Cascade utilization method and system for recycled water of urban sewage

Abstract

The invention discloses an urban sewage reclaimed water gradient utilization method and system, and relates to the technical field of urban sewage recycling. The method comprises the following steps: S1, acquiring real-time water quality parameters of effluent of a reclaimed water treatment system; s2, acquiring a real-time water quality demand or a target water quality standard corresponding to each cascade water consumption unit; s3, evaluating the water quality suitability grade between the reclaimed water outlet water and each cascade water consumption unit; s4, generating a dynamic regulation and control instruction according to the water quality suitability evaluation grade, and S5, executing the dynamic regulation and control instruction to realize optimized gradient utilization of reclaimed water. The system comprises a water quality monitoring module, a demand acquisition module, an adaptability evaluation module, a regulation and control instruction generation module, a regulation and control execution module and a feedback optimization module. The problem that in the prior art, water outlet is unstable due to inflow water quality fluctuation is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of urban sewage recycling, in particular to a method and system for gradient utilization of urban sewage recycling water. BACKGROUND

[0002] Gradient utilization of urban sewage recycling water refers to a water resource recycling method in which treated sewage is classified for different uses according to water quality differences. Generally, recycling water can be used in turn for industrial cooling, landscape environment, municipal miscellaneous use, and farmland irrigation, which have relatively high, relatively low, and the lowest water quality requirements, respectively. This classification utilization method can significantly improve water resource utilization efficiency and reduce fresh water consumption, and is an important way to achieve sustainable management of urban water resources.

[0003] However, in actual operation, due to the fluctuation of urban sewage inflow water quality, the effluent water quality of the recycling treatment system is difficult to remain stable all the time, resulting in that different gradient water units often face the problem of insufficient water quality adaptability when actually receiving recycling water. The existing technology relies on fixed process parameters for treatment, lacks real-time response and regulation and control capability for dynamic water quality demand in multi-level water use scenarios, causes water quality risk hidden in high-standard water units, and over-treatment in low-standard water units, thereby restricting the efficiency and economy of overall gradient utilization. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a method and system for gradient utilization of urban sewage recycling water to solve the problems of unstable effluent water due to fluctuation of urban sewage inflow water quality, and insufficient water quality adaptability of gradient water units, high-standard water risk, and over-treatment of low-standard water due to lack of dynamic response of fixed process parameters, avoid unstable effluent water caused by fluctuation of inflow water quality, and improve the efficiency and economy of gradient utilization.

[0005] To achieve the above object, the present application is realized by the following technical scheme.

[0006] A method for gradient utilization of urban sewage recycling water, comprising:

[0007] S1, acquiring real-time water quality parameters of effluent water of a recycling water treatment system, the real-time water quality parameters including pH value, turbidity, chemical oxygen demand COD, total nitrogen TN, and total phosphorus TP;

[0008] S2, acquiring real-time water quality demand or target water quality standard corresponding to each gradient water unit, the gradient water units including industrial cooling, landscape environment, municipal miscellaneous use, and farmland irrigation;

[0009] S3, according to the real-time water quality parameter and the real-time water quality demand or target water quality standard, evaluating the water quality adaptability level between the regenerated water effluent and each cascade water unit through a preset water quality adaptability evaluation model;

[0010] S4, generating a dynamic control instruction according to the water quality adaptability evaluation level, the dynamic control instruction including adjusting the process parameters of the regenerated water treatment system and controlling the distribution path and flow of the regenerated water;

[0011] S5, executing the dynamic control instruction to dynamically match the water quality of the regenerated water with the real-time water quality demand or target water quality standard of each cascade water unit, and realizing the optimized cascade utilization of the regenerated water.

[0012] Further,

[0013] The real-time water quality parameter of the regenerated water treatment system effluent obtained in S1 includes:

[0014] Through the deployment of multiple types of online water quality sensors on the regenerated water treatment system effluent pipeline, real-time continuous collection of pH value, turbidity, COD, total nitrogen and total phosphorus water quality data is performed;

[0015] The collected water quality data is preprocessed, and the preprocessing includes data cleaning, calibration and outlier detection to obtain accurate and reliable real-time water quality parameters.

[0016] In S2, when obtaining the real-time water quality demand or target water quality standard corresponding to each cascade water unit, it includes:

[0017] From the integrated target water quality standard database, according to the actual use, importance and historical water use characteristics of each cascade water unit, the corresponding preset target water quality standard is queried and obtained;

[0018] Receive real-time water quality demand input from each cascade water unit, and dynamically use it as the current target water quality standard to realize flexible response at the demand end.

[0019] In S3, the water quality adaptability level between the regenerated water effluent and each cascade water unit is evaluated through a preset water quality adaptability evaluation model, which includes:

[0020] Using a multi-index comprehensive evaluation algorithm, the real-time water quality parameter and the real-time water quality demand or target water quality standard are compared item by item;

[0021] According to the accurate comparison results of each index, a comprehensive water quality adaptability index is calculated in combination with preset weight coefficients and experience;

[0022] According to the comprehensive water quality adaptability index and the preset threshold interval, the water quality adaptability is divided into multiple clear levels, and the levels include "complete adaptation", "basic adaptation", "edge adaptation" and "non-adaptation";

[0023] The specific process is as follows:

[0024] The min-max normalization method is used for normalization processing of the real-time water quality parameters and the target water quality standard, and the normalization formula is as follows:

[0025]

[0026] Wherein, x' ij is the normalized value of the jth water quality index in the ith detection, x ij is the original value of the jth water quality index in the ith detection, min(x j ) is the minimum value of the jth water quality index in the historical detection data, and max(x j ) is the maximum value of the jth water quality index in the historical detection data;

[0027] After normalization, the multi-index comprehensive evaluation algorithm is used to calculate the comprehensive water quality adaptability index, and the weighted summation method is selected, and the formula is as follows:

[0028]

[0029] Wherein, I is the comprehensive water quality adaptability index, n is the number of water quality indexes participating in evaluation, n is 5 in the embodiment, which corresponds to pH value, turbidity, chemical oxygen demand COD, total nitrogen TN and total phosphorus TP, w j is the weight coefficient of the jth water quality index, the sum of the weight coefficients of all indexes is equal to 1, y' j is the normalized value of the jth water quality index target water quality standard;

[0030] Finally, according to the comprehensive water quality adaptability index and the preset threshold interval, the water quality adaptability level is divided: when I≤0.1, the level is "complete adaptation"; When 0.1<I≤0.3, the level is "basic adaptation"; When 0.3<I≤0.5, the level is "edge adaptation"; When I>0.5, the level is "non-adaptation".

