Drainage basin discharge capacity distribution optimization method coupled with ecological compensation model

Abstract

The invention relates to the technical field of hydraulic engineering, and discloses a drainage basin pollution discharge capacity distribution optimization method of a coupling ecological compensation model, comprising the following steps: obtaining drainage basin pollution discharge data; constructing a drainage basin discharge capacity distribution double-layer optimization model by taking minimization of pollution treatment cost as an upper-layer target and maximization of discharge allocation income as a lower-layer target; constructing an ecological compensation model, and coupling the ecological compensation model to the drainage basin discharge capacity distribution double-layer optimization model; a water environment bearing index uncertainty set is introduced into the drainage basin discharge capacity distribution double-layer optimization model of the coupled ecological compensation model, and a drainage basin discharge capacity distribution double-layer robust optimization model of the coupled ecological compensation model is constructed; and solving the drainage basin discharge capacity distribution double-layer robust optimization model coupled with the ecological compensation model to obtain an optimal drainage basin discharge capacity distribution result. According to the invention, the accuracy and response efficiency of drainage basin discharge capacity decision allocation are obviously improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects, and in particular to a watershed sewage discharge allocation optimization method coupled with an ecological compensation model. Background Art

[0002] In pollution control practices, traditional pollutant discharge allocation methods often rely on static indicators, ignoring the hydrological conditions of a river basin, the spatiotemporal heterogeneity of environmental capacity, and the migration and diffusion patterns of pollutants. This leads to a disconnect between total pollutant discharge control and the region's actual carrying capacity. Building a scientifically accurate, dynamically responsive, fair, and efficient intelligent pollutant discharge allocation system to address the inherent flaws of traditional management models has become a pressing issue in water environment governance. Summary of the Invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a watershed discharge optimization method coupled with an ecological compensation model.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is: A method for optimizing watershed discharge allocation coupled with an ecological compensation model includes the following steps: Obtain basin pollution data; A two-level optimization model for watershed pollutant discharge allocation is constructed with minimizing pollution control costs as the upper level goal and maximizing pollutant discharge allocation benefits as the lower level goal. Construct an ecological compensation model and couple it to a two-layer optimization model for watershed discharge allocation; The uncertainty set of water environment carrying index is introduced into the two-level optimization model of watershed discharge allocation coupled with the ecological compensation model, and a two-level robust optimization model of watershed discharge allocation coupled with the ecological compensation model is constructed. The two-layer robust optimization model of watershed discharge allocation coupled with the ecological compensation model is solved to obtain the optimal watershed discharge allocation result.

[0005] Furthermore, with minimizing pollution control costs as the upper-level goal and maximizing pollution discharge allocation benefits as the lower-level goal, a two-level optimization model for basin pollution discharge allocation is constructed, including: Taking minimizing pollution control costs as the upper-level goal, and taking the Gini coefficient constraint of pollutant discharge distribution, water environment carrying index constraint, pollutant discharge demand constraint and parameter non-negativity constraint as the constraint conditions, the upper-level model is constructed; The lower-level model is constructed with the maximization of pollution discharge allocation benefits as the lower-level goal, and the pollutant transfer constraints in each region and the pollutant emissions of each polluting enterprise not exceeding the minimum and maximum demand constraints as constraints; A two-layer optimization model for basin discharge allocation is constructed based on the upper model and the lower model.

[0006] Furthermore, with minimizing the pollution control cost as the upper-level goal, and with the Gini coefficient constraint of pollutant discharge distribution, the water environment carrying index constraint, the pollutant discharge demand constraint, and the parameter non-negative constraint as the constraint conditions, the upper-level model is constructed, specifically: ; st

[0007]

[0008]

[0009]

[0010] in, is the pollution control cost function, x , y is the decision variable; Assigned to the region pollutants The amount of sewage discharged, For the region Allocated to polluting enterprises pollutants The amount of sewage discharged; For the region Medium pollutants governance ratio; For the region Treating pollutants Cost; To allocate to polluting enterprises pollutants the revenue from pollution discharge; , is the weight coefficient, For the region The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region h The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region s The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; For polluting enterprises The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises m The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises n The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; Assigning a Gini coefficient to pollution discharge; For the region Pollutant carrying capacity; , Respectively for regions emission Minimum and maximum required levels of pollutants; I is the number of regions; J is the number of polluting enterprises.

