A water distribution method for a water treatment plant
By establishing a hierarchical structure and combining subjective and objective methods to calculate the water allocation weight of water purification facilities, the problems of facility overload and low efficiency in traditional methods are solved, and the rational utilization and efficiency improvement of facilities are realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN TANGGU SINO FRENCH WATER SUPPLY CO LTD
- Filing Date
- 2026-05-11
- Publication Date
- 2026-07-31
AI Technical Summary
Traditional water purification facilities rely on experience-based judgment or proportional allocation for water distribution, which leads to facility overload, accelerated equipment aging, and increased chemical and electricity consumption, affecting the quality of effluent and operational efficiency.
By adopting a hierarchical structure and combining subjective hierarchical analysis and objective entropy weighting, the final combined weight of each water purification facility is calculated through a combined weighting formula to scientifically and rationally allocate water volume.
This approach enables the rational use of facilities, extends equipment lifespan, reduces chemical and electrical consumption, improves the efficiency of the water purification system, adapts to seasonal changes, and achieves a win-win situation for both economic and environmental benefits.
Smart Images
Figure CN122491798A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of water distribution technology, and in particular to a water distribution method for water purification facilities in a water plant. Background Technology
[0002] During water plant operation, it is typically necessary to rationally allocate raw water or treated water to multiple parallel-operating water purification facilities. Traditional water allocation methods often rely on the experience and judgment of operators or employ simple proportional allocation, lacking a comprehensive consideration of the actual performance of each purification facility. This allocation method is not only highly subjective and arbitrary, making it difficult to fully utilize the technical advantages of each facility, but may also lead to overload operation of some facilities, accelerated equipment aging, and increased chemical and electrical consumption, thereby affecting the effluent quality and operational efficiency of the entire water purification system. Therefore, there is an urgent need for a scientifically sound and dynamically adjustable water allocation method for water plant purification facilities that can balance subjective experience with objective data. Summary of the Invention
[0003] This application provides a water distribution method for a water treatment plant, which at least solves the problems affecting the effluent quality and operational efficiency of the entire water treatment system in related technologies:
[0004] This application provides a method for distributing water volume in a water treatment plant's water purification facility, the method comprising:
[0005] S1: Establish a hierarchical structure, which includes a target layer A, a criterion layer B, and a scheme layer C in sequence. The target layer A is the water volume allocation weight of the water plant's water purification facilities. The criterion layer B includes factors that affect the water rights allocation of the water plant's water purification facilities. The scheme layer C includes multiple water purification facilities that need to be allocated water volume.
[0006] S2: Based on the hierarchical structure, the subjective weights of each water purification facility in scheme layer C are calculated using both subjective and objective methods. and objective weight ;
[0007] S3: The subjective weights and the objective weights Substituting into the combined weighting formula, the final combined weight of each water purification facility is calculated. And according to the final combined weight Water volume is allocated to each water purification facility.
[0008] Furthermore, the factors influencing water rights allocation in the water treatment facility of the criterion layer B include turbidity removal rate. Operational stability Impact resistance and operational economy At least one of them.
[0009] Furthermore, subjective methods include:
[0010] Based on the hierarchical structure, a judgment matrix P is constructed;
[0011] Calculate the relative weights of the judgment matrix P to obtain the eigenvectors. ;
[0012] Perform a consistency check on the judgment matrix P and calculate the consistency ratio CR;
[0013] When the consistency ratio CR is less than 0.1, the feature vector is... As the subjective weight .
[0014] Furthermore, constructing the judgment matrix P further includes:
[0015] The importance of elements at the upper and lower levels in the hierarchical structure is compared and assigned using the 1-9 scale.
[0016] Furthermore, objective methods include:
[0017] Based on the influencing factors of the criterion layer B and the water purification facilities of the scheme layer C, a database X with multiple evaluation objects and multiple influencing factors is constructed.
[0018] The data in the database X is normalized.
