Secondary chlorination system for long-distance water distribution network based on control of disinfection by-products

Abstract

The present application provides a long-distance water distribution network secondary chlorination system based on controlling disinfection by-products, which relates to the field of water supply control technology, including: a residual chlorine concentration prediction module for predicting the residual chlorine concentration of a predetermined water distribution plan; a secondary chlorination point site selection module for selecting the site of a secondary chlorination point; a secondary chlorination decision module for making secondary chlorination decisions based on the chlorination scene registration threshold, combined with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan; a secondary chlorination optimization module for performing multi-order optimization according to a secondary chlorination multi-order optimization algorithm; a secondary chlorination module for performing secondary chlorination of a long-distance water distribution network according to a secondary chlorination optimization strategy. The present application can solve the technical problem in the prior art that excessive disinfection by-products will be generated due to secondary chlorination, affecting water quality safety. Through a multi-order optimization algorithm, the amount of chlorination can be dynamically adjusted to effectively reduce the generation of disinfection by-products, thereby improving water quality safety.

Description

Technical Field

[0001] The present application relates to the technical field of water supply control, and in particular to a secondary chlorination system for a long-distance water distribution network based on controlling disinfection by-products. Background Art

[0002] Secondary chlorination of long-distance water distribution networks is an effective disinfection optimization strategy to ensure water quality safety. The purpose is to eliminate bacteria or other microorganisms that may grow in the water distribution network and ensure that the water can still meet the sanitary standards for drinking water when it is delivered to users. However, since the re-dosing of chlorine will lead to an increase in disinfection by-products, especially when the total chlorine dosage and the timing of chlorination are not appropriate, it may cause the concentration of trihalomethanes (TCM) and haloacetic acids (such as DCAA, TCAA) to exceed the standard, thereby endangering human health. Existing secondary chlorination methods usually rely on fixed chlorination concentrations and chlorination timings, without considering the specific conditions of water quality and the network, which often leads to the generation of excessive disinfection by-products.

[0003] In summary, the prior art has a technical problem that secondary chlorination will produce excessive disinfection by-products, which are harmful to water quality and human health, and further affect water quality safety. Summary of the invention

[0004] The purpose of this application is to provide a long-distance water distribution network secondary chlorination system based on controlling disinfection by-products, so as to solve the technical problem in the prior art that secondary chlorination will produce excessive disinfection by-products, which is harmful to water quality and human health and further affects water quality safety.

[0005] In view of the above problems, the present application provides a long-distance water distribution network secondary chlorination system based on controlling disinfection by-products, wherein the long-distance water distribution network secondary chlorination system based on controlling disinfection by-products comprises: a residual chlorine concentration prediction module, the residual chlorine concentration prediction module is used to predict the residual chlorine concentration of a predetermined water distribution plan of the long-distance water distribution network, and obtain a predicted residual chlorine concentration set; a secondary chlorination point site selection module, the secondary chlorination point site selection module is used to select the secondary chlorination point of the long-distance water distribution network according to the predicted residual chlorine concentration set, and obtain a secondary chlorination point site selection plan; a secondary chlorination point A decision module, wherein the secondary chlorination decision module is used to make a secondary chlorination decision based on the chlorination scenario alignment threshold, in combination with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, and establish a secondary chlorination decision space; a secondary chlorination optimization module, wherein the secondary chlorination optimization module is used to perform multi-order optimization on the secondary chlorination decision space according to the embedded secondary chlorination multi-order optimization algorithm, and determine the secondary chlorination optimization strategy; a secondary chlorination module, wherein the secondary chlorination module is used to perform secondary chlorination on the long-distance water distribution network based on the predetermined water distribution plan and according to the secondary chlorination optimization strategy.

[0006] The technical solution provided in this application has at least the following technical effects or advantages:

[0007] Through the residual chlorine concentration prediction module, the residual chlorine concentration prediction module is used to predict the residual chlorine concentration of the predetermined water distribution plan of the long-distance water distribution network to obtain a predicted residual chlorine concentration set; the secondary chlorination point site selection module, the secondary chlorination point site selection module is used to select the secondary chlorination point for the long-distance water distribution network according to the predicted residual chlorine concentration set, and obtain a secondary chlorination point site selection plan; the secondary chlorination decision module, the secondary chlorination decision module is used to make a secondary chlorination decision based on the chlorination scene alignment threshold, combined with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, and establish a secondary chlorination decision space; the secondary chlorination optimization module, the secondary chlorination optimization module is used to perform multi-order optimization on the secondary chlorination decision space according to the embedded secondary chlorination multi-order optimization algorithm, and determine the secondary chlorination optimization strategy; the secondary chlorination module, the secondary chlorination module is used to perform secondary chlorination on the long-distance water distribution network based on the predetermined water distribution plan and the secondary chlorination optimization strategy. In other words, by predicting the residual chlorine concentration at different pipeline locations and at different time points, the chlorination points are accurately selected, and the chlorination amount is dynamically adjusted through a multi-order optimization algorithm to ensure that the chlorination amount in each area is at the optimal level, which can not only ensure the disinfection effect, but also reduce the generation of disinfection by-products and improve water quality safety.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0010] Figure 1 This is a schematic diagram of the structure of the secondary chlorination system for a long-distance water distribution network based on controlling disinfection by-products in this application;

[0011] Figure 2 This is a flow chart of determining the optimal secondary chlorination strategy in a secondary chlorination system for a long-distance water distribution network for controlling disinfection by-products in this application.

[0012] Explanation of the reference numerals: residual chlorine concentration prediction module 11, secondary chlorination point site selection module 12, secondary chlorination decision module 13, secondary chlorination optimization module 14, secondary chlorination module 15. DETAILED DESCRIPTION

[0013] This application solves the technical problem in the prior art that excessive disinfection by-products will be generated due to secondary chlorination, which is harmful to water quality and human health and further affects water quality safety by providing a long-distance water distribution network secondary chlorination system based on controlling disinfection by-products. By predicting the residual chlorine concentration at different network locations and different time points, the chlorination point is accurately selected, and the chlorination amount is dynamically adjusted through a multi-order optimization algorithm to ensure that the chlorination amount in each area is at the optimal level, which can not only ensure the disinfection effect, but also reduce the generation of disinfection by-products, thereby improving water quality safety.

[0014] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0015] For examples, please see the attached Figure 1 The present application provides a long-distance water distribution network secondary chlorination system based on controlling disinfection by-products, wherein the long-distance water distribution network secondary chlorination system based on controlling disinfection by-products comprises:

[0016] The residual chlorine concentration prediction module 11 is used to predict the residual chlorine concentration of a predetermined water distribution plan of a long-distance water distribution network to obtain a predicted residual chlorine concentration set.

[0017] Specifically, the long-distance water distribution network refers to the water distribution pipeline system that transports tap water from the water plant to each user. It usually covers a wide geographical area, with long pipelines, and the areas involved may include cities, towns, and rural areas. Due to the long length and wide area of ​​the pipeline network, factors such as water flow rate, pipeline materials, and water quality will vary with location. The predetermined water distribution plan refers to the water delivery plan preset based on water source, demand, geographical location and other conditions when the water leaves the water plant, taking into account the water supply pressure, flow and water quality requirements in different regions, with the aim of ensuring that each user can get a stable water source in different time periods.

