Multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities

Abstract

The invention discloses a multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities: step 1, constructing a hierarchical structure for optimizing the configuration evaluation of grey-green rainwater facilities in sponge cities; step 2, scenario design and simulation; step 3, establishing a relationship model between the configuration ratio of grey-green rainwater facilities and evaluation indicators; step 4, quantification and monetization of benefit evaluation indicators; step 5, constructing a multi-objective decision-making monetization mathematical model; step 6, solving the objective function to obtain the optimal solution; the invention establishes a structural hierarchy for optimizing the configuration evaluation of grey-green rainwater facilities in sponge cities, and evaluates the monetization benefits of the construction of grey-green rainwater facilities in sponge cities; a multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities is proposed, and a multi-objective optimization solution for the configuration of grey-green facilities under appropriate investment is efficiently found.

Description

Technical Field

[0001] The invention belongs to the technical field of urban construction optimization configuration, and specifically relates to a multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities. Background Art

[0002] Urban expansion and climate change restrict the sustainable development of cities. It is difficult to solve urban waterlogging and non-point source pollution at a low cost by relying solely on traditional gray infrastructure. Innovative planning solutions are needed. Green infrastructure is dominated by urban natural ecology and green space. Under normal rainfall conditions, it can effectively purify initial rainfall, reduce pollution in rainwater runoff, reduce surface runoff and control the total amount of runoff. However, when rainfall is heavy and relatively concentrated, the control effect of green infrastructure on rainwater at the source is limited, and it still needs to be coordinated with gray infrastructure to play an effective role.

[0003] In the decision-making process of coupled optimization configuration of grey-green rainwater facilities in sponge cities, previous studies considered single-form objectives, such as the reduction rate of SS in water environment and the reduction rate of overflow in water safety. In fact, the construction of grey-green rainwater facilities in sponge cities can bring benefits in water ecology, water environment, water safety, water economy, society and other aspects. Different benefits are composed of multiple benefit sub-indicators. However, the size of these benefit values ​​is often not directly measurable. The benefit values ​​can be converted into prices for comparison through monetization methods.

[0004] Different benefit objectives may have mutually restrictive relationships and often cannot be satisfied at the same time; general methods consider multiple options and conduct repeated experiments until all design objectives are achieved. Given the large number of decision variables and possible scenario combinations, traditional methods that rely on a limited number of experiments are no longer able to effectively solve such problems; therefore, multi-objective optimization methods are needed to consider the trade-offs between different benefit objectives in order to obtain the optimal solution. One of the most effective multi-objective optimization algorithms is the non-dominated sorting genetic algorithm (NSGA-II), which has been successfully applied to various water environment management problems; NSGA-II uses an iterative process to search for the optimal solution under a specific environment, allowing decision makers to consider different constraints when looking for the best trade-off between competing objective functions (i.e., the Pareto optimal frontier), thus becoming a powerful method to facilitate the decision-making process; in addition, the coverage, quality, and efficiency of the resulting Pareto optimal frontier are also significantly better than those of the traditional method with a limited number of experiments. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities, establish a structural hierarchy for the optimization evaluation of the configuration of grey-green rainwater facilities in sponge cities, and evaluate the monetary benefits of the construction of grey-green rainwater facilities in sponge cities; propose a multi-objective optimization configuration method for grey-green rainwater facilities in sponge cities, and efficiently find a multi-objective optimization scheme for the configuration of grey-green facilities under appropriate investment.

[0006] The technical solution adopted by the present invention is a multi-objective optimization configuration method for gray-green rainwater facilities in sponge cities, which is specifically implemented in the following steps:

[0007] Step 1: construct a hierarchical structure for optimizing the configuration of gray-green rainwater facilities in sponge cities;

[0008] Step 2: scenario design and simulation;

[0009] Step 3, establish a relationship model between the gray-green rainwater facility configuration ratio and the evaluation index;

[0010] Step 4: Quantification and monetization of benefit evaluation indicators;

[0011] Step 5, construct a multi-objective decision-making monetization mathematical model;

[0012] Step 6: Solve the objective function to obtain the optimal solution.