[0031] The process parameters of the reclaimed water treatment system in S4 are adjusted, including:

[0032] If the water quality adaptability level is "non-adaptation" or "edge adaptation", at least one process unit in the reclaimed water treatment system is selectively adjusted according to the specific water quality index and the deviation degree leading to insufficient adaptability, and the process unit includes a biological reactor, a membrane separation unit, a advanced oxidation unit and a disinfection unit;

[0033] The adjustment of the process parameters includes the aeration amount, the membrane flux, the dosage of the medicament, the reaction time, and the ultraviolet irradiation intensity, so that the regenerated water meets the target water quality requirements.

[0034] The distribution path and flow of the regenerated water in the S4 are regulated, including:

[0035] Based on the water quality adaptability evaluation grade, the priority order of each cascade water unit, and the total amount of currently available regenerated water, an initial allocation scheme is generated;

[0036] If the total amount of regenerated water with good adaptability cannot meet the demand of all high-priority cascade water units, the allocation flow of the high-priority units is dynamically adjusted, and the remaining regenerated water is allocated to lower-priority cascade water units according to the water quality adaptability grade, to ensure the maximum effective use of water resources.

[0037] The above method further includes:

[0038] After executing the dynamic regulation instruction, real-time water quality parameters of the regenerated water treatment system and actual water quality data of each cascade water unit are continuously obtained in real time;

[0039] The actual water quality data obtained is compared and analyzed in detail with the expected effect of the dynamic regulation instruction, to evaluate the actual effectiveness of the dynamic regulation instruction;

[0040] Based on the effectiveness evaluation result, the water quality adaptability evaluation model and the dynamic regulation decision model are updated and iteratively optimized in real time, to continuously improve the response speed and regulation accuracy of the system.

[0041] The above method further includes:

[0042] A historical operation database is established and maintained, for storing long-time sequence key data, including real-time water quality parameters, target water quality standards, water quality adaptability evaluation grades, dynamic regulation instructions, and execution effects;

[0043] Using the historical operation data, pattern recognition, trend analysis, and predictive analysis are performed through advanced machine learning algorithms, to predict future water quality fluctuation trends and changes in cascade water demand, thereby realizing intelligent predictive regulation of regenerated water treatment and distribution.

[0044] The above method further includes:

[0045] Through an intuitive user interface, the running state of the regenerated water treatment system, the water quality adaptability status of each cascade water unit, the execution process of the dynamic regulation instruction, and the visual display of detailed historical data reports are provided in real time;

[0046] The user interface also supports authorized users to manually intervene in parameters, adjust strategies, or perform manual operations in emergencies to deal with unexpected situations or specific management needs.

[0047] The present invention also provides a system for the cascade utilization of urban wastewater, for applying the method for the cascade utilization of urban wastewater as described above, comprising:

[0048] The water quality monitoring module is configured to acquire real-time water quality parameters of the effluent from the reclaimed water treatment system and perform pretreatment.

[0049] The demand acquisition module is configured to acquire the real-time water quality demand or target water quality standard corresponding to each cascade water use unit;

[0050] The compatibility assessment module is configured to assess the water quality compatibility level between the reclaimed water effluent and each cascade water use unit based on real-time water quality parameters and real-time water quality requirements or target water quality standards.

[0051] The control instruction generation module is configured to generate dynamic control instructions based on the water quality adaptability assessment level. The dynamic control instructions include adjusting the process parameters of the reclaimed water treatment system, as well as controlling the distribution path and flow rate of the reclaimed water.

[0052] The control execution module is configured to execute dynamic control commands;

[0053] The feedback optimization module is configured to continuously acquire actual water quality data, evaluate the effectiveness of dynamic control commands, and perform real-time parameter updates and optimizations for the adaptability assessment module and the control command generation module.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] This invention uses water quality sensors to collect parameters such as pH and turbidity of the effluent from the reclaimed water treatment system in real time and pre-process them. It then combines an integrated target water quality standard database with the real-time needs of each cascade water-using unit to obtain water quality standards. A multi-index comprehensive evaluation algorithm is used to assess the water quality suitability level, and process parameters of bioreactors, membrane separation units, etc., as well as the reclaimed water distribution path and flow rate, are adjusted accordingly. This solves the problems in existing technologies where fluctuations in influent water quality lead to unstable effluent, reliance on fixed processes lacks dynamic response, and consequently, water quality risks in high-standard water-using units and over-treatment in low-standard water-using units. Simultaneously, through feedback optimization iterative models, historical data machine learning predictive control, and user interface visualization and manual intervention, the system's response speed and control accuracy are continuously improved, avoiding resource waste and effectively enhancing the efficiency and economy of cascaded reclaimed water utilization, achieving optimized cascaded utilization of reclaimed water. Attached Figure Description

[0056] Figure 1A flow chart of the method for cascade utilization of municipal sewage reclaimed water in the present application.

[0057] Figure 2 A structural diagram of the system for cascade utilization of municipal sewage reclaimed water in the present application.

[0058] Figure 3 A circulation diagram of the intelligent feedback and prediction optimization in the present application. DETAILED DESCRIPTION

[0059] The following is a detailed description of the method for cascade utilization of municipal sewage reclaimed water in the present application, which comprises the following steps: Figure 1

[0060] S1, acquiring real-time water quality parameters of effluent of a reclaimed water treatment system, the real-time water quality parameters including pH value, turbidity, chemical oxygen demand COD, total nitrogen TN and total phosphorus TP;

[0061] S2, acquiring real-time water quality requirements or target water quality standards corresponding to each cascade water use unit, the cascade water use units including industrial cooling, landscape environment, municipal miscellaneous use and farmland irrigation;

[0062] S3, according to the real-time water quality parameters and the real-time water quality requirements or target water quality standards, evaluating water quality adaptability levels between the reclaimed water effluent and each cascade water use unit through a preset water quality adaptability evaluation model;

[0063] S4, generating dynamic control instructions according to the water quality adaptability evaluation levels, the dynamic control instructions including adjusting process parameters of the reclaimed water treatment system, and controlling distribution paths and flow rates of the reclaimed water;

[0064] S5, executing the dynamic control instructions to dynamically match the water quality of the reclaimed water with the real-time water quality requirements or target water quality standards of each cascade water use unit, and realizing optimized cascade utilization of the reclaimed water.