[0018] The water flow rate measured in each water distribution node and pipe network is measured by flow meter; the initial chlorine concentration, temperature, pH value, chemical oxygen demand and other factors affecting chlorine attenuation in the water are collected; the pipe network characteristics, including pipe length, diameter, material (such as steel pipe, plastic pipe), etc., affect the propagation speed and attenuation rate of chlorine; the initial residual chlorine concentration, that is, the residual chlorine concentration of the water discharged from the water plant, is collected. In most water pipe network applications, the attenuation of chlorine can usually be well described by the first-order reaction kinetic model, because under stable flow conditions, the attenuation of chlorine is mainly exponentially related to its concentration. The attenuation rate constant is estimated through experimental data or existing literature data. The higher the temperature, the faster the chlorine decay rate. In general, the attenuation rate doubles for every 10°C increase in temperature; the attenuation of chlorine is closely related to the pH value. Generally, in an acidic environment, chlorine decays more rapidly; the reaction of organic matter with chlorine also affects the attenuation rate. For example, suppose that through experimental data or literature search, the attenuation rate constant of a certain pipe network section is obtained as 0.02h -1 , that is, the chlorine concentration decays by 2% per hour. This value can be adjusted according to specific conditions.

[0019] Use the residual chlorine concentration of the factory water as the initial value, select the time range to be predicted (such as 24 hours), and set the pipe network area. Apply the first-order reaction kinetic model to calculate the residual chlorine concentration at each time and each pipe network node. For example, assuming that the initial residual chlorine concentration of a pipe network is 1.0 mg / L, the residual chlorine concentration after 24 hours is calculated to be 0.62 mg / L. By setting a residual chlorine sensor in the pipe network, the actual residual chlorine concentration is monitored in real time and compared with the predicted value. If the predicted value deviates greatly from the actual value, the model parameters, such as the decay rate constant, need to be adjusted. After model verification, an accurate first-order reaction kinetic model, namely the residual chlorine decay model, is obtained to predict the change of residual chlorine concentration under different conditions.

[0020] The residual chlorine attenuation model is used to predict the residual chlorine concentration of the scheduled water distribution plan at each key pipe network node and different time periods, and a series of residual chlorine concentration values ​​are obtained to form a predicted residual chlorine concentration set, which includes the predicted residual chlorine concentration prediction results at each time point and each chlorination point. By accurately predicting the residual chlorine concentration in each area, over-chlorination or under-chlorination is avoided to ensure the stability of water disinfection effect.

[0021] The secondary chlorination point site selection module 12 is used to select the secondary chlorination point for the long-distance water distribution network according to the predicted residual chlorine concentration set, and obtain a secondary chlorination point site selection plan.

[0022] Specifically, according to the predicted residual chlorine concentration set of the long-distance water distribution network, by analyzing the chlorine concentration distribution in the network, the appropriate location is selected to set the secondary chlorination point to ensure that the chlorine concentration in certain areas of the network can be effectively increased or maintained, and unnecessary chlorination is avoided, thereby reducing the generation of disinfection by-products. According to the predicted residual chlorine concentration set, the area where the chlorine concentration is already below the preset safety threshold is found, that is, the target area that needs secondary chlorination, and the first space for secondary chlorination point decision is established.

[0023] By selecting the site that meets the secondary chlorination coverage threshold and has the smallest number of chlorination points in the first space of the secondary chlorination point decision, it is ensured that the chlorine concentration in the target area can be raised to a safe level after chlorination, while the number of chlorination points is reduced as much as possible to reduce construction and operation costs. Select the appropriate location of the chlorination point to avoid excessive chlorination and reduce the generation of by-products. After screening, a secondary chlorination point site selection plan is output, including the location and related parameters of each chlorination point, to ensure the optimal balance between chlorination efficiency and cost, and to achieve the dual goals of water quality safety and disinfection by-product control. By accurately predicting and optimizing the site selection of chlorination points, the chlorination efficiency can be effectively improved, and water quality safety can be guaranteed. By optimizing the site selection, unnecessary chlorination point settings are reduced, excessive costs are avoided, and the generation of disinfection by-products is reduced, which meets water quality safety and environmental protection requirements.

[0024] The secondary chlorination decision module 13 is used to make a secondary chlorination decision based on the chlorination scene registration threshold, in combination with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, to establish a secondary chlorination decision space.

[0025] Specifically, the secondary chlorination records of the long-distance water distribution network are retrieved to screen out decision plans that meet the chlorination scenario alignment threshold. The chlorination scenario alignment threshold is used to determine whether the chlorination scenario meets the preset conditions. If the predicted scenario (such as residual chlorine concentration distribution, chlorination point site selection, etc.) is sufficiently similar to the historical record (that is, the similarity of its twin evaluation is greater than the threshold), it is considered to meet the preset conditions, and the secondary chlorination record in the historical record is used as a backup plan. The predicted residual chlorine concentration set is a residual chlorine concentration data set predicted according to the predetermined water distribution plan, which reflects the residual chlorine concentration of each location in the long-distance water distribution network at a specific time. The secondary chlorination point site selection plan is the location where secondary chlorination operations are required in the long-distance water distribution network.

[0026] By comparing the predicted residual chlorine concentration set with the residual chlorine concentration set of historical secondary chlorination records, and comparing the secondary chlorination point site selection plan with the chlorination point site selection plan of historical secondary chlorination records, the secondary chlorination plans corresponding to the historical secondary chlorination records with similarity greater than the chlorination scene registration threshold are used as the alternative plan set. The trigger domain of secondary chlorination, that is, the conditions for secondary chlorination, is determined according to the alternative plan set. Secondary chlorination decisions are made for the secondary chlorination point site selection plan according to the trigger domain, including determining the timing and amount of chlorination, and constructing a multidimensional decision space, in which each point represents a possible secondary chlorination plan. By combining the predicted residual chlorine concentration, the chlorination point site selection plan, and the chlorination scene registration, accurate decisions on the timing and location of secondary chlorination are achieved, effectively ensuring the disinfection effect of water quality while avoiding excessive chlorination.

[0027] The secondary chlorination optimization module 14 is used to perform multi-stage optimization on the secondary chlorination decision space according to the embedded secondary chlorination multi-stage optimization algorithm to determine the secondary chlorination optimization strategy.

[0028] Specifically, basic optimization factors are constructed, including the residual chlorine concentration compliance rate, residual chlorine distribution uniformity, and disinfection by-product risk, to ensure that the final residual chlorine concentration meets the drinking water standard, optimize the distribution of residual chlorine in the entire pipe network, reduce the phenomenon of local excessive or low concentrations, and minimize the generation of disinfection by-products (such as trihalomethanes and haloacetic acids). According to the basic optimization factors, the expected target range is set, including the expected range of residual chlorine concentration compliance rate, the expected range of residual chlorine distribution uniformity, and the expected range of disinfection by-product risk.

[0029] The secondary chlorination multi-order optimization algorithm is a multi-stage optimization algorithm for optimizing the secondary chlorination process. It includes three optimizations, namely the first-order optimization condition for secondary chlorination, the second-order optimization function for secondary chlorination, and the third-order optimization condition for secondary chlorination. The decision plan is gradually optimized to make the overall chlorination decision as consistent with the water quality requirements as possible. The secondary chlorination decision space refers to the set of all possible chlorination decisions. Each decision represents a possible chlorination strategy, including the specific amount of chlorination, the timing of chlorination, the chlorination point, etc. According to the preliminary chlorination requirements (such as the compliance rate of residual chlorine concentration, the uniformity of distribution, and the expected range of disinfection by-product risk), the first round of optimization is carried out to eliminate the chlorination schemes that do not meet the target range and screen out the chlorination decisions that meet the basic requirements.