[0013] The present invention is also characterized in that:

[0014] Step 1 is as follows:

[0015] Taking the maximization of multi-objective benefits as the target layer, the middle layer includes the first-level decision-making indicators of multi-objective benefits and the corresponding second-level decision-making indicators, and the lowest layer is the alternative scheme of the combination configuration of gray-green rainwater facilities, thus constructing a hierarchical structure for the optimization evaluation of the configuration of gray-green rainwater facilities in sponge cities;

[0016] Based on the constructed evaluation hierarchy, the analytic hierarchy process is used to determine the weight value of each indicator; the test is carried out according to formula (1-1) and formula (1-2). When the consistency index CR is less than 0.1, the test passes:

[0017]

[0018]

[0019] In the formula, λ max is the maximum eigenvalue of the pairwise judgment matrix; n is the matrix order; RI is obtained according to the value of n;

[0020] The multi-objective benefit indicators specifically include: the first-level decision-making indicators of water ecological benefit, water environmental benefit, water safety benefit, water economic benefit and social benefit, as well as the corresponding second-level decision-making indicators;

[0021] Step 2 is as follows: select the types and layout areas of grey infrastructure and green infrastructure, use the MIKE URBAN urban stormwater model to simulate urban waterlogging and non-point source pollution without the grey-green stormwater facility scheme, and obtain the overflow node reduction rate, SS reduction, COD reduction, total runoff control, and overload pipe section reduction rate in the study area through model simulation;

[0022] Step 3 is as follows: establish the direct relationship between different configuration ratios of gray-green rainwater facilities (x) and the indicators simulated by the MIKEURBAN model (y) under different return periods:

[0023] y=f(x) (1-3);

[0024] Step 4 is as follows:

[0025] Combining the simulation results of the urban stormwater model with the monetization model, the benefits generated by a rainfall are calculated. Then, according to the frequency and number of rainfalls in the study area, the number of rainfalls with different return periods in a year is estimated, and the benefit value of the construction of gray-green rainwater facilities in a year is estimated.

[0026] The specific monetization model of water ecological benefits in step 4 is:

[0027] Monetization model for total runoff control:

[0028] The control effect of total runoff volume is calculated by alternative engineering method, and the monetization model is as follows:

[0029] B1=q0×(p1+p2) (1-4)

[0030] Where: q0 is the total runoff control of gray-green rainwater facilities, m 3 ; P1 is the operating cost of the rainwater pipe network, RMB / m 3 ; P2 is the tap water pollution treatment fee, yuan / m 3 ;

[0031] Monetization Model of Urban Heat Island Effect:

[0032] The alternative engineering method is used to calculate the urban heat island effect, and the monetization model is as follows:

[0033] B2=S1×P3×189 (1-5)

[0034] P3=P4×Y×n×24×30 (1-6)

[0035] Where S1 is the total area of ​​rain garden and green roof, ha; P3 is the climate regulation value of rain garden and green roof per unit area, yuan / (hm2 a); P4 is the power consumption of each air conditioner, KWh / h; Y is the electricity price; n is the month the air conditioner is used;

[0036] Monetization model for groundwater depth:

[0037] The shadow price method is used to calculate the effect of groundwater depth, and the monetization model is shown in the following formula.

[0038] B3=Q1×P5 (1-7)

[0039] Q1=α×H×A (1-8)

[0040] Where: Q1 is the infiltration recharge, m 3 ; P5 is the price of groundwater resources, RMB / m 3 ; α is the recharge coefficient of urban precipitation to groundwater; H is the annual rainfall, mm; A is the total area of ​​rain garden, green roof and permeable pavement, m 2 ;

[0041] Monetization model of wastewater recycling rate:

[0042] The shadow price method is used to calculate the wastewater recycling rate, and the monetization model is as follows:

[0043] B4=Q2×P6×d (1-9)

[0044] Where: Q2 is the amount of recycled rainwater, 10,000 m 3 / d; P6 is the price of recycled water, RMB / m 3 ; d is the number of days in a year;

[0045] The monetization model of water environmental benefits is specifically as follows:

[0046] The water environment benefits are calculated using the restoration and protection cost method, and the monetization model is as follows:

[0047] B5~B6=q×Q C ×c (1-10)

[0048] Where, q is the reduction of pollutant loads after installing gray-green rainwater facilities, kg; Q c is the pollutant equivalent value, kg; c is the pollution equivalent levy standard, yuan;

[0049] The monetization model for water security benefits is as follows:

[0050] The water security benefits are calculated using the alternative engineering method, and the monetization model is as follows:

[0051] B7~B8=q1×q2×(P1+P2) (1-11)

[0052] Where q1 is the total runoff when only the pipe network is laid, m 3 q2 is the overflow node reduction rate or overload pipe section reduction rate of gray-green rainwater facilities, %; P1 is the operating cost of the rainwater pipe network, yuan / m 3 ; P2 is the tap water pollution treatment fee, yuan / m 3 ;

[0053] The monetization model of water economic benefits is specifically as follows:

[0054] The water economic benefits take into account the construction costs of grey infrastructure and green infrastructure as well as the maintenance and management costs. When calculating the benefit value, the construction costs and operation and maintenance costs should be reduced by a multiple of the corresponding payback period, taking into account the 15-year facility operation cycle;