[0065] The following is a detailed description of each step.

[0066] S1, acquiring real-time water quality parameters of effluent of a reclaimed water treatment system.

[0067] Multiple types of online water quality sensors are deployed at key positions of effluent pipelines of the reclaimed water treatment system to ensure that the sensors can comprehensively capture changes in effluent water quality, and the acquired real-time water quality parameters include pH value, turbidity, chemical oxygen demand COD, total nitrogen TN and total phosphorus TP. To ensure data accuracy, the acquired water quality data need to be preprocessed:

[0068] First, data cleaning is performed to remove noise data generated due to transient interference of the sensors;

[0069] ​Then, the sensor is calibrated by the standard solution corresponding to the water quality index to avoid the data deviation caused by instrument drift.

[0070] Finally, the abnormal value detection is performed. For example, the 3σ principle is adopted to calculate the mean value μ and the standard deviation σ of the multiple collected data of an index. If a collected value exceeds the range of μ±3σ, it is determined as an abnormal value. At this time, the average value of the previous five normal collected values of the index is used to replace the abnormal value, and finally the accurate and reliable real-time water quality parameter is obtained.

[0071] S2, obtaining real-time water quality requirements or target water quality standards corresponding to each cascade water use unit.

[0072] Each cascade water use unit specifically includes industrial cooling, landscape environment, municipal miscellaneous use, and farmland irrigation. First, a target water quality standard database is integrated. The database stores the water quality standards of different cascade water use units under normal scenarios. The staff can query and obtain the corresponding preset target water quality standards from the database according to the actual use, importance, and historical water use characteristics of each cascade water use unit. For example, the preset target standard of industrial cooling water for COD is usually required to be low to avoid pipe fouling, and the preset target standard of landscape environment water for turbidity is usually required to be low to ensure the visual effect. At the same time, the system supports receiving real-time water quality requirement input from each cascade water use unit. For example, due to temporary adjustment of production process, the industrial user needs to improve the water quality requirement of cooling water. The adjusted requirement can be input through the system terminal. The system will dynamically use the real-time requirement as the current target water quality standard to realize flexible response to the demand side.

[0073] S3, according to the real-time water quality parameter and the real-time water quality requirement or the target water quality standard, the water quality adaptability level between the regenerated water effluent and each cascade water use unit is evaluated through a preset water quality adaptability evaluation model.

[0074] The multi-index comprehensive evaluation algorithm is used to compare the real-time water quality parameter and the real-time water quality requirement or the target water quality standard item by item; according to the accurate comparison result of each index, the comprehensive water quality adaptability index is calculated by combining the preset weight coefficient and the expert experience; according to the comprehensive water quality adaptability index and the preset threshold interval, the water quality adaptability is divided into multiple clear levels, including “complete adaptation”, “basic adaptation”, “edge adaptation”, and “inadaptation”.

[0075] The specific process is as follows.

[0076] Since there are differences in the dimensions of different water quality indexes, for example, the unit of COD is mg / L, and the unit of pH value is unitless, direct calculation will affect the evaluation accuracy. Therefore, the min-max normalization method is used to normalize the real-time water quality parameter and the target water quality standard. The normalization formula is as follows:

[0077]

[0078] wherein x′ ij is the normalized value of the jth water quality index in the ith detection, x ij is the original value of the jth water quality index in the ith detection, min(x j ) is the minimum value of the jth water quality index in the historical detection data, and max(x j ) is the maximum value of the jth water quality index in the historical detection data.

[0079] After normalization, a multi-index comprehensive evaluation algorithm is used to calculate a comprehensive water quality adaptability index. The weighted summation method is selected for the algorithm, and the formula is as follows:

[0080]

[0081] wherein I is the comprehensive water quality adaptability index, n is the number of water quality indexes participating in the evaluation, n is 5 in the embodiment, corresponding to pH value, turbidity, chemical oxygen demand COD, total nitrogen TN and total phosphorus TP, w j is the weight coefficient of the jth water quality index, the weight coefficient is determined by expert experience combined with the analytic hierarchy process, for example, considering that COD has a greater impact on equipment in industrial cooling water, the weight coefficient of COD can be set to 0.25, the weight coefficient of pH value can be set to 0.2, the weight coefficient of turbidity can be set to 0.2, the weight coefficient of TN can be set to 0.15, and the weight coefficient of TP can be set to 0.2, and the sum of the weight coefficients of all indexes satisfies the condition that the sum is equal to 1, y′ j is the normalized value of the jth water quality index target water quality standard.

[0082] Finally, the water quality adaptability grade is divided according to the comprehensive water quality adaptability index and the preset threshold interval: when I≤0.1, the grade is “completely adapted”; when 0.1<I≤0.3, the grade is “basically adapted”; when 0.3<I≤0.5, the grade is “edge adapted”; and when I>0.5, the grade is “not adapted”. The evaluation process can accurately reflect the adaptation of reclaimed water to each cascade water unit, and provide clear basis for subsequent regulation and control.

[0083] S4, generating a dynamic regulation and control instruction according to the water quality adaptability evaluation grade.

[0084] The dynamic control instructions consist of two parts: first, adjusting the process parameters of the reclaimed water treatment system; and second, regulating the distribution path and flow rate of the reclaimed water. For example, when the suitability level of a certain water-using unit is "incompatible," the specific water quality indicators causing the incompatibility are first analyzed. If it is found that COD exceeds the standard, the dosage of reagents in the advanced oxidation unit of the reclaimed water treatment system is adjusted accordingly. If the suitability level is "fully compatible," the current process parameters are maintained to avoid overtreatment. Regarding the distribution path and flow rate control, a priority order is first set according to the importance of each water-using unit. For example, industrial cooling water has a higher priority than municipal miscellaneous water due to its connection with production continuity. Then, a preliminary distribution plan is formulated based on the real-time suitability level and the current total amount of available reclaimed water.

[0085] S5. Execute dynamic control commands to ensure that the quality of reclaimed water dynamically matches the real-time water quality requirements or target water quality standards of each cascade water use unit, thereby achieving optimized cascade utilization of reclaimed water.