[0030] In the first-order chlorination optimization space, the fitness value of each decision plan after the first round of screening is calculated based on the second-order optimization function. If its fitness value is higher than the predetermined fitness threshold, it will be included in the second-order chlorination optimization space, otherwise it will be eliminated. Under the premise of meeting the water quality requirements, the chlorination amount is optimized to reduce the chlorine addition cost and the amount of by-products generated, and the decision plan with the smallest total chlorination amount is found in the second round of screening. The chlorination strategy that meets all optimization conditions is output as the final secondary chlorination optimization strategy. Through the multi-order optimization algorithm, the residual chlorine concentration of the secondary chlorination strategy finally determined meets the standard and is reasonably distributed, the peak concentration of by-products such as trihalomethanes and haloacetic acids is reduced as much as possible, and the total amount of chlorination is minimized under the premise of meeting the water quality requirements, thereby achieving a more efficient, economical and environmentally friendly water treatment process.

[0031] The secondary chlorination module 15 is used for performing secondary chlorination on the long-distance water distribution network based on the predetermined water distribution plan and the secondary chlorination optimization strategy.

[0032] Specifically, the scheduled water distribution plan refers to a water distribution plan that is pre-formulated based on factors such as the characteristics of the pipe network, user needs, and water source conditions, including parameters such as water flow direction, flow rate, and pressure. The secondary chlorination optimization strategy is applied to perform secondary chlorination operations on long-distance water distribution pipe networks. According to the optimization strategy, the optimal chlorination point location and the optimal chlorination amount for each chlorination point are determined, that is, according to the structure of the long-distance water distribution pipe network (such as pipe network length, flow rate, etc.) and water quality requirements, the appropriate secondary chlorination time is selected. Chlorination is performed at the determined chlorination point according to the calculated chlorination amount, and the chlorination amount is adjusted according to the current water quality conditions (such as water temperature, flow rate, pipe network type, etc.) through the secondary chlorination optimization strategy. Select the appropriate chlorination point in the long-distance water distribution pipe network, and apply the optimization strategy to determine the chlorination amount and chlorination time.

[0033] During the chlorination process, the residual chlorine concentration in the pipe network is monitored in real time, the chlorination effect is evaluated, and the amount of chlorination is adjusted according to the actual situation to ensure water quality safety. For example, assuming that the predetermined water distribution plan requires a water supply flow rate of 1,000 cubic meters per hour in a certain period of time, according to the secondary chlorination optimization strategy, chlorination is determined at three key points in the pipe network, and the amount of chlorination at each point is 20 kg, 15 kg and 10 kg respectively. Through the chlorination operation based on the secondary chlorination optimization strategy, the residual chlorine concentration in the long-distance water distribution network can be controlled more accurately, which can not only ensure the water quality of end users, but also reduce the generation of disinfection by-products (such as chloroform, chlorophenol, etc.), and reduce the risk of environmental pollution.

[0034] Furthermore, the secondary chlorination point site selection module 12 in the long-distance water distribution network secondary chlorination system based on controlling disinfection by-products is also used for:

[0035] A secondary chlorination point decision is made for the long-distance water distribution network according to the predicted residual chlorine concentration set, and a first space for secondary chlorination point decision is established; an optimization analysis is performed on the first space for secondary chlorination point decision according to the secondary chlorination coverage rate threshold, and a second space for secondary chlorination point decision is established; and optimization is performed to minimize the number of secondary chlorination points according to the second space for secondary chlorination point decision, and the secondary chlorination point site selection plan is determined.

[0036] Specifically, the predicted residual chlorine concentration set provides information on residual chlorine concentration at different times, different pipe sections or different locations. Based on the predicted residual chlorine concentration set, the residual chlorine concentration of each node or area in the long-distance water distribution network is evaluated. The various areas in the network are classified, and those areas with residual chlorine concentrations below a certain threshold are selected as potential locations for secondary chlorination. These may be the end of the water supply network, longer parts of the pipes, or areas with slower water flow, where the chlorine concentration usually decays faster. Based on the predicted residual chlorine concentration, areas with residual chlorine concentrations below the set threshold are selected as chlorination points. At this time, multiple chlorination points in the network may be selected to ensure that the residual chlorine concentration of the long-distance water distribution network meets the requirements.

[0037] The secondary chlorination point decision is based on the predicted residual chlorine concentration to determine where to add chlorine and how to distribute these chlorination points to ensure that the residual chlorine concentration of the entire pipe network is maintained at an appropriate level. The first space of the secondary chlorination point decision refers to the chlorination point distribution plan preliminarily determined based on the predicted residual chlorine concentration set. By analyzing the residual chlorine concentration at different locations in the pipe network, the nodes or areas that initially need chlorination are selected to form a candidate space for chlorination points.

[0038] The secondary chlorination coverage rate threshold is a standard used to evaluate the effect of the secondary chlorination point setting. It is usually based on the proportion of water volume or pipe network area that the chlorination point can cover. A threshold is set to indicate whether the coverage of the secondary chlorination point meets the requirements. By setting the threshold, it can be determined whether the distribution of chlorination points meets the coverage requirements to ensure that all areas that require chlorination can be fully disinfected. If the initially set chlorination point coverage rate is lower than the secondary chlorination coverage rate threshold, it is necessary to adjust the location of the chlorination point or increase the number of chlorination points.

[0039] According to the secondary chlorination coverage threshold, the first space of the secondary chlorination point decision is optimized and analyzed, and the position of the chlorination point is adjusted by an optimization algorithm (such as genetic algorithm, particle swarm optimization, etc.), so that the chlorination point can meet the coverage threshold while reducing the number of chlorination points as much as possible to improve the overall coverage. The particle swarm optimization algorithm is an optimization algorithm that simulates group behavior. It optimizes the objective function by simulating the process of bird flocks looking for food. Each particle represents a chlorination point scheme (including position and number), and its advantages and disadvantages are evaluated according to a certain fitness function. Each particle represents a chlorination point distribution scheme. Initially, the position and velocity of the particle are randomly generated. The position represents the distribution scheme of the chlorination point (the position vector of each particle is composed of the coordinates of the chlorination point), and the velocity represents the adjustment direction of the chlorination point.

[0040] According to the importance of coverage score (the proportion of the pipe network area covered by the chlorination point to the entire area requiring chlorination), chlorination point number score (the fewer chlorination points, the higher the score), and byproduct control score (if secondary chlorination can effectively reduce the generation of byproducts, the fitness will increase), different weights are assigned to calculate the fitness of each particle point. Each particle adjusts its position and speed according to the current fitness and the historical optimal solution (the optimal solution of each particle itself and the optimal solution of all particles) and moves in the direction of the optimal solution. When the change in the fitness function is less than the preset threshold, or the maximum number of iterations is reached, it terminates and returns the optimal chlorination point distribution plan. After a series of iterative optimizations, the particle swarm algorithm further determines a more suitable chlorination point layout, that is, the second space for secondary chlorination point decision.