[0055] The monetization model of the social benefits is specifically:

[0056] Social Benefits Considering the benefits of green roofs and rain garden facilities in purifying the air, the monetization model is as follows:

[0057] B 13 ~B 15 =(q3×A1+q4×A2+Q5×A1×β2)×P4 (1-12)

[0058] Where q3 and q4 are the air pollutants absorbed by green roofs and rain gardens per square meter per year, g / m 2 a; A1 and A2 are the areas of green roof and rain garden, m 2 ; Q5 is the annual reduction in electricity consumption of green roofs, kWh / m 2 a; β2 is the air pollutant emitted per 1 kWh of electricity used, g / kWh; P4 is the cost of treating air pollutants, yuan / g;

[0059] Step 5 is as follows:

[0060] Taking the configuration ratio of rain gardens, green roofs, and permeable pavement as decision variables, the maximum net benefit, minimum cost, and maximum water safety benefit of gray-green facilities as objective functions, and the annual runoff control rate, SS reduction rate, single facility configuration area, and comprehensive benefits as constraints, a multi-objective decision-making monetization mathematical model is constructed:

[0061]

[0062] Where w is the indicator weight; V i M is the benefit generated by the construction of grey-green rainwater facilities per unit area in sponge cities; i S is the cost of gray-green rainwater facilities construction per unit area in sponge cities;i is the water safety benefit per unit area; f(xi) is the benefit index of gray-green rainwater facilities; A is the total area of ​​the study area;

[0063] The constraints include: the annual runoff control rate is not less than 80%; the runoff pollutant reduction rate is not less than 40%; the configuration area of ​​a single gray-green rainwater facility does not exceed 10%; the net benefit is positive:

[0064] α≥80% (1-14)

[0065] β 污染物 ≥40% (1-15)

[0066] 0≤F i ≤10% (1-16)

[0067]

[0068] Step 6 specifically uses the non-dominated sorting genetic algorithm with elite strategy (NSGA-II) to solve the objective function and realize the automatic optimization of the scale of gray-green rainwater facilities.

[0069] The beneficial effects of the present invention are:

[0070] The present invention establishes a macro-configuration optimization evaluation hierarchy of sponge city grey-green rainwater facilities through the hierarchical analysis method, which can comprehensively evaluate the construction benefits of sponge city grey-green rainwater facilities; calculates the construction benefits of sponge cities through the monetization method, and realizes the quantification and monetization of benefit indicators; by constructing a multi-objective decision-making monetization mathematical model, it weighs the conflicts of interest among multiple goal orientations, realizes the automatic optimization of the scale of grey-green rainwater facilities, and can efficiently find the optimal configuration plan of sponge city grey-green rainwater facilities under suitable investment; an example verification is carried out in a certain area of ​​a certain city, and the optimal configuration scenario of grey-green rainwater facilities in the study area is obtained, which can better solve the problems of rainwater runoff pollution and urban waterlogging in the study area, and can meet the multi-faceted benefits brought by sponge city construction, which illustrates the feasibility of the present invention in actual project planning and evaluation, in order to provide a reference for the reasonable layout of grey-green rainwater facilities in sponge city planning and construction, as well as performance appraisal and evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a technical roadmap of the multi-objective optimization configuration method of the sponge city grey-green rainwater facilities of the present invention;

[0072] Figure 2 A hierarchical structure diagram of the optimization evaluation of the configuration of the gray-green rainwater facilities in the sponge city in the multi-objective optimization configuration method of the gray-green rainwater facilities in the sponge city of the present invention;

[0073] Figure 3 The process steps of the non-dominated sorting genetic algorithm (NSGA-II) with elite strategy in the multi-objective optimization configuration method of the sponge city grey-green rainwater facilities of the present invention;

[0074] Figure 4 The gray-green rainwater facility optimization scheme taking into account three goal-oriented gray-green rainwater facility optimization schemes in the embodiment of the multi-objective optimization configuration method of the sponge city of the present invention;

[0075] Figure 5 The embodiment of the multi-objective optimization configuration method for gray-green rainwater facilities in the sponge city of the present invention takes into account both the rainfall return period and the safety and benefit goal-oriented optimal configuration scheme of gray-green rainwater facilities;

[0076] Figure 6 The embodiment of the multi-objective optimization configuration method for grey-green rainwater facilities in a sponge city of the present invention takes into account both the rainfall return period and the optimal configuration scheme for grey-green rainwater facilities guided by three objectives. DETAILED DESCRIPTION

[0077] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0078] The present invention provides a multi-objective optimization configuration method for gray-green rainwater facilities in sponge cities, such as Figure 1 As shown, the specific implementation steps are as follows:

[0079] Step 1: Determine the optimization goal of gray-green rainwater facility configuration, that is, multi-objective benefit maximization, select evaluation indicators, construct a hierarchical structure for gray-green rainwater facility configuration optimization evaluation, and determine the weight value of each evaluation indicator:

[0080] Taking multi-objective benefit maximization as the target layer, the middle layer includes the first-level decision-making indicators such as water ecological benefit, water environmental benefit, water safety benefit, water economic benefit, social benefit and the corresponding second-level decision-making indicators, and the lowest layer is the alternative scheme for the combination configuration of gray-green rainwater facilities. The hierarchical structure of the optimization evaluation of the configuration of gray-green rainwater facilities in sponge cities is constructed, such as Figure 2 As shown;

[0081] Based on the constructed evaluation hierarchy, the analytic hierarchy process is used to determine the weight value of each indicator. This method must pass the consistency test according to formula (1-1) and formula (1-2). When the consistency index CR is less than 0.1, the test is passed. The final composite weight calculation is shown in Table 1-1:

[0082]

[0083]

[0084] In the formula, λ maxis the maximum eigenvalue of the pairwise judgment matrix; n is the matrix order; RI is obtained according to the value of n;

[0085] Table 1-1 Synthesis weight

[0086]

[0087] Step 2: Analyze the suitable location and scope of the gray-green rainwater facilities in the target area, and use the urban stormwater model to simulate and analyze different configuration ratios of gray-green rainwater facilities and different rainfall scenarios:

[0088] Select appropriate types and layout areas of grey infrastructure and green infrastructure. Use the MIKE URBAN urban stormwater model to simulate urban waterlogging and non-point source pollution without the grey-green rainwater facility plan. Pre-install storage facilities and LID facilities in areas with severe waterlogging and non-point source pollution. For pipe sections with severe waterlogging, expand their pipe diameters. The number of overflow nodes, SS load, COD load, total runoff, and length of overloaded pipe sections in the study area are obtained through model simulation.

[0089] Step 3: Analyze the simulation results of different gray-green rainwater facility layout ratio scenarios in step 2, and obtain the overflow reduction rate, SS reduction, COD reduction, total runoff control, overload pipe section reduction rate and other result values; establish a direct relationship between different gray-green rainwater facility configuration ratios and urban stormwater model results under different return periods, in order to accurately reflect the interaction between the two:

[0090] The direct relationship between the different configuration ratios of gray-green rainwater facilities (x) and the indicators simulated by the MIKE URBAN model (y) under different return periods is established to accurately reflect their interaction:

[0091] y=f(x) (1-3);

[0092] Step 4: According to the hierarchical structure of gray-green rainwater facility configuration optimization evaluation constructed in step 1, the benefits of sponge city construction are quantitatively analyzed from the aspects of water ecology, water environment, water safety, water economy, and society; the total runoff control in the water ecological benefit index, the SS reduction rate and COD reduction rate in the water environment benefit index, and the overflow node reduction rate and overload pipe section reduction rate in the water safety benefit index are all obtained by simulating the urban rainwater model in step 2, and the remaining indicators are obtained by quantitative analysis; the monetization value of the benefits of sponge city construction is obtained through the alternative engineering method, the water resource shadow price method, the restoration and protection cost method, etc.; specifically:

[0093] Combining the simulation results of the urban stormwater model with the monetization model (i.e., formulas 1-4, 1-10, and 1-11), the benefits generated by a rainfall event are calculated. Then, according to the rainfall frequency and number in the study area, the number of rainfall events with a return period of 2a, 5a, 10a, 20a, 50a, and 100a in a year is estimated, and the benefit value generated by the construction of gray-green rainwater facilities in one year is estimated:

[0094] (1) Monetization model for total runoff control:

[0095] The control effect of total runoff volume is calculated by alternative engineering method, and the monetization model is as follows:

[0096] B1=q0×(p1+p2) (1-4)

[0097] Where: q0 is the total runoff control of gray-green rainwater facilities, m 3 ; P1 is the operating cost of the rainwater pipe network, RMB / m 3 , at 0.5 yuan / m 3 Value; P2 is the tap water pollution treatment fee, yuan / m 3 , at 0.95 yuan / m 3 Get value;

[0098] (2) Monetization model of urban heat island effect:

[0099] The alternative engineering method is used to calculate the urban heat island effect, and the monetization model is as follows:

[0100] B2=S1×P3×189 (1-5)

[0101] P3=P4×Y×n×24×30 (1-6)

[0102] Where S1 is the total area of ​​rain garden and green roof, ha; P3 is the climate regulation value of rain garden and green roof per unit area, yuan / (hm 2 a); P4 is the power consumption of each air conditioner, KWh / h, 0.86KWh / h; Y is the electricity price, 0.5KWh; n is the month the air conditioner is used, calculated as 4 months;

[0103] (3) Monetization model of groundwater depth:

[0104] The shadow price method is used to calculate the effect of groundwater depth, and the monetization model is shown in the following formula.