[0086] The system executes dynamic control commands, which are then sent via an automatic control module to valves, pumps, and other equipment in the process units and distribution network of the reclaimed water treatment system. For example, it adjusts the aeration rate of the bioreactor, the membrane flux of the membrane separation unit, or controls the valve opening of corresponding cascade water-using units in the distribution network to regulate flow. After execution, the quality of the reclaimed water dynamically matches the real-time water quality requirements or target water quality standards of each cascade water-using unit, effectively avoiding water quality risks in high-standard water-using units, reducing over-treatment in low-standard water-using units, and improving the overall efficiency and economy of cascade utilization.

[0087] In this embodiment, obtaining real-time water quality parameters of the effluent from the reclaimed water treatment system in step S1 includes:

[0088] By deploying multiple types of online water quality sensors on the effluent pipeline of the reclaimed water treatment system, real-time and continuous data on various water quality parameters such as pH, turbidity, COD, total nitrogen, and total phosphorus are collected.

[0089] The collected water quality data is preprocessed, including data cleaning, calibration, and outlier detection, to obtain accurate and reliable real-time water quality parameters.

[0090] Specifically, when acquiring real-time water quality parameters of the effluent from the reclaimed water treatment system, the deployment scheme of online water quality sensors is first determined: multiple types of online water quality sensors are deployed at the main outlet of the effluent pipeline of the reclaimed water treatment system and before the inlet of the branch pipelines to each cascade water use unit to ensure that the total effluent water quality and the water quality before entering each cascade water use unit can be monitored simultaneously. The sensor type must match the monitoring index. For example, glass electrode sensors are used to monitor pH value, scattered light sensors are used to monitor turbidity, potassium dichromate method online analyzers are used to monitor COD, and ultraviolet spectrophotometric sensors are used to monitor TN and TP.

[0091] The data preprocessing process needs to be executed meticulously in stages: In the data cleaning stage, a moving average method is used to smooth the continuously collected water quality data. For example, a 10-minute moving average window is used, and the average value within that window is calculated as the final collected value at that moment, removing transient pulse interference. In the calibration stage, nationally recognized standard substances are used monthly to perform single-point or multi-point calibration on each sensor. For example, when calibrating the COD sensor, COD standard solutions of 0 mg / L, 50 mg / L, and 100 mg / L are used for calibration to correct the sensor's measurement deviation. In the outlier detection stage, in addition to using the 3σ principle, the trend of data changes at adjacent time points can also be considered. For example, if the TN detection value suddenly increases by 5 times compared to the previous time point without significant process adjustments, it can be identified as an outlier. In this case, linear interpolation is used to supplement the data at that time point to ensure the continuity and accuracy of real-time water quality parameters. The water quality parameters obtained in this way can truly reflect the condition of the reclaimed water effluent, laying a reliable foundation for subsequent suitability assessments.

[0092] In this embodiment, S2, when obtaining the real-time water quality requirements or target water quality standards corresponding to each cascade water use unit, includes:

[0093] From the integrated target water quality standard database, based on the actual use, importance and historical water use characteristics of each water use unit, the corresponding preset target water quality standards are queried and obtained;

[0094] It receives real-time water quality demand inputs from each cascade water use unit and dynamically uses them as the current target water quality standard to achieve flexible response on the demand side.

[0095] Specifically, when obtaining real-time water quality requirements or target water quality standards corresponding to each tier of water use units, a multi-dimensional requirement acquisition mechanism needs to be constructed. First, the target water quality standard database needs to cover national and local standards for different industries and scenarios. For example, industrial cooling water should refer to the relevant requirements in the "Design Code for Industrial Circulating Cooling Water Treatment," municipal miscellaneous water should refer to the requirements in the "Water Quality Standard for Urban Miscellaneous Water Used in Urban Wastewater Reuse," and farmland irrigation water should refer to the requirements in the "Farmland Irrigation Water Quality Standard." When staff query preset target water quality standards, they need to further filter based on the actual use, importance, and historical water use characteristics of each tier of water use unit. For example, if the cooling water in an industrial park is used for cooling high-temperature equipment, the requirements for water quality corrosion prevention are higher. Therefore, the pH control range can be appropriately increased based on the national standard, and the pH value of the preset target standard can be adjusted to 7.5-8.5.

[0096] Simultaneously, the system needs to provide a convenient real-time water quality demand input interface, allowing managers of each tier of water use units to input their needs via computer terminals, mobile apps, or on-site control panels. For example, if a landscape and environmental water use unit needs to temporarily reduce turbidity to improve the landscape effect due to a large-scale event, managers can input a real-time demand of "turbidity ≤ 3 NTU." Upon receiving this demand, the system will automatically override the unit's current preset target standard and use it as the basis for subsequent adaptability assessments. Furthermore, the system will record historical demand data for each tier of water use units. By analyzing historical data, it can identify patterns in demand changes. For instance, if municipal miscellaneous water use increases during the rainy season and water quality requirements slightly decrease, the system can proactively remind staff whether to adjust preset standards, achieving a forward-looking response on the demand side. This approach can accommodate both routine and temporary needs, ensuring the comprehensiveness and flexibility of water quality demand acquisition.

[0097] In this embodiment, S3, evaluating the water quality compatibility level between the reclaimed water effluent and each cascade water use unit includes:

[0098] Using a multi-index comprehensive evaluation algorithm, real-time water quality parameters are compared with real-time water quality requirements or target water quality standards item by item.

[0099] Based on the precise comparison results of various indicators, combined with the preset weighting coefficients and expert experience, the comprehensive water quality adaptability index is calculated.

[0100] Based on the comprehensive water quality compatibility index and the preset threshold range, water quality compatibility is divided into several distinct levels, including "fully compatible", "basically compatible", "marginally compatible" and "not compatible".

[0101] Specifically, when assessing the water quality compatibility between reclaimed water effluent and each cascade water use unit, the process of "item-by-item comparison - weight allocation - comprehensive calculation - grade classification" must be followed. First, a detailed comparison is performed item by item, comparing the normalized real-time water quality parameters with the normalized values ​​of the target water quality standards one by one, analyzing the degree of deviation for each indicator. For example, if the normalized target standard value for COD of an industrial cooling water unit is 0.2, and the normalized real-time COD value is 0.4, the deviation is 0.2, indicating a certain risk of exceeding the COD standard. If the normalized target standard value for pH is 0.5, and the normalized real-time pH value is 0.55, the deviation is 0.05, indicating that the pH value basically meets the requirements.

