CN114897233A - Rural domestic sewage treatment mode optimization method based on spatial clustering improved algorithm - Google Patents
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Abstract
The invention discloses a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, which comprises the steps of firstly, correcting a clustering center coordinate calculation formula by adopting the population number and terrain elevation of a village to generate an alternative scheme of a rural domestic sewage treatment mode; secondly, analyzing a raw material list of the sewage treatment facilities of each alternative scheme, and analyzing the full life cycle environmental influence of the sewage treatment facilities; thirdly, calculating the initial cost, the construction cost, the operation cost and the abandonment cost of the sewage treatment facility; and finally, constructing an objective function according to the full life cycle environmental influence latent value and the treatment cost, and performing multi-objective optimization on all treatment mode alternatives to obtain the optimal sewage treatment modes under different scene conditions. The invention can be used for scientifically determining the spatial layout, the treatment scale and the treatment process of rural domestic sewage treatment facilities, and can be popularized and applied in rural domestic sewage treatment special planning and rural environment comprehensive improvement scheme establishment.
Description
Technical Field
The invention relates to a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, and belongs to the technical field of environmental management.
Background
With the continuous improvement of the agricultural modernization degree, the rural water environment problem is increasingly prominent. Meanwhile, due to the influence of a binary structure of urban and rural economic and social development, the rural water environment infrastructure and treatment capacity are relatively weak, and the problems of rural water ecological environment safety and ecological protection are weak links of rural environmental protection work and key restriction factors of new rural construction development. Therefore, strengthening the construction of rural domestic sewage treatment facilities becomes an important content of rural environmental comprehensive treatment and ecological environment construction in China.
The rural domestic sewage treatment mode mainly comprises nano-tube treatment, centralized treatment and decentralized treatment, and the reasonable determination of the sewage treatment mode and the scale of treatment facilities is an important premise for realizing the maximization of the environmental benefit and the economic benefit of the rural domestic sewage. At present, most of related researches take construction investment and operation cost as consideration factors, and the influence of the whole process environment in the construction period and the operation period of a sewage facility is rarely brought into decision. Therefore, the factors such as the environmental impact and the treatment cost of the whole life cycle need to be comprehensively considered, the spatial layout, the treatment scale and the treatment process of rural domestic sewage treatment facilities are reasonably determined, the scientificity of the rural domestic sewage treatment mode decision process is improved, and the environmental benefit and the economic benefit of rural domestic sewage are maximized.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, which improves the scientificity of a rural domestic sewage treatment mode decision process, realizes the maximization of the environmental benefit and the economic benefit of rural domestic sewage treatment, and can be popularized and applied in rural domestic sewage treatment special planning and rural environment comprehensive improvement scheme establishment.
The technical scheme is as follows: in order to solve the technical problems, the invention provides a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, which comprises the following steps:
(1) adopting a spatial clustering algorithm to generate various rural domestic sewage spatial layout schemes, and combining the spatial layout schemes with various sewage treatment processes to form a plurality of alternative treatment mode schemes;
(2) performing inventory analysis on the sewage treatment facilities of each alternative scheme, establishing a life cycle evaluation model of the sewage treatment facilities, and calculating the environmental impact potential value of the whole life cycle;
(3) calculating the initial cost, the construction cost, the operation cost and the abandonment cost of each alternative scheme, constructing a life cycle cost model of the sewage treatment facility, and calculating the sewage treatment cost of the whole life cycle;
(4) and constructing an objective function according to the full life cycle environmental influence latent value and the treatment cost, and performing multi-objective optimization on all the treatment mode alternatives to obtain the optimal sewage treatment modes under different scene conditions.