[0105] B3=Q1×P5 (1-7)

[0106] Q1=α×H×A (1-8)

[0107] Where: Q1 is the infiltration recharge, m 3; P5 is the price of groundwater resources, RMB / m 3 , take 4.1 yuan / m 3 ; α is the recharge coefficient of urban precipitation to groundwater, which is 0.2; H is the annual rainfall, mm, which is based on the average annual rainfall of 571 mm; A is the total area of ​​rain garden, green roof and permeable pavement, m 2 ;

[0108] (4) Monetization model of wastewater recycling rate:

[0109] The shadow price method is used to calculate the wastewater recycling rate, and the monetization model is as follows:

[0110] B4=Q2×P6×d (1-9)

[0111] Where: Q2 is the amount of recycled rainwater, 10,000 m 3 / d; P6 is the price of recycled water, RMB / m 3 , at 0.924 yuan / m 3 Value; d is the number of days in a year;

[0112] The specific monetization model of water environmental benefits is as follows:

[0113] The water environment benefits are calculated using the restoration and protection cost method, and the monetization model is as follows:

[0114] B5~B6=q×Q C ×c (1-10)

[0115] In the formula, q is the reduction of pollutant loads by installing gray-green rainwater facilities, kg; Qc is the pollutant equivalent value, which is the relative relationship between the pollution hazards and treatment costs of different pollutants (kg), and the pollution equivalent values ​​of SS and COD are 4.0 kg and 1.0 kg respectively; c is the pollution equivalent levy standard, yuan, calculated at 0.7 yuan;

[0116] The specific monetization model of water security benefits is as follows:

[0117] The water security benefits are calculated using the alternative engineering method, and the monetization model is as follows:

[0118] B7~B8=q1×q2×(P1+P2) (1-11)

[0119] Where q1 is the total runoff when only the pipe network is laid, m 3 q2 is the overflow node reduction rate or overload pipe section reduction rate of gray-green rainwater facilities, %; P1 is the operating cost of the rainwater pipe network, yuan / m 3 , at 0.5 yuan / m 3 Value; P2 is the tap water pollution treatment fee, yuan / m 3, at 0.95 yuan / m 3 Get value;

[0120] The specific monetization model of water economic benefits is as follows:

[0121] The water economic benefits take into account the construction costs of grey infrastructure and green infrastructure as well as the maintenance and management costs, and need to be obtained through data collection and actual investigation based on local conditions. The unit price of the construction cost of the storage pond is 1,200 yuan / m 3 The maintenance and management unit price is 100 yuan / m 3 The unit price of pipe network reconstruction and construction cost is 600 yuan / m, and the road restoration cost management, i.e. maintenance and management cost, is 300 yuan / m; the construction costs of rain garden, green roof and permeable pavement are 300 yuan, 100 yuan and 300 yuan respectively; the maintenance and management costs of rain garden, green roof and permeable pavement are 30 yuan, 15 yuan and 2.4 yuan respectively. Because the construction of sponge facilities is effective for a long time, the construction cost and operation and maintenance cost should be reduced by the multiple of the corresponding payback period when calculating the benefit value, and the 15-year facility operation cycle will be considered;

[0122] The specific monetization model of social benefits is as follows:

[0123] Social Benefits Considering the benefits of green roofs and rain garden facilities in purifying the air, the monetization model is as follows:

[0124] B 13 ~B 15 =(q3×A1+q4×A2+Q5×A1×β2)×P4 (1-12)

[0125] Where q3 and q4 are the air pollutants absorbed by green roofs and rain garden facilities per square meter per year, g / m 2 a; The values ​​of pollutants absorbed by green roofs and rain gardens are approximately the same, with NO2, SO2, and PM10 being 1.9, 1.6, and 0.6, respectively; A1 and A2 are the areas of green roofs and rain gardens, m 2 ; Q5 is the annual reduction in electricity consumption of green roofs, kWh / m 2 a, take 15.39kWh / m 2 a; β2 is the air pollutant emitted per 1 kWh of electricity used, g / kWh, NO2, SO2, PM10 are 1.2, 1.7, 0 respectively; P4 is the treatment cost of air pollutants, yuan / g, NO2, SO2, PM10 are 0.05418 yuan / g, 0.02322 yuan / g, 0.03613 yuan / g respectively;