[0041] According to the second space of secondary chlorination point decision, the number of secondary chlorination points is minimized and optimized. Increasing chlorination points will increase costs and maintenance burdens, so a balance needs to be found to ensure that water quality meets standards while minimizing the number of chlorination points. By screening out the site selection points with the widest coverage, the least number of chlorination points, and the highest by-product control score, the chlorination amount and distribution of chlorination points are adjusted, unnecessary chlorination points are reduced, and the required coverage and water quality standards are maintained. For example, in some areas, the chlorination amount of some chlorination points can be increased to reduce the demand for chlorination points in other areas, thereby reducing the total number of chlorination points.

[0042] After optimization, the final site selection plan for secondary chlorination points is obtained, the location and number of chlorination points are finally determined, and a corresponding operation plan is formulated, that is, which areas need chlorination and the location and operation frequency of each chlorination point. Through scientific site selection of chlorination points, the chlorination effect is maximized, redundant chlorination point settings are avoided, costs are reduced, and the generation of excessive by-products is avoided, ensuring water quality safety.

[0043] Furthermore, the secondary chlorination decision module 13 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0044] The secondary chlorination records are retrieved according to the long-distance water distribution network to obtain a secondary chlorination record set; based on the chlorination scene registration threshold, the secondary chlorination record set is registered and associated according to the predicted residual chlorine concentration set and the secondary chlorination point site selection plan to obtain a registered chlorination plan set; trigger intervals are identified according to the registered chlorination plan set to establish a secondary chlorination trigger domain; secondary chlorination parameter decisions are made on the secondary chlorination point site selection plan according to the secondary chlorination trigger domain to generate the secondary chlorination decision space.

[0045] Specifically, the secondary chlorination record set of the long-distance water distribution network is the record data of the secondary chlorination operation of the long-distance water distribution network in the past or in history, including the time of each chlorination operation, chlorination point, amount of chlorine added, water quality after chlorination, residual chlorine concentration after chlorination, etc. The chlorination scenario registration threshold refers to the standard or threshold required to determine the accuracy and consistency of the registration data under different chlorination scenarios, and align different data sets (such as the secondary chlorination record set and the predicted residual chlorine concentration set) in time and space.

[0046] Each record in the secondary chlorination record set includes a residual chlorine concentration set, a secondary chlorination point site selection plan, and a secondary chlorination plan. Through the chlorination scenario registration threshold, the secondary chlorination record set is compared and registered according to the predicted residual chlorine concentration set and the secondary chlorination point site selection plan to ensure the temporal and spatial alignment of the data. In other words, the residual chlorine concentration set and the predicted residual chlorine concentration set corresponding to each record in the secondary chlorination record set are compared and registered, and the chlorination point site selection plan and the secondary chlorination point site selection plan corresponding to each record in the secondary chlorination record set are compared and registered, and the records that both meet the chlorination scenario registration threshold are screened out, and their corresponding secondary chlorination plans are added to the registered chlorination plan set. The registered chlorination plan set includes all chlorination plans that meet the chlorination scenario registration threshold.

[0047] Ensure that the predicted residual chlorine concentration set and the sample residual chlorine concentration set in the secondary chlorination record set are aligned in time and space, and ensure that the two represent data at the same time and location, pointing to the water body in the same area. If the time points or sampling points of the two are different, they need to be synchronized or interpolated to ensure the correspondence between the two on the time axis. If the predicted data is collected based on different locations of the pipeline network, it needs to be matched with the location of the chlorination point in the historical record. Similarly, ensure that the secondary chlorination point site selection plan and the sample secondary chlorination point site selection plan in the secondary chlorination record set are aligned in time and space, and ensure that the two represent data at the same time and location, pointing to the water body in the same area.

[0048] According to the registered chlorination scheme set, the trigger intervals that require secondary chlorination are identified, that is, when and how each area triggers secondary chlorination. According to the trigger interval, a secondary chlorination trigger domain is established to clarify which chlorination points need to perform chlorination operations and when. For example, if the residual chlorine concentration is found to be low and close to the set threshold (such as 0.1 mg / L) at the end of the pipe network, then these points and their corresponding times will be used as the secondary chlorination trigger domain. After identifying the secondary chlorination trigger domain, based on the secondary chlorination point site selection plan, the chlorination points are accurately selected, and chlorination parameter decisions are made, including the secondary chlorination chlorine dosage, the residual chlorine concentration during secondary chlorination, the secondary chlorination time, etc., to generate a decision space containing different parameter combinations.

[0049] The secondary chlorination decision space is a multi-dimensional decision space generated after analyzing all relevant data, covering different decision parameters such as chlorination amount, chlorination timing, and chlorination point location, forming a comprehensive optimization view. For example, when the initial chlorination concentration decays to 0.23 mg / L (combination 1), 0.18 mg / L (combination 2), 0.13 mg / L (combination 3), and 0.09 mg / L (combination 4), the total chlorine amount is set to 2.82 mg / L (combination 5) for a control test. Before the secondary chlorination, the initial chlorination concentrations of combination 1, combination 2, combination 3, and combination 4 (2.35 mg / L) are all lower than that of combination 5 (2.82 mg / L). After the second chlorination, the residual chlorine concentration rises briefly and then drops rapidly. Combinations 1, 2, and 3 are lower than the first chlorination (combination 5) after the second chlorination. Combination 4 has a slightly higher chlorination concentration than the first chlorination because the second chlorination time point is later. Therefore, the total residence time of the pipe network should be comprehensively considered in the selection of the second chlorination time point. When the chlorine concentration is lower than 0.09 mg / L, the second chlorination is performed. At this time, the second chlorination can ensure that the water quality is effectively guaranteed and avoid excessive generation of by-products. Through accurate chlorination decisions, the residual chlorine concentration in the pipe network is always maintained within the appropriate range, ensuring water quality safety, optimizing the amount and timing of chlorination, avoiding excessive chlorination, reducing the generation of by-products, and meeting environmental protection requirements.

[0050] Furthermore, the secondary chlorination decision module 13 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0051] Traverse the secondary chlorination record set and extract the first secondary chlorination record, wherein the first secondary chlorination record includes the first sample residual chlorine concentration set, the first sample secondary chlorination point site selection plan and the first sample secondary chlorination plan; according to the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, perform twin evaluation on the first sample residual chlorine concentration set and the first sample secondary chlorination point site selection plan to determine the first chlorination scene alignment coefficient; determine whether the first chlorination scene alignment coefficient is greater than or equal to the chlorination scene alignment threshold; if the first chlorination scene alignment coefficient is greater than or equal to the chlorination scene alignment threshold, add the first sample secondary chlorination plan to the aligned chlorination plan set.

[0052] Specifically, the extracted secondary chlorination record set is traversed, and one record is randomly selected as the first secondary chlorination record, including the first sample residual chlorine concentration set, the first sample secondary chlorination point site selection plan and the first sample secondary chlorination plan, that is, the residual chlorine concentration value, site selection point and operation plan corresponding to the first secondary chlorination record, which reflects the detailed process and results of the chlorination operation in the first record.

