Real-time regulation and control method for rainwater and sewage mixed connection point of urban drainage system based on simultaneous treatment of sewage and waterlogging
By constructing a precise drainage model and a three-level control strategy, and combining real-time monitoring data for dynamic regulation, the problems of pipe network overflow and pollution caused by mixed rainwater and sewage connections have been solved. This has achieved the goals of cost control, energy consumption optimization, and pollution prevention and control, and improved the operational efficiency and stability of the urban drainage system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-29
- Publication Date
- 2026-04-03
AI Technical Summary
The problem of overflow and pollution caused by the mixing of rainwater and sewage in urban drainage systems cannot be effectively regulated by traditional control methods, resulting in resource waste and environmental pollution.
By constructing a precise drainage model that incorporates cost and energy consumption parameters, combining multi-scenario rainfall simulation and a three-level control strategy, and using real-time monitoring data for dynamic regulation, the gate opening degree and opening/closing timing can be determined to achieve precise matching of different rainfall intensities and real-time changes.
It significantly reduces the operation and maintenance costs of drainage systems, improves the accuracy of regulation and the system's self-adaptability, prevents overflow and pollution risks, avoids resource waste, and delays investment in infrastructure expansion.
Smart Images
Figure CN121785173A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of smart water management and urban drainage technology, specifically to a real-time control method for the combined control of sewage and rainwater in urban drainage systems. Background Technology
[0002] Urban drainage systems are crucial infrastructure, but they have long suffered from the problem of "reconstruction over maintenance." This has resulted in drainage network management lagging behind urban development, leading to the failure to promptly detect issues such as pipe siltation, blockage, corrosion, leakage, damage, and deformation. Combined sewer overflows are a prominent problem in drainage systems, causing large amounts of rainwater to enter the sewage system through these points. This can easily lead to excessively high sewage levels, pump station overload, reduced efficiency of sewage treatment plants, and even environmental pollution incidents such as road overflows. Traditional control methods often involve constructing intercepting weirs in civil engineering, with fixed and unadjustable interception volumes. While sewage on sunny days and initial rainwater on rainy days are intercepted and flow into the sewage system, cleaner rainwater also enters later, causing insufficient sewage network capacity and overflows. This wastes the treatment capacity of sewage treatment plants and fails to effectively control pollution.
[0003] With the development of sensing and IoT technologies, an increasing number of online monitoring devices are being applied to urban drainage systems. These devices provide massive amounts of real-time data for the drainage system. Furthermore, with the widespread development and application of smart water management, it has become possible to achieve refined management and intelligent scheduling of the drainage system by integrating multi-dimensional monitoring data. Utilizing data-driven refined management and dynamic control, a method and system for "quantitative and qualitative synergistic" control of stormwater and sewage mixing points is provided to maximize the utilization of the pipe network's storage capacity and minimize environmental pollution risks. This offers a method and system capable of predicting in advance, accurately judging, and dynamically adjusting control strategies. Summary of the Invention
[0004] The purpose of this invention is to solve the technical problems mentioned above, and to propose a real-time control method for the combined stormwater and sewage connection points in urban drainage systems based on the integrated treatment of sewage and flooding, comprising the following steps: S1. Utilizing geophysical information of the drainage network within the study area, combined with GIS geographic information system data, pump station operation data, sewage treatment plant operation data and energy consumption data, daily maintenance cost data of the network, and sewage treatment cost data, and integrating existing water quality and liquid level monitoring data within the drainage unit, the model is calibrated and validated to enable the model to accurately simulate the time-series liquid level changes and water quality concentration changes of the network under different intensity rainfall events, as well as the energy consumption process and cost accounting results under the corresponding scenarios; S2. Based on the local rainstorm intensity formula and the Chicago rain pattern, design rainfall scenarios with different total rainfall are generated. The calibrated drainage model is used to simulate the changes in liquid level, water quality, energy consumption and cost of the inspection wells near the mixing point under each rainfall scenario. The dynamic adjustable storage space of the sewage pipe network downstream of the mixing point is statistically analyzed, the overflow situation and related parameters are analyzed, and the safety threshold and overflow threshold are defined. S3. Develop a three-level control strategy based on the safety threshold and the overflow threshold, incorporating the goals of optimal energy consumption and controllable cost in the strategy development process; S4. Obtain high-precision quantitative rainfall forecast data and real-time monitoring data for a specific future period, start the real-time dynamic control mode, and combine energy consumption monitoring data and cost accounting data to correct the forecast results and dynamically decide the gate opening degree or opening and closing timing. S5. Receive real-time data from level gauges, water quality monitoring equipment, and energy consumption monitoring, and establish mandatory control rules that include exceeding level limits, water quality deterioration, and exceeding energy consumption limits.
[0005] In the preferred embodiment, the cost parameters in step S1 include the cost of daily pipeline inspection and maintenance, pipeline dredging, pump station operation electricity, wastewater treatment plant chemical consumption, and sludge disposal.