[0019] Calculate the entropy value for each evaluation object. ;
[0020] According to the entropy value Calculate the weight of each evaluation object under the objective method, as the objective weight. .
[0021] Furthermore, data normalization processing further includes:
[0022] For data where larger values are preferred, normalization is performed using a formula:
[0023] ;
[0024] For data where smaller values are preferred, normalization is performed using the following formula:
[0025] ;
[0026] in, The maximum value among identical data. It is the minimum value among the same data.
[0027] Furthermore, the formula for combined weighting is:
[0028] ;
[0029] in, For the final combined weights, Subjective weighting, For objective weights, i = 1, 2, ..., n, where n is the number of water purification facilities in the scheme layer. The objective weight is the proportion of the objective weight in the combined weighting.
[0030] Furthermore, the proportionality coefficient is calculated using the following formula:
[0031] ;
[0032] in, Subjective weight The values are rearranged in ascending order, where n represents the number of water purification facilities in the scheme layer.
[0033] Furthermore, based on the seasonal variations in residential water consumption and water plant supply, the final combined weights of each water purification facility are calculated and adjusted quarterly. .
[0034] Furthermore, the water purification facilities in the solution layer C include water purification facilities. Water purification facilities and water purification facilities .
[0035] The application employs the above technical solution and has at least the following beneficial effects:
[0036] This method establishes a hierarchical structure, comprehensively utilizes subjective analytic hierarchy process (AHP) and objective entropy weighting, and introduces a combined weighting formula to organically combine subjective experience with objective operational data. Compared to traditional methods that rely on experience or proportional allocation, this method can scientifically and rationally allocate the treatment capacity of each water purification facility, effectively avoiding facility overload or idleness, fully leveraging the technical advantages of each facility, extending equipment lifespan, reducing chemical and power consumption, and improving the overall operational efficiency of the water purification system. It achieves a win-win situation for both economic and environmental benefits while ensuring effluent quality. Furthermore, this method supports dynamic quarterly weight adjustments, adapting to seasonal changes in water volume and quality, and possesses strong practicality and adaptability.
[0037] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0039] Figure 1 This is a flowchart provided in an embodiment of the present invention;
[0040] Figure 2 This is a schematic diagram of the hierarchical structure of water rights allocation in a water purification facility provided in an embodiment of the present invention;
[0041] Figure 3 This is a table of meanings of influencing factors at the criterion level provided in this embodiment of the invention;
[0042] Figure 4 This is a table of meanings for the scaling method provided in the embodiments of the present invention;
[0043] Figure 5 This is a random consistency index table provided in the embodiments of the present invention. Detailed Implementation
[0044] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.
[0045] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0046] This invention provides a method for water allocation among water purification facilities in a water plant. This method establishes a hierarchical structure, calculates the water allocation weight for each purification facility using both subjective and objective methods, and then obtains the final combined weight through a combined weighting formula. Water is then allocated to the purification facilities based on this final combined weight. This method can be applied to water allocation among multiple purification facilities in water treatment systems such as water supply plants and wastewater treatment plants.
[0047] like Figure 1 and Figure 2 As shown, a hierarchical structure that conforms to the actual situation of the water plant is first established. The hierarchical structure includes a target layer A, a criterion layer B, and a scheme layer C. The target layer A represents the water volume allocation weight of the water plant's water purification facilities. The criterion layer B includes factors that affect the water rights allocation of the water plant's water purification facilities. In this embodiment, the selected influencing factors include turbidity removal rate. Operational stability Impact resistance and operational economy There are four indicators in total. The meaning of each influencing factor is as follows: Figure 3 As shown.
[0048] Solution layer C includes multiple water purification facilities that require water allocation. In this embodiment, solution layer C includes three water purification facilities, namely water purification facilities... Water purification facilities and water purification facilities It should be noted that, in other embodiments, the influencing factors in criterion layer B can be added or removed according to the actual situation of the water plant, and the number of water purification facilities in scheme layer C can also be increased or decreased according to the actual configuration of the water plant.