[0053] According to the predicted residual chlorine concentration set, the first sample residual chlorine concentration set is twin-evaluated, the residual chlorine concentration set in the first record is compared with the predicted residual chlorine concentration set, and the similarity between the two is calculated. According to the chlorination scene registration threshold, the predicted residual chlorine concentration set and the sample residual chlorine concentration set in the secondary chlorination record set are aligned in time and space. The similarity of the predicted residual chlorine concentration set and the first sample residual chlorine concentration set at each moment and position is calculated respectively, and then the total similarity is obtained. The residual chlorine concentration values ​​at each time point and location are compared, and the similarity is calculated by cosine similarity, Pearson correlation coefficient, etc. For example, the Pearson correlation coefficient of each two sets of residual chlorine concentration data is calculated. The closer the value is to 1, the higher the similarity.

[0054] Similarly, according to the secondary chlorination point site selection plan, a twin evaluation is performed on the first sample secondary chlorination point site selection plan, and the site selection points in the first record are compared with the site selection points in the secondary chlorination point site selection plan to calculate the similarity between the two. Use the Euclidean distance or shortest path algorithm to calculate the spatial similarity between the chlorination points. The smaller the distance, the higher the similarity. Based on the calculated similarity, determine whether the chlorination scene meets the registration criteria. The total similarity is obtained through the similarity at each time and location. If the similarity of the first sample residual chlorine concentration set and the similarity of the first sample secondary chlorination point site selection plan are both greater than or equal to the set chlorination scene registration threshold, the first sample secondary chlorination plan is considered to meet the requirements and is added to the registered chlorination plan set.

[0055] The above operation is performed for each record in the secondary chlorination record set, and the sample secondary chlorination schemes corresponding to all records that meet the requirements are added to the registered chlorination scheme set. Through twin evaluation, the high consistency of the selected chlorination scheme and the actual scenario is ensured, making the effect of the chlorination operation more predictable and accurate. The qualified chlorination schemes are integrated into the registered chlorination scheme set to achieve a more accurate and flexible secondary chlorination strategy, ensuring water quality safety while reducing the risk of by-product generation.

[0056] Further, as attached Figure 2 As shown, the secondary chlorination optimization module 14 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0057] A basic optimization factor for secondary chlorination is set, wherein the basic optimization factor for secondary chlorination includes the residual chlorine concentration compliance rate, the residual chlorine distribution uniformity and the risk of disinfection by-products; a first-order optimization condition for secondary chlorination is constructed according to the basic optimization factor for secondary chlorination, wherein the first-order optimization condition for secondary chlorination includes the expected interval of the residual chlorine concentration compliance rate, the expected interval of the residual chlorine distribution uniformity and the expected interval of the risk of disinfection by-products; a first-order optimization is performed on the secondary chlorination decision space according to the first-order optimization condition for secondary chlorination to establish a first-order chlorination optimization space; a second-order optimization function for secondary chlorination is constructed according to the basic optimization factor for secondary chlorination, and a second-order optimization is performed on the first-order chlorination optimization space according to the second-order chlorination optimization function to generate a second-order chlorination optimization space; a third-order optimization condition for secondary chlorination is set, wherein the third-order optimization condition for secondary chlorination is the minimum chlorine addition amount; a third-order optimization is performed on the second-order chlorination optimization space according to the third-order optimization condition for secondary chlorination to generate the secondary chlorination optimization strategy.

[0058] Specifically, according to the actual situation of the long-distance water distribution network and user needs, the basic optimization factors for secondary chlorination are set to guide the optimization of the secondary chlorination scheme, including the residual chlorine concentration compliance rate, the uniformity of residual chlorine distribution and the risk of disinfection by-products. The residual chlorine concentration compliance rate refers to the proportion of residual chlorine concentrations at all nodes and time periods in the network that meet the preset standards. A high compliance rate indicates that the chlorination effect is good and water disinfection is fully achieved. The uniformity of residual chlorine distribution refers to the degree of difference in residual chlorine concentrations at different nodes and time periods in the network, which is used to describe whether the residual chlorine concentrations at different locations in the water body are balanced. If the distribution is uniform, it means that the selection of chlorination points and the distribution of chlorination are reasonable, which helps to ensure the overall water quality of the network. The risk of disinfection by-products refers to the types and concentration levels of disinfection by-products generated during the secondary chlorination process, and evaluates the risk level of by-products (such as THMs, HAAs, etc.) generated during the chlorination process. A lower by-product risk means that the chlorination process is safer and more environmentally friendly.

[0059] According to the basic optimization factors of secondary chlorination, the first-order optimization conditions of secondary chlorination are constructed, that is, the expected intervals are set, including the expected intervals of residual chlorine concentration compliance rate (such as 95%-100%), the expected intervals of residual chlorine distribution uniformity (such as above 0.8) and the expected intervals of disinfection by-product risk (such as below 10%). The first-order optimization conditions of secondary chlorination are used to perform first-order optimization in the secondary chlorination decision space, and all the solutions that meet the first-order optimization conditions of secondary chlorination in the secondary chlorination decision space are screened out. In other words, only the decision-making solutions whose residual chlorine concentration compliance rate, residual chlorine distribution uniformity, and disinfection by-product risk in the secondary chlorination decision space meet the expected intervals can be selected and integrated into the first-order optimization space of chlorination. The first-order optimization space of chlorination includes all the solutions that meet the first-order optimization conditions of secondary chlorination in the secondary chlorination decision space, which are the solutions after further screening.

[0060] According to the basic optimization factors of secondary chlorination, namely, the residual chlorine concentration compliance rate, the residual chlorine distribution uniformity and the risk of disinfection by-products, a secondary chlorination second-order optimization function is constructed, and the first-order chlorination optimization space is optimized again. The prediction coefficient of the residual chlorine concentration compliance rate, the prediction coefficient of the residual chlorine distribution uniformity and the disinfection by-product risk prediction coefficient are normalized so that their values ​​are between 0 and 1. According to the actual situation and needs, the weight values ​​of the residual chlorine concentration compliance rate, the residual chlorine distribution uniformity and the disinfection by-product risk are determined, and the value that is more concerned is given a higher weight. Through the secondary chlorination second-order optimization function, the secondary chlorination fitness of each decision-making scheme in the first-order chlorination optimization space is calculated respectively. According to the calculated secondary chlorination fitness, the chlorination schemes in the first-order chlorination optimization space are sorted, and the chlorination scheme with better comprehensive performance is selected. A fitness threshold is set, and all schemes with secondary chlorination fitness greater than or equal to the fitness threshold in the first-order chlorination optimization space are added to the second-order chlorination optimization space, and the schemes less than the fitness threshold are eliminated.

[0061] Set the third-order optimization conditions for secondary chlorination, that is, further optimize on the basis of the second-order optimization to find the solution with the minimum chlorination amount. Reducing the amount of chlorination can reduce operating costs and the risk of by-product generation during water treatment. Traverse all decisions in the second-order optimization space for chlorination, calculate the total amount of chlorination, screen out the final decision that meets the minimum chlorination condition from the second-order optimization space, and generate the final secondary chlorination optimization strategy. Through phased optimization, the decision space is gradually narrowed to ensure that the final strategy meets multiple optimization goals. The weights in the second-order optimization function can be flexibly set according to actual needs to adapt to the optimization needs in different scenarios. The third-order optimization process focuses on minimizing the amount of chlorination, reducing operating costs and the risk of disinfection by-products, and achieving economic and environmental benefits.