Preferably, the step (1) adopts an improved k-means algorithm to perform spatial clustering, and the specific improvement process is as follows:
first, cluster y is constructed as follows j The population number and terrain elevation weight factors of each village are as follows:
in the formula, P xi * Population number weighting factor for village xi; p is xi Population size for village xi; p is min To cluster y j The minimum value of population number of villages; p max To cluster y j The maximum value of the population number of each village; alpha is alpha P Is P xi * Lower limit of (a) P ∈ (0,1)；CV P To cluster y j The coefficient of variation of the population number of each village represents the dispersion degree of the population number; p t Taking 10-20% as the population number variation coefficient threshold; z xi * Weighting factors for village terrain elevation; z xi Is the terrain elevation of village xi; z min To cluster y j The minimum value of the terrain elevation of each village; z max To cluster y j The maximum value of the terrain elevation of each village; alpha is alpha Z Is Z xi * Lower limit of (a) Z ∈(0,1)；CV Z To cluster y j The variation coefficient of the terrain elevation of each village represents the discrete degree of the terrain elevation; z is a linear or branched member t The threshold value of the terrain elevation variation coefficient is 10-20%.
α in the formula (1) P In order to prevent village P with the least population xi * A zero condition results in the denominator of the terms of equation (3) and equation (4) being zero. α in the formula (2) Z In order to avoid village Z with lowest terrain elevation xi * Equal to zero, resulting in zero for the abscissa and ordinate terms of village xi in equations (3) and (4).
Meanwhile, in order to avoid the population difference or too small terrain height difference of villages in the research area, P is amplified xi * And Z xi * By using a piecewise function to calculate P xi * And Z xi * . When the population number or the terrain elevation variation coefficient of the research area is less than or equal to a certain threshold value, the number of population of villages in the area is small in difference or the terrain is flat, and at the moment,P xi * or Z xi * Equal to 1.0, corresponding to neglecting the impact of population or terrain; when the population number of the research area or the terrain elevation variation coefficient is larger than a certain threshold value, the normalization function is adopted to calculate P xi * Or Z xi * 。
From the perspective of reducing investment cost and operating cost and reducing leakage of a pipe network, sewage treatment facilities are distributed near villages with large population and low terrain elevation as much as possible, so that the clustering y is corrected by adopting the following formula j The center coordinate calculation method of (2):
in the formula, X yj And Y yj Respectively as corrected cluster y j The abscissa and ordinate of the center; x xi And Y xi Are respectively village x i The abscissa and ordinate of (a); m is cluster y j The number of villages.
And finally, finishing spatial clustering of the sewage treatment facilities according to the other steps of the k-means algorithm.
Preferably, the various sewage treatment processes in the step (1) comprise mainstream rural biological sewage treatment processes such as an anaerobic-anoxic-aerobic process (AAO), an integrated sewage treatment MBR, a Sequencing Batch Reactor (SBR), a composite biofilter and the like.
Preferably, the inventory analysis in step (2) is to investigate and collect data of raw materials consumed, energy sources consumed and air pollutants, solid wastes and water pollutants discharged in the whole life cycle of the sewage treatment facility.
Preferably, the treatment cost of the sewage with the whole life cycle in the step (3) is LCC ═ C 1 +C 2 +C' 3 +C' 4 ，C 1 Is the initial cost, yuan; c 2 To buildSetting cost and yuan; c 3 ' is the total operating cost of the sewage treatment facility in the life cycle, Yuan; c 4 ' is the abandonment cost converted into the current cost, Yuan; wherein:
in the formula, C 3 The annual operation cost is high; c 4 The cost is waste; r is the mark rate,%; n is a radical of l The life of the sewage treatment facility is year.
Preferably, in the step (4), coordinates of central points of villages are obtained according to a research area administrative zoning map, a series of proposed sewage treatment facility numbers are set as a cluster number k, spatial clustering is performed by adopting a k-means algorithm to generate a plurality of rural domestic sewage spatial layout schemes, each cluster centroid generated by each spatial layout scheme is used as a sewage treatment facility proposed place, the number of village population corresponding to each cluster is counted, the corresponding rural domestic sewage discharge amount is calculated, the sewage treatment facility construction scale is determined, the distance from a village to a sewage treatment facility is measured and calculated, and the distance is used as a pipe network laying length for calculating the environmental impact potential value and the sewage treatment cost.