[0126] Step 5, the configuration ratio of rain gardens, green roofs, and permeable pavement is used as the decision variable. The maximum net benefit, minimum cost, and maximum water safety benefit of gray-green rainwater facilities are used as the objective function, and the annual runoff control rate constraint, SS reduction rate constraint, single facility configuration area constraint, and comprehensive benefit constraint are used as constraints to establish a multi-objective decision-making monetization mathematical model; the direct relationship between the different configuration ratios of gray-green rainwater facilities and indicators established in step 3 is used as the input condition of the multi-objective optimization model; specifically:

[0127] Taking the configuration ratio of rain gardens, green roofs, and permeable pavement as decision variables, the maximum net benefit (i.e., the difference between cost and benefit) of gray-green facilities, the minimum cost, and the maximum water safety benefit as objective functions, and the annual runoff control rate, SS reduction rate, single facility configuration area, and comprehensive benefits as constraints, a multi-objective decision-making monetization mathematical model is constructed:

[0128]

[0129] Where w is the indicator weight; V i M is the benefit generated by the construction of grey-green rainwater facilities per unit area in sponge cities; i S is the cost of gray-green rainwater facilities construction per unit area in sponge cities; i is the water safety benefit per unit area; f(xi) is the benefit index of gray-green rainwater facilities; A is the total area of ​​the study area;

[0130] The constraints include: the annual runoff control rate should not be less than 80%, and the corresponding calculated runoff volume should be 17.2 mm; the runoff pollutant reduction rate (in terms of suspended solids SS) should not be less than 40%; the configuration area of ​​a single gray-green rainwater facility should not exceed 10%; the net benefit is positive:

[0131] α≥80% (1-14)

[0132] β 污染物 ≥40% (1-15)

[0133] 0≤F i ≤10% (1-16)

[0134]

[0135] Step 6, using the non-dominated sorting genetic algorithm with elite strategy (NSGA-II) to solve, using the set of non-inferior solutions to describe the configuration mode under different goal orientations, to obtain the final optimal solution, to achieve automatic optimization of the scale of gray-green rainwater facilities, thus avoiding the dilemma of traditional exhaustive solutions that cannot obtain the optimal solution. The flow chart is as follows: Figure 3 As shown;

[0136] Example:

[0137] This area is the central area of ​​a certain city, covering an area of ​​28.01km 2 The terrain is high in the southeast and slightly low in the northwest. It has a warm temperate continental monsoon climate with distinct cold and warm seasons and dry and wet seasons. The annual average temperature is 13.1℃~14.3℃, and the annual precipitation is 528.3~716.5mm. The population is dense, the building density is high, there are many hard roads, the drainage system is imperfect, and the drainage capacity of the pipe network is limited. It is still plagued by rainwater runoff pollution and waterlogging problems;

[0138] (1) Rainfall scenario design:

[0139] The rainstorm intensity was calculated using the actual rainstorm intensity formula for the area in a certain city. The rainfall recurrence period was considered to be 2a, 5a, 10a, 20a, 50a, and 100a. The rainfall duration was 2h, the peak coefficient was 0.4, and the total rainfall was 23.985mm, 38.804mm, 50.014mm, 61.224mm, 76.044mm, and 87.254mm respectively.

[0140] (2) Gray-green rainwater facility configuration scenario

[0141] The areas of green rainwater facilities are 1%, 2%, 3%, 4%, 5%, 7% and 10% of the total area of ​​the study area, respectively. The diameter of the original pipeline is enlarged, and the total length of the enlarged pipeline is 9885.94mm:

[0142] Option 1: 0.1% storage tank + 10% rainwater garden + 10% green roof + 10% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0143] Option 2: 0.1% storage tank + 7% rainwater garden + 7% green roof + 7% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0144] Option 3: 0.1% storage tank + 5% rainwater garden + 5% green roof + 5% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0145] Option 4: 0.1% storage tank + 4% rainwater garden + 4% green roof + 4% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0146] Plan 5: 0.1% storage tank + 3% rainwater garden + 3% green roof + 3% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0147] Plan 6: 0.1% storage tank + 2% rainwater garden + 2% green roof + 2% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0148] Option 7: 0.1% storage tank + 1% rainwater garden + 1% green roof + 1% permeable pavement + expansion of pipe diameter to 9885.94mm;

[0149] (3) Dynamic optimization of gray-green rainwater facility layout scheme based on multi-objective linkage