[0062] For example, before the secondary chlorination, the initial chlorination concentration (2.35 mg / L) of combination 1, combination 2, combination 3 and combination 4 was lower than that of combination 5 (2.82 mg / L), and the generated trichloromethane (TCM), monobromodichloromethane (BDCM) and dibromochloromethane (DBCM) were all lower than that of combination 5. After the secondary chlorination, the trihalomethanes (THMs) generated by all combinations were higher than those of combination 5, which shows that the secondary chlorination can increase the generation of trihalomethanes. Comparing the secondary chlorination effects with different chlorination times, the highest values ​​of trichloromethane produced by combinations 1, 2, 3, 4, and 5 were 34.2 mg / L, 35.3 mg / L, 35.2 mg / L, 24.4 mg / L, and 36.4 mg / L, respectively, and the highest values ​​of monobromodichloromethane were 13 mg / L, 13.2 mg / L, 13 mg / L, 9.53 mg / L, and 13.7 mg / L, respectively. The highest values ​​of TCM and BDCM produced by single chlorination were higher than the peak value of the secondary chlorination combination. The highest values ​​of dibromochloromethane produced by combinations 1, 2, 3, 4, and 5 were 2.45 mg / L, 2.63 mg / L, 2.61 mg / L, 1.76 mg / L, and 1.85 mg / L, respectively. It can be seen that the maximum value of dibromochloromethane produced by combination 1, combination 2, and combination 3 is higher than that of combination 5, while the maximum value of dibromochloromethane produced by combination 4 is lower than that of combination 5. When the total dosage is equal, secondary chlorination when the residual chlorine concentration is low (0.09 mg / L) can reduce the peak value of dibromochloromethane.

[0063] Before secondary chlorination, due to different initial chlorine concentrations, the dichloroacetic acid (DCAA) produced by combination 1, combination 2, combination 3 and combination 4 was lower than that produced by combination 5. After secondary chlorination, the DCAA concentration was higher than that produced by combination 5. The highest values ​​of DCAA produced by combination 1, combination 2, combination 3, combination 4 and combination 5 were 15.113 mg / L, 16.378 mg / L, 18.203 mg / L, 15.5 mg / L and 15.941 mg / L, respectively. The highest value of secondary DCAA of combination 4 was lower than that of single chlorination combination 5. Under the condition of equal total dosage, secondary chlorination can be carried out when the residual chlorine concentration is low (0.09 mg / L) to reduce the maximum generation of DCAA.

[0064] In contrast, the generation patterns of trichloroacetic acid (TCAA) and DCAA are different. Before and after secondary chlorination, the maximum TCAA values ​​produced by combination 1, combination 2, combination 3, and combination 4 are 8.115 mg / L, 8.521 mg / L, 8.392 mg / L, and 7.622 mg / L, respectively, which are all lower than combination 5 (11.897 mg / L), fully demonstrating that secondary chlorination has advantages in controlling TCAA generation.

[0065] In summary, secondary chlorination when the residual chlorine decays to 0.09 mg / L can make the residual chlorine concentration meet the standard and distribute more evenly, while effectively reducing the generation of disinfection by-products (DBPs). Therefore, when the total chlorine dosage is equivalent, it is recommended to appropriately reduce the amount of secondary chlorination while meeting the water quality requirements. Secondary chlorination when the residual chlorine decays to a low value can reduce the generation of DBPs during the chlorine decay process and optimize water quality safety.

[0066] Furthermore, the secondary chlorination optimization module 14 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0067] According to the secondary chlorination decision space, extract the first secondary chlorination decision; based on the predetermined water distribution plan, perform secondary chlorination prediction on the long-distance water distribution network according to the first secondary chlorination decision, and obtain the first decision chlorination prediction result; determine whether the first decision chlorination prediction result meets the first-order optimization condition for secondary chlorination; if the first decision chlorination prediction result meets the first-order optimization condition for secondary chlorination, add the first secondary chlorination decision to the first-order chlorination optimization space; continue to perform first-order optimization on the secondary chlorination decision space according to the first-order optimization condition for secondary chlorination, and generate the first-order chlorination optimization space.

[0068] Specifically, a decision is randomly selected from the secondary chlorination decision space as the first decision for secondary chlorination, including the amount of chlorination, residual chlorine concentration during chlorination, chlorination site selection, etc. The first decision for secondary chlorination is simulated according to the predetermined water distribution plan, and the secondary chlorination prediction is carried out for the long-distance water distribution network, that is, the effect of the first decision for secondary chlorination is predicted, and the prediction results of the first decision for chlorination are obtained, including the prediction coefficient of the residual chlorine concentration compliance rate, the prediction coefficient of the residual chlorine distribution uniformity, and the prediction coefficient of the risk of disinfection by-products.

[0069] Obtain historical water quality monitoring data for the past year or several months, including water distribution plans (such as water flow rate, pressure, temperature, etc.), chlorination decisions (such as chlorination points, chlorination amount, chlorination time, etc.), and historical monitoring data (such as historical residual chlorine concentration, disinfection by-products, etc.). Select appropriate models based on factors such as the complexity of the pipe network, data accessibility, and prediction accuracy requirements, including physical models (such as water flow dynamics models) and data-driven models (such as regression models, neural network models, support vector machines, etc.). Perform data preprocessing on historical water quality monitoring data, including data cleaning, outlier processing, missing value supplementation, data standardization, etc., so that the data meets the model input requirements. Extract effective features from historical water quality monitoring data, including water flow characteristics (such as water flow rate, pressure, temperature, etc.), water quality characteristics (such as water quality data, raw water chlorine concentration, existing chlorine residual in the pipe network, etc.), and chlorination parameter characteristics (such as chlorination amount, location of chlorination point, chlorination time, etc.).

[0070] The data set is divided into a training set and a validation set, usually 80% training set and 20% validation set. If a machine learning model is used, the training set is used to train the model. The input data is factors such as chlorination amount, chlorination time, water flow rate, etc. The output is the predicted value of water quality after chlorination (residual chlorine concentration, disinfection by-products, etc.). During the training process, a cross-validation method is used to optimize the hyperparameters of the model to avoid overfitting. The validation set is used to evaluate the model, such as the mean absolute error, to measure the absolute value of the prediction error and verify the prediction accuracy of the model. Once the model training is completed and verified, it is used as a secondary chlorination prediction model to make predictions based on specific secondary chlorination decisions.

[0071] Determine whether the obtained first decision chlorination prediction result meets the first-order optimization condition of secondary chlorination, that is, determine whether the residual chlorine concentration compliance rate prediction coefficient, the residual chlorine distribution uniformity prediction coefficient, and the disinfection by-product risk prediction coefficient are in the expected interval of residual chlorine concentration compliance rate, the expected interval of residual chlorine distribution uniformity, and the expected interval of disinfection by-product risk. When the first decision chlorination prediction result meets the first-order optimization condition of secondary chlorination, that is, the residual chlorine concentration compliance rate prediction coefficient, the residual chlorine distribution uniformity prediction coefficient, and the disinfection by-product risk prediction coefficient all meet the corresponding expected intervals, it means that this decision is valid, and the first decision of secondary chlorination is added to the first-order optimization space of chlorination. In this way, all effective chlorination decision plans will enter the first-order optimization space, waiting for further optimization and screening.