[0049] After establishing the hierarchical structure, the subjective weights of each water purification facility in scheme layer C were calculated using both subjective and objective methods. and objective weight , where i represents the serial number of the water purification facility, i=1,2,...,n, and n is the number of water purification facilities in the scheme layer.
[0050] Specifically, the calculation process for both subjective and objective methods is as follows:
[0051] 1. Subjective method to calculate subjective weights.
[0052] The subjective approach is based on the Analytic Hierarchy Process (AHP), and the specific steps are as follows:
[0053] First, based on the established hierarchical structure, a judgment matrix P is constructed. When constructing the judgment matrix P, the 1-9 scaling method is used to compare and assign values to the importance of elements at the upper and lower levels in the hierarchical structure. The meaning of the 1-9 scaling method is as follows: Figure 4 As shown.
[0054] For example, for target layer A and criterion layer B, the importance of each factor in criterion layer B to target layer A is compared and assigned a value, and a judgment matrix is constructed. Similarly, for each factor in criterion layer B and solution layer C, the importance of each water purification facility in solution layer C to that factor is compared and assigned a value, and a judgment matrix is constructed accordingly.
[0055] Secondly, the relative weights of the judgment matrix P are calculated to obtain the eigenvectors. The specific calculation process is as follows:
[0056] Calculate the product of the elements in each row of the judgment matrix P. The formula is:
[0057] ;
[0058] Where i = 1, 2, ..., n.
[0059] Recalculate The formula for the nth root is: .
[0060] For vectors The normalization process is performed using the following formula:
[0061] ;
[0062] Then the eigenvector This refers to the relative weight of this level relative to the level above it.
[0063] Then, a consistency check is performed on the judgment matrix P, and the largest eigenvalue of the judgment matrix P is calculated. The formula is:
[0064] ;
[0065] in, .
[0066] The consistency index (CI) is calculated using the following formula:
[0067] .
[0068] Based on the order n of the judgment matrix P, the RI value is obtained by looking up the random consistency index table. The values of the random consistency index RI are as follows: Figure 5 As shown, the consistency ratio CR is calculated using the following formula: ;
[0069] When CR is less than 0.1, the consistency of the judgment matrix P is within an acceptable range, and the eigenvectors are then... As subjective weight If CR is greater than or equal to 0.1, the judgment matrix P must be rescored and recalculated.
[0070] Finally, the relative weights of criterion layer B with respect to target layer A and the relative weights of scheme C with respect to each factor of criterion layer B are multiplied and summed to obtain the weights of scheme C with respect to target layer A, i.e., the water allocation weights of each water purification facility under the subjective method. .
[0071] Taking the three water purification facilities in this embodiment as an example, let the relative weight of criterion layer B to target layer A be ( The relative weights of each factor in scheme layer C to criterion layer B are as follows: ), ( ), ( ), ( ),but:
[0072] ;
[0073] ;
[0074] ;
[0075] This yields the subjective weight. .
[0076] 2. Objective weights are calculated using objective methods.
[0077] The objective method is based on the entropy weight method. The specific steps are as follows:
[0078] First, based on the influencing factors in criterion layer B and the water purification facilities in scheme layer C, a database X is constructed containing multiple evaluation objects and multiple influencing factors. Taking this embodiment as an example, a database X containing 3 evaluation objects and 4 influencing factors is constructed; the 3 evaluation objects are the water purification facilities. Water purification facilities and water purification facilities Four influencing factors, namely turbidity removal rate Operational stability Impact resistance and operational economy , ,in Let m be the m-th data point for the i-th evaluation object under the j-th influencing factor, where i=1,2,3; j=1,2,3,4; m=1,2,...,n.
[0079] Secondly, the data in database X is normalized. Different formulas are used for normalization depending on the nature of the data.
[0080] For data where larger values are preferred, such as turbidity removal rate and operational stability, the formula is used:
[0081] ;
[0082] For data where smaller values are preferred, such as resilience and operational economy, the formula is used:
[0083] ;
[0084] in, The maximum value among identical data. It is the minimum value among the same data.