[0011] Furthermore, with maximizing the benefits of pollution discharge configuration as the lower-level goal, and with the pollutant transfer constraints in each region and the pollutant emissions of each polluting enterprise not exceeding the minimum and maximum demand constraints as constraints, the lower-level model is constructed, specifically: ; st

[0012] in, For the region i The pollution discharge configuration income, For the region Allocated to polluting enterprises of the income generated by the emission rights; For the region The pollutants are delivered to the area proportion; , Respectively for regions Medium-sized polluting enterprises emission Minimum and maximum required levels of pollutants; K is the amount of pollutants.

[0013] Furthermore, the construction of the ecological compensation model is as follows:

[0014] in, For the region Horizontal ecological compensation parameters; For the region and region About pollutants Unit horizontal ecological compensation parameters; For the region About pollutants The horizontal ecological compensation standard value; For the region development opportunity costs.

[0015] Furthermore, the uncertainty set of water environment carrying index is introduced into the two-layer optimization model of watershed discharge allocation coupled with the ecological compensation model, including: Convert the water environment carrying index constraint into uncertainty constraint; Set random parameters in the interval Symmetrical distribution is adopted, and the uncertain parameters are characterized according to the nominal value of the regional environmental carrying index and the maximum variation range of the regional environmental carrying index, and the linear constraint of the water environment carrying index is obtained.

[0016] Furthermore, the linear constraint of the water environment carrying index is specifically:

[0017] in, For the region Nominal value of the environmental carrying index, For the region The maximum range of variation of the environmental carrying index, For the region The random parameters of .

[0018] Furthermore, a two-layer robust optimization model for basin discharge allocation coupled with an ecological compensation model is constructed as follows:

[0019] in, is the robust adjustment coefficient, is the dual variable.

[0020] Furthermore, the two-layer robust optimization model for watershed discharge allocation coupled with the ecological compensation model is solved, and the optimal watershed discharge allocation results are obtained, including: Introducing Lagrange multipliers , the Karush-Kuhn-Tucker method is used to transform the lower-level objective function and constraints, and the two-level optimization model is transformed into a single-level optimization model; Clarify the domain of the single-layer optimization model; Randomly select the initial optimal solution within the model domain and record it as ; The interior point method is used to find the optimal solution Iterate and finally get the optimal solution of the model ; Adjust the robustness adjustment coefficient The value of , we can get the series optimal solutions of the optimization model at different conservative levels. , and obtain the optimization results of basin discharge allocation under uncertain environment.

[0021] The present invention has the following beneficial effects: The present invention considers multi-layer and multi-factor allocation indicators to replace the traditional single-factor allocation, adds multiple indicators of upper and lower-level decision-making to enhance the fairness and rationality of the allocation scheme, and significantly improves the accuracy and response efficiency of basin pollution discharge decision-making allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of the flow chart of a watershed discharge allocation optimization method coupled with an ecological compensation model; Figure 2 Schematic diagram of the framework of a watershed discharge allocation optimization method coupled with an ecological compensation model. DETAILED DESCRIPTION

[0023] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0024] like Figure 1 and Figure 2 As shown, the embodiment of the present invention provides a method for optimizing watershed discharge allocation coupled with an ecological compensation model, comprising the following steps S1 to S5: S1. Obtain basin pollution data; In an optional embodiment of the present invention, step S1 obtains basin pollution discharge data as raw data to perform basin pollution discharge allocation optimization processing.