Preferably, the method for determining the optimal sewage treatment mode in the step (4) comprises the following steps: the environmental impact latent value and the treatment cost in the whole life cycle are normalized, and the calculation formula is as follows:
in the formula, EIP * And LCC * Respectively representing the environmental influence latent value and the treatment cost after normalization treatment; EIP and LCC are respectively the environmental impact potential value and the treatment cost of the whole life cycle; EIP max And LCC max Respectively the maximum value of environmental impact potential value and treatment cost, EIP min And LCC min Respectively is the minimum value of the environmental influence potential value and the treatment cost;
the environment influence potential value EIP of each alternative subjected to normalization processing * And treatment cost LCC * And the number of sewage treatment facilities N w Carrying out nonlinear fitting to obtain an environmental influence latent value objective function f corresponding to each sewage treatment process 1 (N w ) And an abatement cost objective function f 2 (N w )。
Converting a multi-objective optimization problem into a single-objective optimization problem by using a weighted summation method, wherein the objective function of a certain sewage treatment process is as follows:
min F(x)＝ω 1 f 1 (N w )+ω 2 f 2 (N w ) (9)
ω 1 +ω 2 ＝1 (10)
in the formula, N w Number of sewage treatment facilities, N w ∈[1,N v ]，N v Number of villages; omega 1 And ω 2 The weight coefficients of the environmental influence latent value and the treatment cost objective function respectively represent the importance degrees of the environmental influence latent value and the treatment cost objective function, omega 1 ,ω 2 ∈[0,1]；
By setting weight coefficients omega of a plurality of objective functions 1 And ω 2 And combining, namely solving an optimal solution of an objective function with the minimum environmental influence and the minimum treatment cost under different weight coefficient combination conditions by adopting a multi-objective optimization method (such as a sequential quadratic programming method), namely, the optimal sewage treatment facility construction quantity and sewage treatment process, as an optimal sewage treatment mode. When the alternative scheme of the spatial layout of the sewage treatment facility is generated by adopting a spatial clustering algorithm, the influence of the population number of villages and the terrain elevation factor on the clustering result is comprehensively considered, and the calculation of the clustering center coordinates is corrected by setting the weighting factorThe formula overcomes the defect that only the spatial distance is taken as the criterion of the clustering center, so that the clustering result of the spatial layout of the sewage treatment facility is more reasonable.
Has the advantages that: compared with the prior art, the rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm adopts the improved k-means spatial clustering algorithm to generate the rural domestic sewage spatial layout scheme, combines the full life cycle environmental impact evaluation technology and the sewage treatment cost accounting method, constructs an objective function by the full life cycle environmental impact latent value and the treatment cost, performs multi-objective optimization on all treatment mode alternative schemes to obtain the optimal sewage treatment modes under different scene conditions, improves the scientificity of the rural domestic sewage treatment mode decision process, realizes the maximization of the environmental benefit and the economic benefit of the rural domestic sewage treatment, and can be popularized and applied in the rural domestic sewage treatment special planning and the establishment of the rural environmental comprehensive treatment scheme.
Drawings
FIG. 1 is a view of a town level administrative division of area A;
FIG. 2 is a spatial distribution diagram of a village in area A;
FIG. 3 is a layout of rural sewage treatment facilities in area A (taking the numbers of sewage treatment facilities as 1, 5, 10 and 20 as examples).
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
In this embodiment, a district (district a) in a certain city of eastern China is taken as an example, and rural domestic sewage treatment and treatment mode optimization analysis based on a spatial clustering improvement algorithm is performed, wherein the district a has 1150 natural villages.
A rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm comprises the following steps:
(1) alternative scheme for determining rural domestic sewage treatment mode
Acquiring the geographic coordinates of 1150 natural villages according to the spatial distribution map (fig. 2) of villages in the area A, respectively setting a series of proposed sewage treatment facility numbers (1, 5, 10, 20, 50, 100, 200, 500 and 1150) as cluster numbers k, and performing spatial clustering by adopting an improved k-means algorithm to generate a plurality of rural domestic sewage spatial layout schemes, as shown in fig. 3. And taking each clustering centroid generated by each spatial layout scheme as a proposed place of the sewage treatment facility, counting the population number of villages corresponding to each cluster, calculating the corresponding rural domestic sewage discharge amount, determining the construction scale of the sewage treatment facility, measuring and calculating the distance from the villages to the sewage treatment facility, and taking the distance as the laying length of a pipe network.
Acquiring 1150 natural village central point coordinates according to a research area administrative zoning map, setting a series of proposed sewage treatment facility quantity as a clustering number k, improving a clustering central coordinate calculation method, performing spatial clustering by adopting an improved k-means algorithm, and generating a plurality of rural domestic sewage spatial layout schemes, wherein the specific improvement process comprises the following steps:
first, each cluster y is calculated as follows j The population number and terrain elevation weight factors of each village are as follows:
in the formula, P xi * A population number weighting factor for village xi; p xi Population size for village xi; p min To cluster y j The minimum value of population number of villages; p max To cluster y j The maximum value of the population number of each village; alpha is alpha P Is P xi * The lower limit of (2) is 0.1; CV of P To cluster y j The coefficient of variation of the population number of each village represents the dispersion degree of the population number; p is t Taking 15% as a population number variation coefficient threshold value; z is a linear or branched member xi * Weighting factors for village terrain elevation; z is a linear or branched member xi Is the terrain elevation of village xi; z min To cluster y j The minimum value of the terrain elevation of each village; z max To cluster y j Each village's topographyMaximum elevation; alpha is alpha Z Is Z xi * The lower limit of (3) is 0.1; CV of Z To cluster y j The variation coefficient of the terrain elevation of each village represents the discrete degree of the terrain elevation; z t Taking 15% as a terrain elevation variation coefficient threshold value;
the cluster y is corrected using the formula j The center coordinate calculation method of (2):
in the formula, X yj And Y yj Respectively as corrected cluster y j The abscissa and ordinate of the center; x xi And Y xi Are respectively village x i The abscissa and ordinate at the center may be, for example, the coordinates of the location of the village committee; m is cluster y j Number of villages;
and finally, finishing spatial clustering of the sewage treatment facilities according to the other steps of the k-means algorithm.
A plurality of rural domestic sewage spatial layout schemes and a plurality of sewage treatment processes (AAO, MBR, SBR and composite biofilter) are combined to form a plurality of alternative treatment mode schemes.
(2) Computing full lifecycle environmental impact latent values
Inventory analysis is performed for each alternative sewage treatment facility, including investigation and collection of raw materials, energy and emitted atmospheric pollutants, solid waste, water pollutants consumed throughout the life cycle of the sewage treatment facility. The data sources include various statistical yearbooks and reports, laboratory test data, books or treatises, research reports and design data, relevant environmental data manuals, and the like.
The construction phase list comprises construction materials (metal pipes, cement, bricks, gravel and the like), equipment (pumps, blowers, stirrers and the like), materials, equipment transportation andenergy (electricity, oil, coal) and resource (water) consumed in the construction process, and waste gas (CO) generated 2 、SO 2 、NO x CO, particulate matter, dust), wastewater (COD, TN, TP, SS, sulfide), solid waste (excavated earth, muck, inorganic waste).
The list of operational phases includes energy (electricity) and chemicals (sodium acetate, methanol, PAC, PAM, lime, chlorine, etc.), CO produced 2 、H 2 S waste gas, grid slag, sludge and other solid wastes.
The list of scrapped phases includes exhaust gas (CO) generated during demolition 2 、SO 2 、NO x CO, particulate matter, dust), waste water (COD, TN, TP, SS, sulphide), solid waste (concrete, brick, muck).