[0085] Then, calculate the entropy value for each evaluation object. The formula for calculating entropy is:
[0086] ;
[0087] in , ,when season .
[0088] Finally, based on the entropy value Calculate the weight of each evaluation object under the objective method, as the objective weight. The calculation formula is:
[0089] ;
[0090] In the formula , Thus, the objective weight vector is obtained. .
[0091] 3. Calculate the final combined weights by assigning weights to the combination.
[0092] Subjective weights obtained through subjective methods and objective weights obtained through objective methods Substituting into the combined weighting formula, the final combined weight of each water purification facility is calculated. .
[0093] The formula for combined weighting is:
[0094] ;
[0095] Where i = 1, 2, ..., n, and n is the number of water purification facilities in the scheme layer. This represents the proportion of objective weights in the portfolio weighting.
[0096] proportionality coefficient Calculated using the following formula:
[0097] ;
[0098] in, Subjective weight The values are rearranged in ascending order, where n represents the number of water purification facilities in the scheme layer.
[0099] In this embodiment, n=3, therefore .
[0100] The calculated Substituting the values into the combination weighting formula, we can obtain the final combination weights of each water purification facility. Based on the final combined weights Water volume is allocated to each water purification facility. For example, if the total inflow to the water plant at a certain moment is Q, then the water volume is allocated to the water purification facilities. The amount of water is .
[0101] 4. Specific application examples.
[0102] The following example, taken from a water plant, illustrates the specific application of this method.
[0103] The water plant has three water purification facilities, namely: , and Select turbidity removal rate Operational stability Impact resistance and operational economy As a criterion-level influencing factor.
[0104] Based on expert scoring, a judgment matrix is constructed and a consistency test is performed (CR < 0.1). The relative weights of criterion layer B to target layer A are calculated as follows: =0.4, =0.3, =0.2, =0.1.
[0105] The relative weights of each factor in the criterion layer B from the alternative layer C are calculated as follows:
[0106] For turbidity removal rate : =0.5, =0.3, =0.2;
[0107] For operational stability : =0.4, =0.4, =0.2;
[0108] Impact resistance : =0.3, =0.3, =0.4;
[0109] For operational economy : =0.2, =0.3, =0.5.
[0110] The subjective weights are calculated as follows:
[0111] =0.4×0.5+0.3×0.4+0.2×0.3+0.1×0.2=0.4;
[0112] =0.4×0.3+0.3×0.4+0.2×0.3+0.1×0.3=0.33;
[0113] =0.4×0.2+0.3×0.2+0.2×0.4+0.1×0.5=0.27;
[0114] Subjective weight =(0.4,0.33,0.27).
[0115] Operational data of various water purification facilities under four influencing factors were collected and a database was constructed. After normalization, an objective weight vector was calculated. =(0.35,0.35,0.3).
[0116] Arrange the subjective weights in ascending order: =0.27, =0.33, =0.4, n=3.
[0117] Calculate the proportionality coefficient :
[0118] =(3 / 2)×[(2 / 3)(0.27+2×0.33+3×0.4)-4 / 3]=0.1305.
[0119] Calculate the final combination weights:
[0120] =(1-0.1305)×0.4+0.1305×0.35=0.3935;
[0121] =(1-0.1305)×0.33+0.1305×0.35=0.3326;
[0122] =(1-0.1305)×0.27+0.1305×0.3=0.274;
[0123] That is, the final combined weight vector =(0.3935,0.3326,0.274).
[0124] Water volume is allocated based on this final combined weight. If the total inflow to the water plant is 10,000... Then it is allocated to water purification facilities. The water volume is 3935 Distributed to water purification facilities The water volume is 3326 Distributed to water purification facilities The net water volume is 2740 .
[0125] 5. Seasonal adjustments.