[0025] S2. Construct a two-level optimization model for watershed pollutant discharge allocation, with minimizing pollution control costs as the upper-level goal and maximizing pollutant discharge allocation benefits as the lower-level goal; In an optional embodiment of the present invention, step S2 constructs a two-level optimization model for watershed pollutant discharge allocation with minimizing pollution control costs as the upper-level goal and maximizing pollutant discharge allocation benefits as the lower-level goal, including: Taking minimizing pollution control costs as the upper-level goal, and taking the Gini coefficient constraint of pollutant discharge distribution, water environment carrying index constraint, pollutant discharge demand constraint and parameter non-negativity constraint as the constraint conditions, the upper-level model is constructed; The lower-level model is constructed with the maximization of pollution discharge allocation benefits as the lower-level goal, and the pollutant transfer constraints in each region and the pollutant emissions of each polluting enterprise not exceeding the minimum and maximum demand constraints as constraints; A two-layer optimization model for basin discharge allocation is constructed based on the upper model and the lower model.

[0026] This embodiment aims to minimize pollution control costs during the watershed pollution control process, and includes two parts: (1) pre-treatment of pollution that is about to be discharged into the water environment; (2) implementation of paid allocation of pollutant discharge. Therefore, the upper objective function is:

[0027] During the allocation process, attention should also be paid to the fairness of the allocation, so as to make full and effective use of the pollution discharge rights and reduce the differences between regions and polluting enterprises.

[0028] When formulating the total amount of pollution discharge rights, the natural carrying capacity of the water environment must be taken into consideration, and pollution discharge must be kept within a reasonable range.

[0029] Different regions have different industrial structures, and the types and quantities of pollutants they emit vary. Therefore, there is an upper limit for pollution emissions in each region. At the same time, it is necessary to ensure the normal production and life of the economy and society. Therefore, pollution emission restrictions are:

[0030] Parameter non-negativity constraint:

[0031] in, is the pollution control cost function, x , y is the decision variable; Assigned to the region pollutants The amount of sewage discharged, For the region Allocated to polluting enterprises pollutants The amount of sewage discharged; For the region Medium pollutants governance ratio; For the region Treating pollutants Cost; To allocate to polluting enterprises pollutants the revenue from pollution discharge; , is the weight coefficient, For the region The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region h The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region s The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; For polluting enterprises The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises m The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises n The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; Assigning a Gini coefficient to pollution discharge; For the region Pollutant carrying capacity; , Respectively for regions emission Minimum and maximum required levels of pollutants; I is the number of regions; J is the number of polluting enterprises.

[0032] This embodiment takes maximizing the benefits of sewage discharge configuration as the lower-level goal, specifically:

[0033] Since watershed pollution is unidirectional, that is, pollutants can only flow from upstream to downstream, some pollutants from upstream will squeeze out a portion of the local pollution discharge share when flowing to downstream; downstream areas can only redistribute their own pollution discharge rights to various polluting enterprises, and at the same time, each polluting enterprise will also have more detailed pollution discharge restrictions. The constraints are:

[0034] in, For the region i The pollution discharge configuration income, For the region Allocated to polluting enterprises of the income generated by the emission rights; For the region The pollutants are delivered to the area proportion; , Respectively for regions Medium-sized polluting enterprises emission Minimum and maximum required levels of pollutants; K is the amount of pollutants.

[0035] S3. Construct an ecological compensation model and couple it to a two-layer optimization model for watershed pollution discharge allocation; In an optional embodiment of the present invention, step S3 considers the impact of the ecological compensation mechanism in the pollutant emission allocation decision model. To mathematically characterize the impact of the ecological compensation mechanism on the pollutant emission allocation model, it is first necessary to clarify the ecological compensation standards and unit compensation amounts. and region For example, For upstream, For the downstream, the standard for ecological compensation calculation should be based on the upstream, and the unit compensation amount needs to be determined after discussion between the two parties. In addition, it is necessary to ensure that the upstream and downstream areas in the basin participate in the ecological compensation. It should be clear that if the upstream area wants to obtain the ecological compensation amount, it needs to make further emission reductions. The more pollutants are reduced, the more ecological compensation it will obtain after calculation. But at the same time, the additional governance costs paid by the upstream area will also be higher. Therefore, the first constraint needs to ensure that the ecological compensation can cover the governance costs of the upstream. For the downstream, the ecological compensation paid by the downstream needs to be less than the pollution cost borne by the downstream if it does not participate, that is, the part of the emission rights occupied by the upstream and the pollution cost that the downstream needs to govern from the upstream. Its mathematical expression is:

[0036] in, For the region Horizontal ecological compensation parameters; For the region and region About pollutants Unit horizontal ecological compensation parameters; For the region About pollutants The horizontal ecological compensation standard value; For the region development opportunity costs.