[0150] Taking into account the optimal scheme and benefit value of gray-green rainwater facility layout under different goal orientations, such as Figure 4 As shown in Figure 2, in order to take into account both the rainfall scenario and the three objectives, the optimal configuration scheme under each return period is re-evaluated under all return period conditions. The results are shown in Figure 2. Figure 5 , Figure 6 As shown in the figure, in the configuration scenario of 1% storage tank + 8.76% rain garden + 9.76% green roof + 3.62% permeable pavement + expansion of pipe diameter 9885.93m, the safety benefit goal orientation under different recurrence conditions can be achieved. In the configuration scenario of 1% storage tank + 9.31% rain garden + 9.90% green roof + 2.21% permeable pavement + expansion of pipe diameter 9885.94mm, the maximum net benefit, cost and safety benefit under different recurrence conditions can be achieved;

[0151] The present invention establishes a hierarchical structure for optimizing the configuration of gray-green rainwater facilities in sponge cities through the analytic hierarchy process, which can comprehensively evaluate the construction benefits of gray-green rainwater facilities in sponge cities. The benefits of sponge city construction are calculated through the monetization method, and the quantification and monetization of benefit indicators are realized. By constructing a multi-objective decision-making monetization mathematical model, the conflicts of interest between multiple goal orientations are weighed, and the automatic optimization of the scale of gray-green rainwater facilities is realized, which can efficiently find the optimal configuration plan of gray-green rainwater facilities in sponge cities under suitable investment. An example verification is carried out in a certain area of ​​a certain city, and the optimal configuration scenario of gray-green rainwater facilities in the study area is obtained, which can better solve the problems of rainwater runoff pollution and urban waterlogging in the study area, and can meet the multi-faceted benefits brought by the construction of sponge cities. It illustrates the feasibility of the present invention in actual project planning and evaluation, in order to provide a reference for the reasonable layout of gray-green rainwater facilities in the planning and construction of sponge cities, as well as performance assessment and evaluation.