[0072] After adding the first decision to the first-order optimization space, continue the first-order optimization. By performing the above prediction and judgment on all the options in the secondary chlorination decision space, all the options that meet the first-order optimization conditions of secondary chlorination are selected to form the first-order optimization space of chlorination. The first-order optimization space of chlorination is a set of qualified chlorination options screened from all possible chlorination decisions based on the first-order optimization conditions of secondary chlorination. By predicting and verifying the first decision of secondary chlorination, it is ensured that the residual chlorine concentration in the water body after chlorination meets the standard and is evenly distributed, and the generation of by-products is controlled within a safe range, reducing resource waste while ensuring the disinfection effect.

[0073] Furthermore, the secondary chlorination optimization module 14 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0074] The secondary chlorination second-order optimization function is: ; Among them, ACF represents the secondary chlorination fitness, WBC, WUX, and WRY represent the weight conditions for chlorination fitness calculation, the value range of WBC, WUX, and WRY is 0 to 1, and the sum of WBC, WUX, and WRY is 1. g(CBC) represents the normalized residual chlorine concentration compliance rate prediction coefficient, g(CUX) represents the normalized residual chlorine distribution uniformity prediction coefficient, and g(CRY) represents the normalized disinfection by-product risk prediction coefficient.

[0075] Specifically, the goal of secondary chlorination decision-making is to achieve the optimal residual chlorine concentration, the most uniform distribution, and minimize the risk of disinfection by-products through optimization methods. A second-order optimization function is constructed based on the basic optimization factors of secondary chlorination (residual chlorine concentration compliance rate, residual chlorine distribution uniformity, and disinfection by-product risk) to further optimize the chlorination decision space. The second-order optimization function of secondary chlorination is: ; Among them, ACF represents the adaptability of secondary chlorination, which is used to measure the comprehensive adaptability of a chlorination decision-making plan. WBC, WUX, and WRY represent the weights of three basic factors (residual chlorine concentration compliance rate, residual chlorine distribution uniformity, and disinfection by-product risk). The residual chlorine concentration compliance rate (WBC) indicates the proportion of water quality that meets the residual chlorine concentration standard in the pipe network; the residual chlorine distribution uniformity (WUX) indicates the distribution uniformity of the residual chlorine concentration at each point in the pipe network. An ideal chlorination plan should be able to make the residual chlorine concentration at each location close to uniform, so as to effectively disinfect; the disinfection by-product risk (WRY) indicates the harmful substances that may be generated during chlorine disinfection when there is organic matter in the water.

[0076] The value range of WBC, WUX, and WRY is 0 to 1. The sum of WBC, WUX, and WRY is 1. g(CBC) represents the normalized residual chlorine concentration compliance rate prediction coefficient, which measures whether the residual chlorine concentration meets the specified standard. g(CUX) represents the normalized residual chlorine distribution uniformity prediction coefficient, which measures the uniformity of residual chlorine at different pipeline nodes after chlorination. g(CRY) represents the normalized disinfection by-product risk prediction coefficient, which measures the risk of by-products produced after chlorination.

[0077] The prediction coefficient of residual chlorine concentration compliance rate, the prediction coefficient of residual chlorine distribution uniformity, and the prediction coefficient of disinfection by-product risk are obtained through the above prediction and normalization. By adjusting the values ​​of WBC, WUX, and WRY (i.e., adjusting the weights), the model can be flexibly controlled to give priority to the optimization of a certain aspect, such as optimizing the risk of disinfection by-products, or improving the uniformity of residual chlorine concentration. The second-order optimization function can comprehensively consider multiple factors and find the optimal solution under multiple objectives. By adjusting the weights, the chlorination scheme can be optimized according to different needs and preferences.

[0078] Furthermore, the secondary chlorination optimization module 14 in the secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products is also used for:

[0079] According to the first-order chlorination optimization space, extract the nth decision of secondary chlorination, wherein n is a positive integer; input the nth decision chlorination prediction result corresponding to the nth decision of secondary chlorination into the second-order chlorination optimization function to obtain the nth decision secondary chlorination fitness; determine whether the nth decision secondary chlorination fitness is greater than or equal to the predetermined secondary chlorination fitness; if the nth decision secondary chlorination fitness is greater than or equal to the predetermined secondary chlorination fitness, add the nth decision of secondary chlorination to the second-order chlorination optimization space; if the nth decision secondary chlorination fitness is less than the predetermined secondary chlorination fitness, eliminate the nth decision of secondary chlorination; based on the predetermined secondary chlorination fitness, continue to perform second-order optimization on the first-order chlorination optimization space according to the second-order chlorination optimization function to obtain the second-order chlorination optimization space.

[0080] Specifically, the nth decision of secondary chlorination is arbitrarily extracted from the first-order optimization space of chlorination, that is, any one of the decisions is extracted. First, the residual chlorine concentration compliance rate prediction coefficient, residual chlorine distribution uniformity prediction coefficient, and disinfection by-product risk prediction coefficient in the nth decision chlorination prediction result are normalized to convert them into a value between 0 and 1. The nth decision chlorination prediction result corresponding to the nth decision of secondary chlorination is input into the second-order optimization function of secondary chlorination, and the fitness of the nth decision of secondary chlorination is calculated according to the weights of the residual chlorine concentration compliance rate, the residual chlorine distribution uniformity, and the risk of disinfection by-products, that is, the fitness of the nth decision of secondary chlorination.

[0081] The secondary chlorination fitness is predefined to screen out sufficiently excellent decision-making plans. Plans that are lower than the predetermined secondary chlorination fitness will be eliminated. If the secondary chlorination fitness of the nth decision is greater than or equal to the predetermined secondary chlorination fitness, it means that the secondary chlorination decision nth meets the optimization goal, and the secondary chlorination decision nth is added to the chlorination second-order optimization space. On the contrary, if the secondary chlorination fitness of the nth decision is less than the predetermined secondary chlorination fitness, it means that the requirements are not met, and the secondary chlorination decision nth is eliminated to avoid entering the final optimization space.

[0082] The above steps are performed on all decisions in the first-order chlorination optimization space, and all decisions that meet the predetermined secondary chlorination fitness are screened out to form the second-order chlorination optimization space. By gradually evaluating different chlorination decisions and their fitness, the chlorination scheme that best meets the water quality optimization goal can be effectively screened out. Ultimately, the second-order optimization function finds a balance between multiple objectives, ensuring that the residual chlorine concentration meets the standard and is evenly distributed, while controlling the risk of disinfection by-products. A second-order optimization is performed based on the preliminary chlorination scheme in the first-order optimization space to screen out the most suitable chlorination decision. Through the comprehensive evaluation of the fitness function, the second-order optimization can balance different optimization objectives, comprehensively consider the residual chlorine concentration, distribution uniformity and by-product risk, and avoid the negative impact that may be caused by the optimization of a single indicator.