[0037] S4. Introduce the uncertainty set of water environment carrying index into the two-layer optimization model of watershed discharge allocation coupled with the ecological compensation model, and construct a two-layer robust optimization model of watershed discharge allocation coupled with the ecological compensation model; In an optional embodiment of the present invention, step S4 considers the uncertainty in the decision-making process and uses a robust optimization method to solve it, processing the uncertainty set of environmental carrying index, including: S4-1. Constraining the water environment carrying index Replace with To characterize uncertainty; S4-2. Set random parameters In the interval Symmetric distribution, and , substituted into the constraints of S4-1,

[0038] in, For the region Nominal value of environmental carrying capacity, For the region The maximum range of variation of environmental carrying capacity.

[0039] In this constraint, the random parameter Slight changes in the optimal allocation plan will render the optimal allocation plan invalid. If left untreated, decision makers will face huge decision-making costs and need to formulate a large number of plans to deal with the uncertainty in reality. To this end, the present invention adopts a robust optimization processing method to transform the originally unsolvable uncertainty constraints into solvable linear constraints, while giving the decision results anti-interference ability.

[0040] S4-3. Form a new optimization model based on the constraints of S4-2:

[0041] Introducing dual variables , solving this model requires its dual form:

[0042] in, represents the robust adjustment coefficient; is the dual variable.

[0043] S4-4. Substitute the transformed optimization model into the constraints of S4-2 to obtain new constraints. From then on, replace the random parameters with deterministic parameters to make the model solvable:

[0044] S4-5. Through the above steps, a two-layer robust optimization model for watershed discharge allocation coupled with an ecological compensation model is finally constructed, specifically:

[0045] in, is the robust adjustment coefficient, is the dual variable.

[0046] S5. Solve the two-layer robust optimization model of watershed discharge allocation coupled with the ecological compensation model to obtain the optimal watershed discharge allocation result.

[0047] In an optional embodiment of the present invention, step S5 solves the two-layer robust optimization model for watershed discharge allocation coupled with the ecological compensation model, and obtains the optimal watershed discharge allocation result including: Introducing Lagrange multipliers , the Karush-Kuhn-Tucker method is used to transform the lower-level objective function and constraints, and the two-level optimization model is transformed into a single-level optimization model; Clarify the domain of the single-layer optimization model; Randomly select the initial optimal solution within the model domain and record it as ; The interior point method is used to find the optimal solution Iterate and finally get the optimal solution of the model ; Adjust the robustness adjustment coefficient The value of , we can get the series optimal solutions of the optimization model at different conservative levels. , and obtain the optimization results of basin discharge allocation under uncertain environment.

[0048] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0049] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0050] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0051] Specific embodiments are used in the present invention to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

[0052] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A basin discharge allocation optimization method coupled with an ecological compensation model, characterized in that: The following steps are involved: Obtain basin pollution data; A two-level optimization model for watershed pollutant discharge allocation is constructed with minimizing pollution control costs as the upper level goal and maximizing pollutant discharge allocation benefits as the lower level goal. Construct an ecological compensation model and couple it to a two-layer optimization model for watershed discharge allocation; The uncertainty set of water environment carrying index is introduced into the two-level optimization model of watershed discharge allocation coupled with the ecological compensation model, and a two-level robust optimization model of watershed discharge allocation coupled with the ecological compensation model is constructed. The two-layer robust optimization model of watershed discharge allocation coupled with the ecological compensation model is solved to obtain the optimal watershed discharge allocation result.

2. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 1 is characterized in that: With minimizing pollution control costs as the upper level goal and maximizing pollution discharge allocation benefits as the lower level goal, a two-level optimization model for watershed pollution discharge allocation is constructed, including: Taking minimizing pollution control costs as the upper-level goal, and taking the Gini coefficient constraint of pollutant discharge distribution, water environment carrying index constraint, pollutant discharge demand constraint and parameter non-negativity constraint as the constraint conditions, the upper-level model is constructed; The lower-level model is constructed with the maximization of pollution discharge allocation benefits as the lower-level goal, and the pollutant transfer constraints in each region and the pollutant emissions of each polluting enterprise not exceeding the minimum and maximum demand constraints as constraints; A two-layer optimization model for basin discharge allocation is constructed based on the upper model and the lower model.

3. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 2 is characterized in that: Taking minimizing pollution control costs as the upper-level goal, and taking the Gini coefficient constraint of pollutant discharge distribution, the water environment carrying index constraint, the pollutant discharge demand constraint, and the parameter non-negative constraint as the constraints, the upper-level model is constructed, specifically: ； st in, is the pollution control cost function, x , y is the decision variable; Assigned to the region pollutants The amount of sewage discharged, For the region Allocated to polluting enterprises pollutants The amount of sewage discharged; For the region Medium pollutants governance ratio; For the region Treating pollutants Cost; To allocate to polluting enterprises pollutants the revenue from pollution discharge; , is the weight coefficient, For the region The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region h The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For the region s The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; For polluting enterprises The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises m The ratio of the amount of pollution discharged to the Gini coefficient of pollution discharge distribution, For polluting enterprises n The ratio of the amount of pollution discharged to the Gini coefficient of pollution distribution; Assigning a Gini coefficient to pollution discharge; For the region Pollutant carrying capacity; , Respectively for regions emission Minimum and maximum required levels of pollutants; I is the number of regions; J is the number of polluting enterprises.

4. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 3 is characterized in that: Taking maximizing the benefits of pollution discharge configuration as the lower-level goal, and taking the pollutant transfer constraints of each region and the pollutant emissions of each polluting enterprise not exceeding the minimum and maximum demand constraints as constraints, the lower-level model is constructed, specifically: ； st in, For the region i The pollution discharge configuration income, For the region Allocated to polluting enterprises of the income generated by the emission rights; For the region The pollutants are delivered to the area proportion; , Respectively for regions Medium-sized polluting enterprises emission Minimum and maximum required levels of pollutants; K is the amount of pollutants.

5. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 4 is characterized in that: The specific construction of the ecological compensation model is as follows: in, For the region Horizontal ecological compensation parameters; For the region and region About pollutants Unit horizontal ecological compensation parameters; For the region About pollutants The horizontal ecological compensation standard value; For the region development opportunity costs.

6. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 5 is characterized in that: The uncertainty set of water environment carrying index is introduced into the two-level optimization model of watershed discharge allocation coupled with the ecological compensation model, including: Convert the water environment carrying index constraint into uncertainty constraint; Set random parameters in the interval Symmetrical distribution is adopted, and the uncertain parameters are characterized according to the nominal value of the regional environmental carrying index and the maximum variation range of the regional environmental carrying index, and the linear constraint of the water environment carrying index is obtained.

7. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 6 is characterized in that: The linear constraints of the water environment carrying index are as follows: in, For the region Nominal value of the environmental carrying index, For the region The maximum range of variation of the environmental carrying index, For the region The random parameters of .

8. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 7 is characterized in that: The two-layer robust optimization model for basin discharge allocation coupled with the ecological compensation model is constructed as follows: in, is the robust adjustment coefficient, is the dual variable.

9. The method for optimizing watershed discharge allocation coupled with an ecological compensation model according to claim 8 is characterized in that: The two-layer robust optimization model for watershed discharge allocation coupled with the ecological compensation model is solved, and the optimal watershed discharge allocation results are obtained, including: Introducing Lagrange multipliers , the Karush-Kuhn-Tucker method is used to transform the lower-level objective function and constraints, and the two-level optimization model is transformed into a single-level optimization model; Clarify the domain of the single-layer optimization model; Randomly select the initial optimal solution within the model domain and record it as ; The interior point method is used to find the optimal solution Iterate and finally get the optimal solution of the model ; Adjust the robustness adjustment coefficient The value of , we can get the series optimal solutions of the optimization model at different conservative levels. , and obtain the optimization results of basin discharge allocation under uncertain environment.

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