A life cycle influence evaluation software Open-LCA is adopted, and a life cycle evaluation model of rural domestic sewage treatment facilities is established by means of the prior art by means of an environmental load database ecoinvent and a CML2001 evaluation method. The full life cycle environmental impact is divided into 3 major categories: consumption of resources (non-biological and biological), environmental pollution (greenhouse effect, depletion of the ozone layer, human toxicity, ecotoxicity, acidification, eutrophication) and damage.
And according to the construction scale of the sewage treatment facility and the laying length of the pipe network in each alternative scheme, calculating the environmental impact potential value in the whole life cycle by utilizing the constructed life cycle evaluation model and according to the steps of characterization, standardization, weighting and the like. Firstly, obtaining various quantified environmental influences by applying a characterization model, then comparing the characterization results of the environmental influences with standardized references to obtain the standardized environmental influences, wherein the standardized references are the total amount of contribution substances under various environmental catalogues of specific countries or regions, and finally applying a weighting factor to combine the standardized results of the various environmental influences into a single value serving as a full life cycle environmental influence potential value.
(3) Calculating the full life cycle sewage treatment cost
The initial cost comprises the construction permission of the project, the project design planning, the cost of project site selection and preparation, the bid and tender work and the like; the construction cost comprises equipment purchase and installation cost, construction and construction cost of engineering and pipe networks, land cost (purchase) and other entrusted cost and the like; the operation cost comprises system and equipment maintenance, personnel wages, medicament investment, sludge treatment cost and the like; the abandonment cost comprises the cost of engineering demolition and treatment, environmental remediation, resource recovery and the like.
The current cost is converted from the long-term cost such as the operation cost, the abandonment cost and the like by adopting the current rate, so that the expenses generated in different time periods can be directly compared, and the calculation formula is as follows:
in the formula, C 3 The annual operation cost is high; c 3 ' is the total operating cost of the sewage treatment facility in the life cycle, Yuan; c 4 The cost is waste; c 4 ' is the abandonment cost converted into the current cost, Yuan; r is the mark rate,%; n is a radical of l The life of the sewage treatment facility is year.
The full life cycle cost calculation formula is as follows:
LCC＝C 1 +C 2 +C' 3 +C' 4 (7)
in the formula, C 1 Is the initial cost, yuan; c 2 The construction cost is high; LCC is the cost of sewage treatment in the whole life cycle, Yuan.
(4) Multi-objective optimization of treatment mode alternatives
The environmental impact latent value and the treatment cost in the whole life cycle are normalized, and the calculation formula is as follows:
in the formula, EIP * And LCC * Respectively representing the environmental influence latent value and the treatment cost after normalization treatment; EIP and LCC are respectively the environmental impact potential value and the treatment cost of the whole life cycle; EIP max And LCC max Respectively the maximum value of environmental impact potential value and treatment cost, EIP min And LCC min Respectively, the environmental impact potential value and the minimum value of the treatment cost.
The EIP of the environmental impact potential value of each alternative scheme after normalization processing * And treatment cost of LCC * And the number of sewage treatment facilities N w Carrying out nonlinear fitting to obtain an environmental influence potential value objective function f corresponding to each sewage treatment process 1 (N w ) And an abatement cost objective function f 2 (N w )。
Converting a multi-objective optimization problem into a single-objective optimization problem by using a weighted summation method, wherein the objective function of a certain sewage treatment process is as follows:
min F(x)＝ω 1 f 1 (N w )+ω 2 f 2 (N w ) (10)
ω 1 +ω 2 ＝1 (11)
in the formula, N w Number of sewage treatment facilities, N w ∈[1,1150]；ω 1 And ω 2 The weight coefficients of the environmental influence latent value and the treatment cost objective function respectively represent the importance degrees of the environmental influence latent value and the treatment cost objective function, omega 1 ,ω 2 ∈[0,1]。
By setting weight coefficients omega of a plurality of objective functions 1 And ω 2 And combining, namely solving an optimal solution of an objective function with the minimum environmental influence and the minimum treatment cost under different weight coefficient combination conditions by adopting a multi-objective optimization method (such as a sequential quadratic programming method), namely, the optimal sewage treatment facility construction quantity and the sewage treatment process, as an optimal sewage treatment mode.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention, and such modifications and adaptations are intended to be within the scope of the invention.