Claims

1. A multi-objective optimization configuration method for gray-green rainwater facilities in sponge cities, characterized in that: Please follow the steps below to implement: Step 1: construct a hierarchical structure for the optimization evaluation of the configuration of gray-green rainwater facilities in sponge cities, specifically: taking the maximization of multi-objective benefits as the target layer, the middle layer includes the first-level decision-making indicators of multi-objective benefits and the corresponding second-level decision-making indicators, and the lowest layer is the alternative scheme for the combination configuration of gray-green rainwater facilities, thus constructing a hierarchical structure for the optimization evaluation of the configuration of gray-green rainwater facilities in sponge cities; Based on the evaluation hierarchy structure, the weight value of each indicator is determined by using the hierarchical analysis method. According to formula (1-1) and formula (1-2), the consistency index CR When <0.1, the test is passed: In the formula, λ max is the maximum eigenvalue of the pairwise judgment matrix; n is the matrix order; RI according to n Get the value size; The multi-objective benefits specifically include: primary decision indicators of water ecological benefits, water environmental benefits, water safety benefits, water economic benefits and social benefits, and corresponding secondary decision indicators; Step 2, scenario design and simulation, specifically: select the types and layout areas of gray infrastructure and green infrastructure, use the MIKE URBAN urban stormwater model to simulate urban waterlogging and non-point source pollution without the gray-green stormwater facility scheme, and obtain the overflow node reduction rate, SS reduction, COD reduction, runoff water control, and overload pipe section reduction rate in the study area through model simulation; Step 3: Establish a relationship model between the configuration ratio of gray-green rainwater facilities and the evaluation index. Specifically, establish a direct relationship between the different configuration ratios x of gray-green rainwater facilities under different return periods and the index y simulated by the MIKE URBAN model: y ＝ f ( x )(1-3)； Step 4: Quantification and monetization of benefit evaluation indicators, specifically: combining the simulation results of the urban stormwater model with the monetization model, calculating the benefits generated by a rainfall event, and then estimating the number of rainfall events with different return periods in a year according to the rainfall frequency and number in the study area, and then estimating the benefit value generated by the construction of gray-green rainwater facilities in one year; The monetization model of water ecological benefits in step 4 is specifically: the monetization model of total runoff control: the control effect of total runoff is calculated by using the alternative engineering method, and the monetization model is as follows: B 1＝ q 0×( p 1+ p 2)(1-4) Where: q 0 is the total runoff control of gray-green rainwater facilities, m 3 ; P 1 is the operating cost of the rainwater pipe network, RMB / m 3 ; P 2 is the tap water pollution treatment fee, RMB / m 3 ; Monetization model of urban heat island effect: The urban heat island effect is calculated using the alternative engineering method, and the monetization model is as follows: B 2＝ S 1× P 3×189(1-5) P 3＝ P 4× Y × m ×24×30(1-6) In the formula, S 1 is the total area of ​​rain garden and green roof, hm 2 ; P 3 is the climate regulation value of rainwater garden and green roof per unit area, RMB / (hm 2 a); P 4 is the power consumption of each air conditioner, KWh / h; Y The price of electricity; m The month in which the air conditioner is used; Monetization model of groundwater depth: The shadow price method is used to calculate the effect of groundwater depth. The monetization model is as follows: B 3＝ Q 1× P 5(1-7) Q 1＝ α × H × Z (1-8) Where: Q 1 is the infiltration recharge, m 3 ; P 5 is the price of groundwater resources, RMB / m 3 ; α is the recharge coefficient of urban precipitation to groundwater; H is the annual rainfall, mm; Z is the total area of ​​rain garden, green roof and permeable pavement, m 2 ; Monetization model of sewage recycling rate: The shadow price method is used to calculate the sewage recycling rate. The monetization model is as follows: B 4＝ Q 2× P 6× d (1-9) Where: Q 2 is the amount of recycled rainwater, 10,000 m 3 / d; P 6 is the price of recycled water, RMB / m 3 ; d is the number of days in a year; The monetization model of water environment benefits is as follows: the water environment benefits are calculated using the restoration and protection cost method, and the monetization model is as follows: B 5～ B 6＝ q × Q C × c (1-10) In the formula, q The reduction of pollutant load for the installation of gray-green rainwater facilities, kg; Q is the pollutant equivalent value, Kg; c is the pollution equivalent levy standard, yuan; The monetization model of water safety benefits is specifically as follows: water safety benefits are calculated using the alternative engineering method, and the monetization model is as follows: B 7～ B 8＝ q 1× q 2×( P 1+ P 2)(1-11) In the formula, q 1 is the total runoff when only the pipe network is laid, m 3 ; q 2 is the overflow node reduction rate or overload pipe section reduction rate of gray-green rainwater facilities, %; P 1 is the operating cost of the rainwater pipe network, RMB / m 3 ; P 2 is the tap water pollution treatment fee, RMB / m 3 ; The monetization model of water economic benefits is as follows: water economic benefits take into account the construction costs and maintenance and management costs of grey infrastructure and green infrastructure. When calculating the benefit value, the construction cost and operation and maintenance cost should be reduced by a multiple of the corresponding payback period, taking into account the 15-year facility operation cycle; The monetization model of the social benefit is specifically as follows: The social benefit takes into account the benefits of green roofs and rain garden facilities in purifying the air, and the monetization model is as follows: B 13 ～ B 15 ＝( q 3× A 1+ q 4× A 2+ Q 5× A 1× β 2)× P 4(1-12) In the formula, q 3. q 4 are the air pollutants absorbed by green roofs and rain gardens per square meter per year, g / m 2 a; A 1. A 2 are the areas of green roof and rain garden, m 2 ; Q 5 is the annual reduction in electricity consumption of green roofs, kWh / m 2 a; β 2 is the air pollutant emitted for every 1kWh of electricity used, g / kWh; P 4 is the cost of treating air pollutants, RMB / g; Step 5: Construct a multi-objective decision-making monetization mathematical model. Specifically, the configuration ratio of rain gardens, green roofs, and permeable pavement is used as the decision variable, the maximum net benefit, minimum cost, and maximum water safety benefit of gray-green facilities are used as the objective function, and the annual runoff control rate, SS reduction rate, single facility configuration area, and comprehensive benefits are used as constraints to construct a multi-objective decision-making monetization mathematical model: In the formula, w is the indicator weight; V i The benefits generated by the construction of grey-green rainwater facilities per unit area in sponge cities; M i The cost of constructing grey-green rainwater facilities per unit area in sponge cities; N i It is the water security benefit per unit area; f ( x i ) is the benefit index of gray-green rainwater facilities; A is the total area of ​​the study area; Step 6: Solve the objective function to obtain the optimal solution.

2. The multi-objective optimization configuration method for gray-green rainwater facilities in sponge cities according to claim 1 is characterized in that: The constraints include: the annual runoff control rate is not less than 80%; the runoff pollutant reduction rate is not less than 40%; the configuration area of ​​a single gray-green rainwater facility does not exceed 10%; the net benefit is positive: ≥80％ (1-14) β 污染物 ≥40％ (1-15) 0≤ F i ≤10％ (1-16) In the formula, is the annual runoff volume control rate, %; β 污染物 is the reduction rate of total runoff pollutants, %; F i Configuration ratio of a single gray-green rainwater facility, %.

3. The multi-objective optimization configuration method for gray-green rainwater facilities in sponge cities according to claim 1 is characterized in that: The step 6 specifically adopts the non-dominated sorting genetic algorithm NSGA-II with an elite strategy to solve the objective function and realize the automatic optimization of the scale of the gray-green rainwater facilities.

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