[0102] The determination of weighting coefficients needs to consider expert experience and the importance of the actual water use scenario. For example, in farmland irrigation, TN and TP have a significant impact on soil and crops, so the weighting coefficients for TN and TP can be increased to 0.25, while the weighting coefficients for pH, turbidity, and COD can be set to 0.15, 0.15, and 0.2, respectively. In landscape water use, turbidity has the greatest impact on visual effects, so the weighting coefficient for turbidity can be set to 0.3, and the weighting coefficients for other indicators can be appropriately reduced. After determining the weighting coefficients, the I value is calculated by substituting them into the comprehensive water quality suitability index formula.

[0103] The classification of water quality levels should be based on reasonable threshold ranges set according to actual application scenarios. For example, for cooling water in the electronics industry with extremely high requirements, the threshold for "fully compatible" can be adjusted to I≤0.05 to ensure absolute water quality safety; for municipal greening water with relatively lower requirements, the threshold for "fully compatible" can be relaxed to I≤0.15 to avoid over-treatment. This refined assessment method can accurately distinguish the compatibility of different water use units. For example, the compatibility level of a certain reclaimed water effluent for industrial cooling water is "not compatible," but the compatibility level for municipal miscellaneous water is "basically compatible," providing clear guidance for subsequent allocation path adjustments and improving the practicality of compatibility assessment.

[0104] In this embodiment, adjusting the process parameters of the reclaimed water treatment system in step S4 includes:

[0105] If the water quality suitability level is "unsuitable" or "marginal suitable", then at least one process unit in the reclaimed water treatment system is selectively adjusted according to the specific water quality indicators and the degree of deviation that cause the insufficient suitability. The process unit includes a bioreactor, a membrane separation unit, an advanced oxidation unit, and a disinfection unit.

[0106] Adjustments to process parameters include aeration rate, membrane flux, reagent dosage, reaction time, and ultraviolet irradiation intensity, to ensure that the reclaimed water effluent meets the target water quality requirements.

[0107] Specifically, when the water quality compatibility level is "incompatible" or "marginally compatible," the process units in the reclaimed water treatment system need to be adjusted specifically based on the specific water quality indicators and the degree of deviation causing the incompatibility. First, analyze the specific indicators exceeding the standards. If the test reveals that excessive TN (total nitrogen) is the main cause of the incompatibility, then adjust the process parameters of the bioreactor. For example, increase the aeration rate to improve nitrification efficiency, or extend the residence time of wastewater in the bioreactor to enhance denitrification. If COD (chemical oxygen demand) exceeds the standard, then adjust the process parameters of the advanced oxidation unit. For example, increase the dosage of the oxidant (hydrogen peroxide can be used), or increase the intensity of ultraviolet radiation to enhance oxidative decomposition.

[0108] If excessive turbidity leads to insufficient compatibility, adjust the process parameters of the membrane separation unit. For example, reduce the membrane flux to decrease membrane fouling, or increase the backwashing frequency to restore membrane filtration performance. If there is a risk of excessive microbial levels, adjust the process parameters of the disinfection unit. For example, increase the dosage of disinfectant (sodium hypochlorite can be used), or extend the disinfection contact time. For instance, if the compatibility level of a certain reclaimed water effluent for landscape environmental water use is "marginal compatibility," and analysis shows that the turbidity is slightly higher than the target standard, the system will automatically increase the membrane flux of the membrane separation unit from 20 L / (m²). 2 ·h) adjusted to 18L / (m 2 (h) At the same time, the backwashing frequency was increased from once every 2 hours to once every 1.5 hours. After the adjustment, the turbidity was significantly reduced, and the compatibility level was improved to "basic compatibility". Through this targeted adjustment method, the quality of reclaimed water can be quickly improved, ensuring that the effluent meets the target water quality requirements and avoiding increased energy consumption caused by blind adjustments.

[0109] In this embodiment, S4, when regulating the distribution path and flow rate of the reclaimed water, includes:

[0110] An initial allocation scheme is generated based on the water quality suitability assessment level, the priority order of each water use unit, and the current total amount of reclaimed water available.

[0111] If the total amount of reclaimed water with good adaptability cannot meet the needs of all high-priority cascade water use units, the allocation flow of high-priority units will be dynamically adjusted, and the remaining reclaimed water will be allocated to lower-priority cascade water use units according to the water quality adaptability level, so as to ensure the maximum effective use of water resources.

[0112] Specifically, when regulating the allocation path and flow of reclaimed water, the core basis should be the water quality suitability assessment level, the priority order of each tier of water use units, and the current total amount of available reclaimed water. First, the priority order of each tier of water use units should be set. For example, industrial cooling water should be set as the first priority because industrial cooling water involves the continuity of industrial production, and substandard water quality may lead to equipment failure. Landscape and environmental water should be set as the second priority, municipal miscellaneous water as the third priority, and farmland irrigation water as the fourth priority.

[0113] An initial allocation scheme is generated based on the above priorities and adaptability levels. For example, if the current total available reclaimed water is 1000 m³. 3 / d, of which 400m³ is industrial cooling water with a compatibility rating of "fully compatible". 3 The average daily demand for industrial cooling water is 400m³. 3 At this point, the initial plan will be 400m 3 All reclaimed water is allocated to industrial cooling water; the volume of water with a "basic fit" rating for landscaping is 300 m³.3 The average daily water demand for landscape environment is 300m³. 3 300m 3 All allocated to landscape and environmental water use; the remaining 300m 3 Reclaimed water with an "adaptability level of basic compatibility" is allocated to municipal miscellaneous water use.

[0114] If the total amount of reclaimed water with good adaptability cannot meet the needs of all high-priority cascade water use units, for example, if the total amount of reclaimed water available at a certain time is 800 m³, then... 3 / d, the water volume for industrial cooling water with a "fully compatible" rating is only 350m³. 3 The average daily demand for industrial cooling water is 400 cubic meters. 3 At this point, the allocated flow of high-priority units is dynamically adjusted, increasing the flow to 350m. 3 All water is allocated to industrial cooling water, and the system notifies industrial users that the current water volume has slightly decreased, suggesting appropriate adjustments to production load; simultaneously, the compatibility of secondary priority units is checked, and if there are 200m... 3 If the suitability level of reclaimed water for landscape environmental water use is "fully suitable", then the 200m 3 250m³ of water was allocated to the landscape environment. 3 It is allocated to municipal miscellaneous water use. This dynamic allocation method can prioritize the basic water needs of high-priority units when water resources are limited, while maximizing the use of reclaimed water and avoiding water waste.