Claims (7)
1. A rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm is characterized by comprising the following steps:
(1) adopting a spatial clustering improved algorithm to generate various rural domestic sewage spatial layout schemes, and combining the spatial layout schemes with various sewage treatment processes to form a plurality of alternative treatment mode schemes;
(2) performing inventory analysis on the sewage treatment facilities of each alternative scheme, establishing a life cycle evaluation model of the sewage treatment facilities, and calculating the environmental impact potential value of the whole life cycle;
(3) calculating the initial cost, the construction cost, the operation cost and the abandonment cost of each alternative scheme, constructing a life cycle cost model of the sewage treatment facility, and calculating the sewage treatment cost of the whole life cycle;
(4) and constructing an objective function according to the full life cycle environmental influence latent value and the treatment cost, and performing multi-objective optimization on all the treatment mode alternatives to obtain the optimal sewage treatment modes under different scene conditions.
2. The rural domestic sewage treatment mode optimization method based on the spatial clustering improvement algorithm according to claim 1, characterized in that: in the step (1), the coordinates of the central points of villages are obtained according to the administrative zoning map of the research area, a series of proposed sewage treatment facility quantities are set as the clustering number k, the clustering center coordinate calculation method is improved, the improved k-means algorithm is adopted for spatial clustering, and a plurality of rural domestic sewage spatial layout schemes are generated, wherein the specific improvement process is as follows:
first, a cluster y is constructed as follows j The population number and terrain elevation weight factors of each village are as follows:
in the formula, P xi * Population number weighting factor for village xi; p xi Population size for village xi; p min To cluster y j The minimum value of population number of villages; p max To cluster y j The maximum value of the population number of each village; alpha is alpha P Is P xi * Lower limit of (a) P ∈(0,1)；CV P To cluster y j The coefficient of variation of the population number of each village represents the dispersion degree of the population number; p t Taking 10-20% as the population number variation coefficient threshold; z xi * Weighting factors for village terrain elevation; z xi Is the terrain elevation of village xi; z min To cluster y j The minimum value of the terrain elevation of each village; z max To cluster y j The maximum value of the terrain elevation of each village; alpha is alpha Z Is Z xi * Lower limit of (a) Z ∈(0,1)；CV Z To cluster y j The variation coefficient of the terrain elevation of each village represents the discrete degree of the terrain elevation; z t Taking 10% -20% as a terrain elevation variation coefficient threshold value;
the cluster y is corrected using the following equation j The center coordinate calculation method of (2):
in the formula, X yj And Y yj Respectively as corrected cluster y j The abscissa and ordinate of the center; x xi And Y xi Are respectively village x i The abscissa and ordinate of (a); m is cluster y j Number of villages;
and finally, finishing spatial clustering of the sewage treatment facilities according to the other steps of the k-means algorithm.
3. The rural domestic sewage treatment mode optimization method based on the spatial clustering improvement algorithm according to claim 1, characterized in that: the various sewage treatment processes in the step (1) comprise an anaerobic-anoxic-aerobic process AAO, an integrated sewage treatment MBR, a Sequencing Batch Reactor (SBR) and a composite biofilter.
4. The rural domestic sewage treatment mode optimization method based on the spatial clustering improvement algorithm according to claim 1, characterized in that: and (3) in the step (2), inventory analysis is carried out on data of raw materials and energy consumed in the whole life cycle of the sewage treatment facility, and data of discharged atmospheric pollutants, solid wastes and water body pollutants are investigated and collected.
