maximizing economic benefits and minimizing the total regional water shortage, and with the water supply from each water source to each irrigation area as the decision variable, construct a basic water resource optimization allocation model.

[0088] In this application example, m = 7 and n = 2.

[0089] Step 3, construct a hierarchical constraint system: Define the constraints in the constraints as hard constraints, such as the total water supply from each water source to all water users not exceeding the corresponding water supply capacity, the total water supply from all water sources in the study area not exceeding the regional water consumption control index, the non-negative water supply constraint, and the water supply being greater than or equal to the minimum water demand of the water users. Set the maximum water demand constraint of the water users as a soft constraint that allows for tolerable oversupply.

[0090] Step 4, Construct a multi-objective water resource optimization model: Construct an objective function for regulating excess water supply to characterize the degree of excess water supply. .

[0091] Step 5, Solve the water resource allocation model: The water resource allocation model is solved using a multi-objective optimization algorithm. The non-dominated solution set that satisfies the hard constraints is shown in Figure 1. All allocation schemes satisfy the hard constraints. The objective function values ​​of the three water resource allocation schemes are shown in Figure 2.

[0092] Step 6: Obtain the optimal water resource allocation plan:

[0093] As shown in Figure 2, Scheme A1, guided by maximizing economic benefits, has a high level of economic efficiency. However, its corresponding target value for controlling excess water supply is relatively large, indicating that in the process of pursuing economic benefits, the water supply of some water users has significantly exceeded their reasonable water demand limit. Scheme A2 is characterized by minimizing excess water supply, which almost eliminates the over-supply behavior of water users, but its economic efficiency is relatively low and the regional water shortage is relatively large. Scheme A3 achieves a relatively balanced compromise among the three objectives of economic benefits, water shortage, and excess water supply. While significantly reducing excess water supply, it still maintains a high level of economic efficiency and an acceptable level of water shortage control.

[0094] Therefore, option A3 was selected as the optimal option for water resource allocation in the study area.

[0095] The results of this application example further demonstrate that the method described in this application, by introducing excess water supply control targets and performing hierarchical processing of water resource allocation constraints, can achieve synergistic optimization between economic benefits, water shortage control, and water use rationality while meeting regional water use red line constraints, providing a variety of optional and engineering-executable configuration schemes for actual water resource scheduling and management.

[0096] Finally, it should be noted that the above is only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention (such as the application of various formulas, the order of steps, etc.) without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimal allocation of water resources considering excess water supply regulation and stratified constraints, characterized in that, The method includes the following steps: Step 1, acquiring water resource allocation parameter data: collecting water supply capacity parameters of various water sources within the study area, water demand range parameters of each water user, regional total water consumption control indicators, economic benefit parameters per unit volume of water supplied by each water source to each water user, and total water demand parameters of each water user; Step 2, constructing a basic water resource optimization allocation model: based on the parameters acquired in Step 1, and using the water supply from each water source to each water user as the decision variable, constructing a basic water resource optimization allocation model with the dual optimization objectives of maximizing economic benefits and minimizing the total regional water shortage; Step 3, constructing a hierarchical constraint system: constructing a hierarchical constraint system for the basic water resource optimization allocation model constructed in Step 2, setting the water supply capacity constraints of each water source and the regional total water consumption control constraints as hard constraints, and setting the maximum planned water demand constraint of water users as a tolerable oversupply. The soft constraints are used to characterize the reasonable upper limit of water consumption or absorption capacity of water users; Step 4, construct a multi-objective water resource optimization allocation model: quantify the violation of the soft constraints in Step 3, construct an excess water supply control target to characterize the degree of excess water supply, and combine the excess water supply control target with the economic benefit maximization target and the regional total water shortage minimization target in Step 2 to form a multi-objective water resource optimization allocation model; Step 5, solve the water resource optimization allocation model: use a multi-objective optimization algorithm to solve the multi-objective water resource optimization allocation model in Step 4 to obtain a non-dominated solution set that satisfies the hard constraints; Step 6, obtain the optimal water resource allocation scheme: according to the preset decision rules, select a water resource optimization allocation scheme that takes into account water shortage, excess water supply and economic benefits from the non-dominated solution set, thereby completing the water resource optimization allocation of the study area.

2. The water resource optimization allocation method according to claim 1, characterized in that, In step 2, the objective function for maximizing economic benefits is: The objective function for minimizing the total water shortage in the region is: The constraint functions include: In the formula, This represents the economic benefit generated by a unit volume of water supplied from the i-th water source to the j-th water user. This represents the amount of water supplied from the i-th water source to the j-th water user. This represents the total water consumption of user j. This indicates the maximum available water volume of water source i. This represents the minimum water demand planned by water user j. This represents the maximum planned water demand of user j. Let n be the total water supply control value for the study area, n be the number of water sources, and m be the number of water users.

3. The water resource optimization allocation method according to claim 1, characterized in that, In step 3, the hard constraints include: the total water supply from each water source to all water users does not exceed the corresponding water supply capacity, and the total water supply from all water sources within the study area does not exceed the regional water consumption control target.

4. The water resource optimization allocation method according to claim 1, characterized in that, In step 4, the violation of the soft constraint mentioned in step 3 is quantified. The quantification method is as follows: calculate the difference between the actual total water supply of a single water user and the planned maximum water demand of that water user. If the actual total water supply exceeds the planned maximum water demand, the excess part is the soft constraint violation amount of that water user; if it does not exceed, the soft constraint violation amount is zero. The total amount of soft constraint violations by all water users is aggregated or weighted to quantify the overall situation of soft constraint violations, thereby determining the target for controlling excess water supply.

5. The water resource optimization allocation method according to claim 1 or 4, characterized in that, In step 4, the objective function for regulating excess water supply is: In the formula, This represents the amount of water supplied from the i-th water source to the j-th water user. This represents the maximum planned water demand of water user j, n is the number of water supply sources, and m is the number of water users.

6. The water resource optimization allocation method according to claim 1, characterized in that, In step 5, the multi-objective optimization algorithm prioritizes ensuring the satisfaction of hard constraints during the solution process, and performs coordinated optimization of the objectives of maximizing economic benefits, minimizing the total regional water shortage, and regulating excess water supply, under the premise of satisfying the hard constraints.

7. The water resource optimization allocation method according to claim 1, characterized in that, In step 6, the decision rule includes: under the premise of meeting the hard constraints, prioritizing the selection of the solution with the smaller excess water supply control target value, and in the solution set where the excess water supply control target value is within the preset tolerance range, selecting the solution with the better economic benefit target as the final water resource optimization allocation scheme.

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