[0115] In this embodiment, the method further includes:

[0116] After executing the dynamic control command, the system continuously acquires real-time water quality parameters of the effluent from the reclaimed water treatment system and actual water quality data of each water-using unit.

[0117] A detailed comparative analysis will be conducted between the actual water quality data obtained and the expected effects of the dynamic control instructions to evaluate the actual effectiveness of the dynamic control instructions.

[0118] Based on the effectiveness assessment results, the water quality adaptability assessment model and the dynamic control decision model are updated and iteratively optimized in real time to continuously improve the system's response speed and control accuracy.

[0119] Specifically, after executing dynamic control commands, the system needs to enter a continuous monitoring and optimization phase. First, sensors deployed in the effluent pipes of the reclaimed water treatment system and the influent pipes of each cascade water-using unit continuously acquire real-time water quality parameters of the effluent from the reclaimed water treatment system and actual water quality data of each cascade water-using unit, for example, data is collected every 5 minutes to ensure timely detection of water quality changes.

[0120] Then, the actual water quality data obtained are compared and analyzed with the expected effects of the dynamic control commands to evaluate the actual effectiveness of the commands. For example, if the expected effect of a certain control command is to reduce the COD of reclaimed water from 60 mg / L to below 40 mg / L, and actual monitoring shows that the COD stabilizes at 38 mg / L after adjustment, the control command is effective. If actual monitoring shows that the COD only drops to 55 mg / L and fails to achieve the expected effect, the reason may be insufficient dosage of reagents in the advanced oxidation unit or insufficient reaction time.

[0121] Based on the effectiveness assessment results, the water quality adaptability assessment model and the dynamic control decision model are updated and iteratively optimized in real time. For example, if the weight coefficient of a certain water quality indicator is found to cause a large deviation between the assessment results and the actual adaptability, the weight coefficient of that indicator can be adjusted; if the adjustment range of a certain process parameter is always too large, the parameter adjustment algorithm in the control decision model can be optimized. Through this continuous optimization method, the system's response speed and control accuracy can be continuously improved, ensuring the long-term stability of the cascade utilization effect of reclaimed water.

[0122] In this embodiment, the method further includes:

[0123] Establish and maintain a historical operation database to store key data over long time series, including real-time water quality parameters, target water quality standards, water quality suitability assessment levels, dynamic control instructions and their effects.

[0124] By utilizing historical operational data and employing advanced machine learning algorithms for pattern recognition, trend analysis, and predictive analysis, the system can predict future water quality fluctuation trends and changes in water demand at each tier, thereby enabling intelligent predictive regulation of reclaimed water treatment and distribution.

[0125] Specifically, when establishing and maintaining a historical operational database, the data types and storage periods must be clearly defined. Key data stored in the database includes real-time water quality parameters over long time series, such as hourly data on pH, turbidity, COD, TN, and TP; target water quality standards for each water-using unit; water quality suitability assessment levels; dynamic control commands, such as process parameter adjustment values ​​and allocated flow data; and their effects, such as adjusted water quality changes. The storage period should be set at least three years to ensure sufficient historical data is accumulated for analysis.

[0126] When using historical operational data for predictive analysis, advanced machine learning algorithms, such as Long Short-Term Memory (LSTM) networks, are employed. First, the historical data is preprocessed, including data normalization and missing value imputation. Then, the preprocessed data is divided into training and testing sets for training and validating the LSTM model. Once the model is trained, it can predict water quality fluctuation trends and changes in water demand at various levels over a future period. For example, it can predict the potential fluctuation range of COD in reclaimed water within the next 24 hours, or predict changes in municipal miscellaneous water demand within the next week.

[0127] Intelligent predictive regulation is achieved based on forecast results. For example, if it is predicted that total nitrogen (TN) may increase due to fluctuations in influent water quality within the next 12 hours, the system can adjust the aeration rate and retention time of the bioreactor in advance to avoid TN exceeding the standard and causing a decrease in adaptability. If it is predicted that the demand for farmland irrigation water will increase within the next 3 days, the system can adjust the reclaimed water allocation plan in advance to reserve sufficient suitable water volume. Through this predictive regulation method, the traditional "passive response" can be transformed into "proactive prevention," reducing the risk of water quality exceeding the standard and further improving the stability of reclaimed water cascade utilization.

[0128] In this embodiment, the method further includes:

[0129] Through an intuitive user interface, the system provides real-time visualization of the operating status of the reclaimed water treatment system, the water quality compatibility of each water-using unit, the execution process of dynamic control commands, and detailed historical data reports.

[0130] The user interface also supports authorized users to manually intervene in parameters, adjust strategies, or perform manual operations in emergencies to deal with unexpected situations or specific management needs.

[0131] Specifically, when designing an intuitive user interface, it is necessary to balance the comprehensiveness of data display with ease of operation. The main page of the user interface displays the real-time operating status of the reclaimed water treatment system, including the current operating parameters of each process unit, which may include bioreactors, membrane separation units, etc., as well as the working status of sensors. It also displays the water quality compatibility status of each stage of water use units, using color to indicate the compatibility level. For example, green indicates "fully compatible", blue indicates "basically compatible", yellow indicates "marginally compatible", and red indicates "not compatible", making it clear to staff at a glance.

[0132] Regarding the display of the execution process of dynamic control commands, the interface updates the execution progress and results of the commands in real time. For example, the execution progress of a certain process parameter adjustment command is 80%, or the actual flow value after a certain distribution flow is adjusted. Detailed historical data reports can be obtained through the "Report Query" module of the interface. Staff can select the query time period according to their needs, such as the past day, the past week, or the past month, and the data type, such as water quality parameters, adaptability level, and control commands. Reports can be exported to Excel or PDF format.