5. The rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm according to claim 1, characterized in that: the sewage treatment cost (LCC ═ C) of the whole life cycle in the step (3) 1 +C 2 +C' 3 +C' 4 ，C 1 Initial cost, yuan; c 2 The construction cost is high; c 3 ' is the total operating cost of the sewage treatment facility in the life cycle, Yuan; c 4 ' is the abandonment cost converted into the current cost, Yuan; wherein:
in the formula, C 3 The annual operating cost is high; c 4 Cost of abandonment, Yuan; r is the mark rate,%; n is a radical of hydrogen l The service life of the sewage treatment facility is year.
6. The rural domestic sewage treatment mode optimization method based on the spatial clustering improvement algorithm according to claim 1, characterized in that: in the step (4), each clustering centroid generated by each spatial layout scheme is used as a sewage treatment facility construction place, the population number of villages corresponding to each cluster is counted, the corresponding rural domestic sewage discharge amount is calculated, the sewage treatment facility construction scale is determined, the distance from the villages to the sewage treatment facility is measured and calculated, and the distance is used as the pipe network laying length and is used for calculating the environmental impact potential value and the sewage treatment cost.
7. The rural domestic sewage treatment mode optimization method based on the spatial clustering improvement algorithm according to claim 1, characterized in that: the method for determining the optimal sewage treatment mode in the step (4) comprises the following steps: the environmental impact potential value and the treatment cost of the whole life cycle are normalized, and the calculation formula is as follows:
in the formula, EIP * And LCC * Respectively representing the environmental influence latent value and the treatment cost after normalization treatment; EIP and LCC are respectively the environmental impact potential value and the treatment cost of the whole life cycle; EIP max And LCC max Respectively the maximum value of environmental impact potential value and treatment cost, EIP min And LCC min Respectively is the minimum value of the environmental influence potential value and the treatment cost;
the EIP of the environmental impact potential value of each alternative scheme after normalization processing * And treatment cost of LCC * And the number of sewage treatment facilities N w Carrying out nonlinear fitting to obtain an environmental influence latent value objective function f corresponding to each sewage treatment process 1 (N w ) And an abatement cost objective function f 2 (N w )；
Converting a multi-objective optimization problem into a single-objective optimization problem by using a weighted summation method, wherein the objective function of a certain sewage treatment process is as follows:
minF(x)＝ω 1 f 1 (N w )+ω 2 f 2 (N w ) (9)
ω 1 +ω 2 ＝1 (10)
in the formula, N w Number of sewage treatment facilities, N w ∈[1,N v ]，N v Number of villages; omega 1 And ω 2 The weight coefficients of the environmental influence latent value and the treatment cost objective function respectively represent the importance degrees of the environmental influence latent value and the treatment cost objective function, omega 1 ,ω 2 ∈[0,1]；
By setting weight coefficients omega of a plurality of objective functions 1 And ω 2 And combining, namely solving an optimal solution of an objective function with the minimum environmental influence and the minimum treatment cost under different weight coefficient combination conditions by adopting a multi-objective optimization method, namely, the optimal sewage treatment facility construction quantity and sewage treatment process, as an optimal sewage treatment mode.
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| CN117195016A (en) * | 2023-11-07 | 2023-12-08 | 长江三峡集团实业发展(北京)有限公司 | Sewage treatment mode determining method and device, computer equipment and storage medium |
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2022
- 2022-04-29 CN CN202210475598.4A patent/CN114897233A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117195016A (en) * | 2023-11-07 | 2023-12-08 | 长江三峡集团实业发展(北京)有限公司 | Sewage treatment mode determining method and device, computer equipment and storage medium |
| CN117195016B (en) * | 2023-11-07 | 2024-02-06 | 长江三峡集团实业发展(北京)有限公司 | Sewage treatment mode determining method and device, computer equipment and storage medium |
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