[0083] In summary, the long-distance water distribution network secondary chlorination system based on controlling disinfection by-products provided by this application has the following technical effects:

[0084] Through the residual chlorine concentration prediction module, the residual chlorine concentration prediction module is used to predict the residual chlorine concentration of the predetermined water distribution plan of the long-distance water distribution network to obtain a predicted residual chlorine concentration set; the secondary chlorination point site selection module, the secondary chlorination point site selection module is used to select the secondary chlorination point for the long-distance water distribution network according to the predicted residual chlorine concentration set, and obtain a secondary chlorination point site selection plan; the secondary chlorination decision module, the secondary chlorination decision module is used to make a secondary chlorination decision based on the chlorination scene alignment threshold, combined with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, and establish a secondary chlorination decision space; the secondary chlorination optimization module, the secondary chlorination optimization module is used to perform multi-order optimization on the secondary chlorination decision space according to the embedded secondary chlorination multi-order optimization algorithm, and determine the secondary chlorination optimization strategy; the secondary chlorination module, the secondary chlorination module is used to perform secondary chlorination on the long-distance water distribution network based on the predetermined water distribution plan and the secondary chlorination optimization strategy. In other words, by predicting the residual chlorine concentration at different pipeline locations and at different time points, the chlorination points are accurately selected, and the chlorination amount is dynamically adjusted through a multi-order optimization algorithm to ensure that the chlorination amount in each area is at the optimal level, which can not only ensure the disinfection effect, but also reduce the generation of disinfection by-products and improve water quality safety.

[0085] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0086] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A secondary chlorination system for long-distance water distribution networks based on controlling disinfection by-products, characterized in that: include: A residual chlorine concentration prediction module, which is used to predict the residual chlorine concentration of a predetermined water distribution plan of a long-distance water distribution network to obtain a predicted residual chlorine concentration set; A secondary chlorination point site selection module, which is used to select secondary chlorination points for the long-distance water distribution network according to the predicted residual chlorine concentration set, and obtain a secondary chlorination point site selection plan; A secondary chlorination decision module, which is used to make a secondary chlorination decision based on the chlorination scenario registration threshold, in combination with the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, to establish a secondary chlorination decision space; A secondary chlorination optimization module, which is used to perform multi-order optimization on the secondary chlorination decision space according to an embedded secondary chlorination multi-order optimization algorithm to determine a secondary chlorination optimization strategy; A secondary chlorination module, the secondary chlorination module is used to perform secondary chlorination on the long-distance water distribution network based on the predetermined water distribution plan and according to the secondary chlorination optimization strategy; Wherein, the secondary chlorination optimization module is also used for: Setting a basic optimization factor for secondary chlorination, wherein the basic optimization factor for secondary chlorination includes the residual chlorine concentration compliance rate, the residual chlorine distribution uniformity and the risk of disinfection by-products; According to the secondary chlorination basic optimization factor, the first-order optimization condition of secondary chlorination is constructed, wherein the first-order optimization condition of secondary chlorination includes the expected range of residual chlorine concentration compliance rate, the expected range of residual chlorine distribution uniformity and the expected range of disinfection by-product risk; Performing first-order optimization on the secondary chlorination decision space according to the first-order optimization condition of the secondary chlorination to establish a first-order optimization space for chlorination; According to the secondary chlorination basic optimization factor, a secondary chlorination second-order optimization function is constructed, and according to the secondary chlorination second-order optimization function, a second-order optimization is performed on the first-order chlorination optimization space to generate a chlorination second-order optimization space; Setting a third-order optimization condition for secondary chlorination, wherein the third-order optimization condition for secondary chlorination is to minimize the amount of chlorination; Performing a third-order optimization on the second-order chlorination optimization space according to the third-order optimization condition of the second-order chlorination to generate the second-order chlorination optimization strategy; The secondary chlorination second-order optimization function is: ； Among them, ACF represents the secondary chlorination fitness, WBC, WUX, and WRY represent the weight conditions for chlorination fitness calculation, the value range of WBC, WUX, and WRY is 0 to 1, and the sum of WBC, WUX, and WRY is 1, g(CBC) represents the normalized residual chlorine concentration compliance rate prediction coefficient, g(CUX) represents the normalized residual chlorine distribution uniformity prediction coefficient, and g(CRY) represents the normalized disinfection by-product risk prediction coefficient; Wherein, the secondary chlorination point site selection module is also used for: Making a secondary chlorination point decision for the long-distance water distribution network according to the predicted residual chlorine concentration set, and establishing a first space for secondary chlorination point decision; Performing optimization analysis on the first space of secondary chlorination point decision according to the secondary chlorination coverage rate threshold, and establishing a second space of secondary chlorination point decision; According to the second space of the secondary chlorination point decision, the number of secondary chlorination points is minimized and optimized to determine the secondary chlorination point site selection plan; Wherein, the secondary chlorination decision module is also used for: Retrieving secondary chlorination records according to the long-distance water distribution network to obtain a secondary chlorination record set; Based on the chlorination scenario registration threshold, the secondary chlorination record set is registered and associated according to the predicted residual chlorine concentration set and the secondary chlorination point site selection plan to obtain a registered chlorination plan set; Identify the trigger interval according to the registered chlorination scheme set and establish a secondary chlorination trigger domain; A secondary chlorination parameter decision is made on the secondary chlorination point site selection plan according to the secondary chlorination trigger domain to generate the secondary chlorination decision space.

2. The secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products according to claim 1, characterized in that: The secondary chlorination optimization module is also used for: Extracting a first secondary chlorination decision according to the secondary chlorination decision space; Based on the predetermined water distribution plan, performing secondary chlorination prediction on the long-distance water distribution network according to the first secondary chlorination decision, and obtaining a first decision chlorination prediction result; Determine whether the first decision-making chlorination prediction result meets the first-order optimization condition of the secondary chlorination; If the prediction result of the first decision on chlorination satisfies the first-order optimization condition of the secondary chlorination, the first decision on the secondary chlorination is added to the first-order optimization space of chlorination; The first-order optimization of the secondary chlorination decision space is continued according to the first-order optimization condition of the secondary chlorination to generate the first-order optimization space of chlorination.

3. The secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products according to claim 1, characterized in that: The secondary chlorination optimization module is also used for: According to the first-order optimization space of chlorination, extracting the nth decision of secondary chlorination, wherein n is a positive integer; Inputting the nth decision chlorination prediction result corresponding to the nth decision of the secondary chlorination into the second-order optimization function of the secondary chlorination to obtain the nth decision secondary chlorination fitness; Determining whether the nth decision secondary chlorination fitness is greater than or equal to a predetermined secondary chlorination fitness; If the nth decision secondary chlorination fitness is greater than or equal to the predetermined secondary chlorination fitness, adding the nth decision of secondary chlorination to the second-order chlorination optimization space; If the secondary chlorination fitness of the nth decision is less than the predetermined secondary chlorination fitness, the secondary chlorination nth decision is eliminated; Based on the predetermined secondary chlorination fitness, the second-order optimization function of the secondary chlorination is used to continue to perform a second-order optimization on the first-order chlorination optimization space to obtain the second-order chlorination optimization space.

4. The secondary chlorination system for long-distance water distribution network based on controlling disinfection by-products according to claim 1, characterized in that: The secondary chlorination decision module is also used for: Traversing the secondary chlorination record set, extracting the first secondary chlorination record, wherein the first secondary chlorination record includes the first sample residual chlorine concentration set, the first sample secondary chlorination point site selection plan and the first sample secondary chlorination plan; According to the predicted residual chlorine concentration set and the secondary chlorination point site selection plan, a twin evaluation is performed on the first sample residual chlorine concentration set and the first sample secondary chlorination point site selection plan to determine the first chlorination scenario registration coefficient; determining whether the first chlorination scene registration coefficient is greater than or equal to the chlorination scene registration threshold; If the first chlorination scenario registration coefficient is greater than or equal to the chlorination scenario registration threshold, the first sample secondary chlorination scheme is added to the registered chlorination scheme set.

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