[0126] Because residential water consumption and water plant supply vary seasonally, this method also includes calculating and adjusting the final combined weights of each water purification facility on a quarterly basis. That is, at the beginning of each quarter, the operational data of the most recent quarter is collected again, and the objective weights are recalculated. Subjective weights are adjusted based on the latest expert scores or historical experience. Then calculate the new final combination weights. To adapt to changes in water volume and quality in different seasons.
[0127] This method establishes a hierarchical structure, comprehensively considering the influence of subjective human experience and objective operational data of water purification facilities on water allocation. It organically combines subjective and objective weights through a weighting formula, avoiding both the subjectivity and arbitrariness of allocation based solely on experience and the shortcomings of relying solely on data calculations that are detached from actual operating conditions. This method can scientifically, rationally, and accurately allocate the treatment volume of each water purification facility, fully leveraging the technical advantages of each facility, extending equipment lifespan, improving the operational efficiency of the water purification system, optimizing chemical and power consumption, and achieving a win-win situation for both economic and environmental benefits while ensuring effluent water quality.
[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A water distribution method for a water treatment plant purification facility, characterized by, Includes the following steps: S1: Establish a hierarchical structure, which includes a target layer A, a criterion layer B, and a scheme layer C in sequence. The target layer A is the water volume allocation weight of the water plant's water purification facilities. The criterion layer B includes factors that affect the water rights allocation of the water plant's water purification facilities. The scheme layer C includes multiple water purification facilities that need to be allocated water volume. S2: Based on the hierarchical structure, the subjective weights of each water purification facility in scheme layer C are calculated using both subjective and objective methods. and objective weight ; S3: The subjective weights and the objective weights Substituting into the combined weighting formula, the final combined weight of each water purification facility is calculated. And according to the final combined weight Water volume is allocated to each water purification facility.
2. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that: The factors influencing water rights allocation in water treatment facilities, as defined in criterion layer B, include turbidity removal rate. Operational stability Impact resistance and operational economy At least one of them.
3. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that, The subjective methods include: Based on the hierarchical structure, a judgment matrix P is constructed; Calculate the relative weights of the judgment matrix P to obtain the eigenvectors. ; Perform a consistency check on the judgment matrix P and calculate the consistency ratio CR; When the consistency ratio CR is less than 0.1, the feature vector is... As the subjective weight .
4. The water distribution method for water purification facilities in a water plant according to claim 3, characterized in that, Constructing the judgment matrix P further includes: The importance of elements at the upper and lower levels in the hierarchical structure is compared and assigned using the 1-9 scale.
5. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that, The objective methods include: Based on the influencing factors of the criterion layer B and the water purification facilities of the scheme layer C, a database X with multiple evaluation objects and multiple influencing factors is constructed. The data in the database X is normalized. Calculate the entropy value for each evaluation object. ; According to the entropy value Calculate the weight of each evaluation object under the objective method, as the objective weight. .
6. The water distribution method for water purification facilities in a water plant according to claim 5, characterized in that, Data normalization further includes: For data where larger values are preferred, normalization is performed using a formula: ； For data where smaller values are preferred, normalization is performed using the following formula: ； in, The maximum value among identical data. It is the minimum value among the same data.
7. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that, The combined weighting formula is as follows: ； in, For the final combined weights, Subjective weighting, For objective weights, i = 1, 2, ..., n, where n is the number of water purification facilities in the scheme layer. The objective weight is the proportion of the objective weight in the combined weighting.
8. The water distribution method for water purification facilities in a water plant according to claim 7, characterized in that, The proportionality coefficient is calculated using the following formula: ； in, Subjective weight The values are rearranged in ascending order, where n represents the number of water purification facilities in the scheme layer.
9. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that, The method further includes: The final combined weights of each water purification facility are calculated and adjusted quarterly based on seasonal variations in residential water consumption and water plant supply. .
10. The water distribution method for water purification facilities in a water plant according to claim 1, characterized in that: The water purification facilities in scheme layer C include water purification facilities. Water purification facilities and water purification facilities .