[0133] The user interface also supports manual intervention by authorized users, who must log in to the system using an account and password or fingerprint verification. Regarding manual parameter intervention, if staff find the automatically generated process parameter adjustment values ​​to be unreasonable, they can manually enter adjustment values, for example, changing the membrane flux from 18 L / (m²) to... 2 ·h) Manually adjust to 17L / (m 2 •h); Regarding strategy adjustments, the priority of each water-using unit can be adjusted according to actual management needs. For example, during the dry season, the priority of farmland irrigation water can be raised to level two. In emergencies, such as sensor malfunctions causing data anomalies, manual operations can be performed, such as closing the inlet valve of a certain water-using unit and switching to a backup water source. Through this user interface, staff can monitor the system's operation in real time, flexibly respond to various situations, and improve the convenience of system management.

[0134] This invention also provides a system for the cascade utilization of urban wastewater, used in applying the urban wastewater cascade utilization method as described above, such as... Figure 2 As shown, the system includes:

[0135] The water quality monitoring module is configured to acquire real-time water quality parameters of the effluent from the reclaimed water treatment system and perform pretreatment.

[0136] The demand acquisition module is configured to acquire the real-time water quality demand or target water quality standard corresponding to each cascade water use unit;

[0137] The compatibility assessment module is configured to assess the water quality compatibility level between the reclaimed water effluent and each cascade water use unit based on real-time water quality parameters and real-time water quality requirements or target water quality standards.

[0138] The control instruction generation module is configured to generate dynamic control instructions based on the water quality adaptability assessment level. The dynamic control instructions include adjusting the process parameters of the reclaimed water treatment system, as well as controlling the distribution path and flow rate of the reclaimed water.

[0139] The control execution module is configured to execute dynamic control commands;

[0140] The feedback optimization module is configured to continuously acquire actual water quality data, evaluate the effectiveness of dynamic control commands, and perform real-time parameter updates and optimizations for the adaptability assessment module and the control command generation module.

[0141] Specifically, the water quality monitoring module consists of multiple types of online water quality sensors and a data preprocessing unit. The online water quality sensors are deployed at the main outlet of the reclaimed water treatment system's effluent pipeline and at the inlet pipelines of each stage of the water-using unit. The sensor types are matched to the monitoring indicators, such as glass electrode pH sensors and diffuse light turbidity sensors. The data preprocessing unit integrates data cleaning, calibration, and outlier detection functions. It processes the data collected by the sensors using built-in algorithms to output accurate real-time water quality parameters. This module provides reliable data support for subsequent compatibility assessments.

[0142] The demand acquisition module includes a target water quality standard database and a demand input interface. The target water quality standard database stores water quality standards for different water use units issued by the state and local governments, allowing staff to query preset standards based on the purpose, importance, and historical characteristics of the water use unit. The demand input interface allows each water use unit to input real-time water quality requirements through terminal devices. The input data is automatically synchronized to the system and used as the current target water quality standard. This module enables comprehensive acquisition of water quality requirements.

[0143] The adaptability assessment module has a built-in water quality adaptability assessment model. The model integrates the min-max normalization algorithm and the multi-index weighted summation algorithm. It can automatically read the real-time water quality parameters output by the water quality monitoring module and the target water quality standards output by the demand acquisition module, calculate the comprehensive water quality adaptability index, classify the adaptability level according to the preset threshold, and output the assessment results to the control instruction generation module.

[0144] Based on the assessment results of the adaptability assessment module, the control instruction generation module combines the preset priority order of cascade water use units and the current available total amount of reclaimed water, and generates dynamic control instructions through built-in decision logic. The instructions include process parameter adjustment values ​​and allocation path flow schemes, and are sent to the control execution module after generation.

[0145] The control and execution module consists of an automatic control unit and an actuator. After receiving the control command, the automatic control unit converts the command into an execution signal. The actuator includes the process unit controller of the reclaimed water treatment system and the valves and pump groups of the reclaimed water distribution network. The process unit controller may include the aeration controller of the bioreactor, the membrane flux controller of the membrane separation unit, etc. The actuator completes the control operation according to the execution signal to realize the dynamic adjustment of water quality and distribution.

[0146] The feedback optimization module collects actual water quality data in real time after the control is implemented, compares and analyzes it with the expected effect of the control command, evaluates the effectiveness of the command, and automatically updates the model parameters of the adaptability assessment module, such as the index weight coefficient, and the decision logic of the control command generation module based on the evaluation results, so as to continuously improve the system's response speed and control accuracy. Figure 3 The process of intelligent feedback and predictive optimization loop is given.

[0147] In summary, this invention collects and pre-processes parameters such as pH and turbidity of the effluent from the reclaimed water treatment system in real time using water quality sensors. It then combines an integrated target water quality standard database with the real-time needs of each cascade water-using unit to obtain water quality standards. A multi-index comprehensive evaluation algorithm is used to assess the water quality suitability level, and process parameters of bioreactors, membrane separation units, etc., as well as the reclaimed water distribution path and flow rate, are adjusted accordingly. This solves the problems in existing technologies where fluctuations in influent water quality lead to unstable effluent, reliance on fixed processes lacks dynamic response, and consequently, water quality risks in high-standard water-using units and over-treatment in low-standard water-using units. Simultaneously, through feedback optimization iterative models, historical data machine learning predictive control, and user interface visualization and manual intervention, the system's response speed and control accuracy are continuously improved, avoiding resource waste and effectively enhancing the efficiency and economy of cascaded reclaimed water utilization, thus achieving optimized cascaded utilization of reclaimed water.

Claims

1. A method for the cascade utilization of urban wastewater reclaimed water, characterized in that, include: S1. Obtain real-time water quality parameters of the effluent from the reclaimed water treatment system, including pH value, turbidity, chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). S2. Obtain the real-time water quality requirements or target water quality standards corresponding to each cascade water use unit, wherein each cascade water use unit includes industrial cooling, landscape environment, municipal miscellaneous use and farmland irrigation. S3. Based on the real-time water quality parameters and the real-time water quality requirements or target water quality standards, evaluate the water quality compatibility level between the reclaimed water effluent and each cascade water use unit using a preset water quality compatibility assessment model. S4. Generate dynamic control instructions based on the water quality suitability assessment level. The dynamic control instructions include adjusting the process parameters of the reclaimed water treatment system and controlling the distribution path and flow rate of the reclaimed water. S5. Execute the dynamic control command to dynamically match the water quality of reclaimed water with the real-time water quality requirements or target water quality standards of each cascade water use unit, thereby achieving optimized cascade utilization of reclaimed water.

2. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, The real-time water quality parameters of the effluent from the reclaimed water treatment system in step S1 include: By deploying multiple types of online water quality sensors on the effluent pipeline of the reclaimed water treatment system, real-time and continuous data on various water quality parameters such as pH, turbidity, COD, total nitrogen, and total phosphorus are collected. The collected water quality data is preprocessed, including data cleaning, calibration, and outlier detection, to obtain accurate and reliable real-time water quality parameters.

3. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, In step S2, obtaining the real-time water quality requirements or target water quality standards corresponding to each cascade water use unit includes: From the integrated target water quality standard database, based on the actual use, importance and historical water use characteristics of each water use unit, the corresponding preset target water quality standards are queried and obtained; It receives real-time water quality demand inputs from each cascade water use unit and dynamically uses them as the current target water quality standard to achieve flexible response on the demand side.

4. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, In step S3, a preset water quality compatibility assessment model is used to evaluate the water quality compatibility level between the reclaimed water effluent and each cascade water use unit, including: Using a multi-index comprehensive evaluation algorithm, real-time water quality parameters are compared with real-time water quality requirements or target water quality standards item by item. Based on the precise comparison results of various indicators, combined with the preset weighting coefficients and experience, the comprehensive water quality adaptability index is calculated. Based on the comprehensive water quality adaptability index and the preset threshold range, water quality adaptability is divided into several distinct levels, including "fully adapted", "basically adapted", "marginally adapted" and "not adapted". The specific process is as follows: The min-max normalization method was used to normalize the real-time water quality parameters and the target water quality standard. The normalization formula is as follows: Where, x′ ij Let x be the normalized value of the j-th water quality indicator in the i-th test. ij Let x be the original value of the j-th water quality indicator in the i-th test, min(x) j Let be the minimum value of the j-th water quality indicator in the historical monitoring data, and max(x) be the minimum value of the j-th water quality indicator. j ) represents the maximum value of the j-th water quality indicator in historical monitoring data; After normalization, a multi-index comprehensive evaluation algorithm is used to calculate the comprehensive water quality suitability index. The algorithm uses a weighted summation method, and the formula is as follows: Where I is the comprehensive water quality suitability index, n is the number of water quality indicators involved in the evaluation, and in this embodiment, n is 5, corresponding to pH value, turbidity, chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP), respectively. j Let y' be the weighting coefficient of the j-th water quality indicator, and the sum of the weighting coefficients of all indicators equals 1. j Let be the normalized value of the target water quality standard for the j-th water quality indicator; Finally, the water quality adaptability level is divided according to the comprehensive water quality adaptability index and the preset threshold range: when I ≤ 0.1, the level is "fully adaptable"; when 0.1 < I ≤ 0.3, the level is "basically adaptable"; when 0.3 < I ≤ 0.5, the level is "marginally adaptable"; when I > 0.5, the level is "not adaptable".

5. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, In step S4, adjusting the process parameters of the reclaimed water treatment system includes: If the water quality adaptability level is "not adaptable" or "marginally adaptable", at least one process unit in the reclaimed water treatment system is selectively adjusted according to the specific water quality indicators and deviation degrees causing insufficient adaptability. The process units include a bioreactor, a membrane separation unit, an advanced oxidation unit, and a disinfection unit; The adjustment of process parameters includes aeration volume, membrane flux, chemical dosage, reaction time, and ultraviolet irradiation intensity to make the reclaimed water effluent meet the target water quality requirements.

6. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, In step S4, regulating the distribution path and flow rate of reclaimed water includes: Based on the water quality adaptability assessment level, the priority order of each cascade water use unit, and the total current available reclaimed water volume, an initial distribution plan is generated; If the total volume of reclaimed water with good adaptability cannot meet the demands of all high-priority cascade water use units, the distribution flow rate of high-priority units is dynamically adjusted, and the remaining reclaimed water is allocated to lower-priority cascade water use units according to the water quality adaptability level to ensure the maximum effective utilization of water resources.

7. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, It also includes: After executing the dynamic regulation instruction, continuously and real-time obtaining the real-time water quality parameters of the effluent of the reclaimed water treatment system and the actual water quality data of each cascade water use unit; Comparing and analyzing the obtained actual water quality data in detail with the expected effect of the dynamic regulation instruction to evaluate the actual effectiveness of the dynamic regulation instruction; Based on the effectiveness evaluation result, real-time parameter update and iterative optimization are performed on the water quality adaptability assessment model and the dynamic regulation decision model to continuously improve the response speed and regulation accuracy of the system.

8. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, It also includes: Establishing and maintaining a historical operation database for storing key data in a long time series, including real-time water quality parameters, target water quality standards, water quality adaptability assessment levels, dynamic regulation instructions, and execution effects; Using historical operation data, through advanced machine learning algorithms for pattern recognition, trend analysis, and predictive analysis, predicting future water quality fluctuation trends and changes in water use demands of each cascade water use unit, so as to achieve intelligent predictive regulation of reclaimed water treatment and distribution.

9. The method for cascade utilization of urban wastewater reclaimed water according to claim 1, characterized in that, It also includes: Through an intuitive user interface, real-time providing a visual display of the operation status of the reclaimed water treatment system, the water quality adaptability status of each cascade water use unit, the execution process of the dynamic regulation instruction, and a detailed historical data report; The user interface also supports authorized users to perform manual intervention of parameters, strategy adjustment, or manual operation in case of emergencies to cope with sudden situations or specific management requirements.

10. A system for the cascade utilization of urban wastewater, used to apply the method for the cascade utilization of urban wastewater as described in any one of claims 1-9, characterized in that, It includes: A water quality monitoring module configured to obtain the real-time water quality parameters of the effluent of the reclaimed water treatment system and perform preprocessing; A demand acquisition module configured to obtain the real-time water quality demands or target water quality standards corresponding to each cascade water use unit; The compatibility assessment module is configured to assess the water quality compatibility level between the reclaimed water effluent and each cascade water use unit based on real-time water quality parameters and real-time water quality requirements or target water quality standards. The control instruction generation module is configured to generate dynamic control instructions based on the water quality adaptability assessment level. The dynamic control instructions include adjusting the process parameters of the reclaimed water treatment system, as well as controlling the distribution path and flow rate of the reclaimed water. The control execution module is configured to execute dynamic control commands; The feedback optimization module is configured to continuously acquire actual water quality data, evaluate the effectiveness of dynamic control commands, and perform real-time parameter updates and optimizations for the adaptability assessment module and the control command generation module.

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