[0006] In the preferred embodiment, the energy consumption parameters in step S1 are calculated based on the rated power of the pump station motor, the running time, the power and operating frequency of the gate drive device, and the energy consumption of the aeration system and the booster pump of the sewage treatment plant.
[0007] In the preferred scheme, during the multi-scenario rainfall simulation in step S2, the unit water volume treatment energy consumption, total energy consumption and total cost of the drainage system under different rainfall scenarios are analyzed simultaneously, and the threshold values of P1 and P2 are optimized in combination with the overflow risk assessment results.
[0008] In the preferred scheme, in the three-level control strategy of step S3, the second-level strategy selects the closing time node with the smallest energy consumption increment when determining the gate closing time based on the energy consumption change trend of the pumping station; the third-level strategy calculates the short-term operating costs under different opening and closing states simultaneously when judging the gate opening and closing status based on water quality, and prioritizes the control method with the best cost and meeting the pollution control requirements.
[0009] In the preferred embodiment, in the real-time dynamic control of step S4, the deviation between the real-time energy consumption data and the preset energy consumption benchmark value, and the deviation between the real-time cost accounting value and the budgeted cost are used as model correction factors to dynamically adjust the gate control command.
[0010] In the preferred embodiment, the mandatory control rule in step S5 is added as follows: when the real-time energy consumption of the drainage system is detected to exceed 120% of the preset energy consumption threshold, the system automatically starts the energy consumption optimization mode, adjusts the gate opening without causing the risk of overflow, and reduces the operating load of the pumping station and related equipment.
[0011] In the preferred embodiment, the water quality indicators involved in steps S1 and S3 are one or more combinations of chemical oxygen demand, ammonia nitrogen, total suspended solids, or conductivity.
[0012] In the preferred embodiment, the criteria for determining the calibration and verification of model parameters in step S1 are as follows: the relative error between the simulated liquid level value and the measured value is ≤10%, the relative error between the simulated water concentration value and the measured value is ≤15%, the relative error between the simulated energy consumption value and the measured value is ≤8%, and the relative error between the cost accounting result and the actual statistical value is ≤12%.
[0013] In the preferred embodiment, the gate opening adjustment accuracy in step S4 is 0.5%-1%, and the opening and closing speed is controlled according to the energy consumption optimization target during the gate opening and closing process, with the opening and closing time controlled within the range of 30s-60s.
[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Based on solving the core problems of pipe network overflow and initial rain pollution caused by mixed rainwater and sewage, by integrating cost parameters such as pipe network maintenance, pump station operation, sewage treatment, and equipment energy consumption data into the drainage model and control strategy, the goals of pollution prevention and control, energy consumption optimization and cost control can be achieved, significantly reducing the daily operation and maintenance costs of the drainage system and avoiding resource waste.
[0015] (2) Based on the critical threshold and three-level classification strategy defined by multi-scenario rainfall simulation, and combined with real-time rainfall forecast, liquid level, water quality, energy consumption and other multi-dimensional data for rolling correction, the gate control can accurately match different rainfall intensity scenarios and dynamically respond to real-time changes in energy consumption and cost, effectively cope with rainfall uncertainty, and significantly improve the control accuracy and system self-adaptability.
[0016] (3) Based on the existing emergency mandatory control for excessive liquid level and water quality deterioration, new emergency rules for excessive energy consumption are added to form a prevention and control system for the risks of overflow, water pollution and excessive energy consumption. Through closed-loop control logic, the system can respond quickly in the event of extreme rainfall, sudden water quality deterioration or abnormal energy consumption, minimize environmental and operational risks, and ensure the stable operation of the drainage system.
[0017] (4) By using refined model simulation and dynamic control, the storage and transportation potential of the existing sewage pipe network can be fully explored. At the same time, the control strategy is optimized with the goal of optimal cost and energy consumption. Without the need for large-scale expansion of pipe networks, pumping stations and other civil engineering projects, the dual needs of pollution prevention and control and efficient system operation can be met, significantly delaying infrastructure expansion investment and providing effective support for the "low-cost and high-quality" operation and maintenance of urban drainage systems. Attached Figure Description
[0018] Figure 1This is a flowchart of a real-time control method for the combined treatment of sewage and rainwater in urban drainage systems. Detailed Implementation
[0019] Example 1 This embodiment provides a real-time control method for the combined stormwater and sewage connection points in urban drainage systems based on the integrated treatment of sewage and flooding. Figure 1 As shown, it includes the following steps: S1. Construct a precise drainage model incorporating cost and energy consumption parameters: Utilize geophysical information such as the topology, pipe diameter, and pipe material of the drainage network within the study area, combined with GIS geographic information system data, pump station operation data, sewage treatment plant operation data and energy consumption data, daily maintenance cost data of the network, and sewage treatment cost data. Integrate existing water quality and liquid level monitoring data within the drainage unit to calibrate and validate the model. This will enable the model to accurately simulate the temporal changes in liquid level and water concentration in the network under different intensities of rainfall events, as well as the energy consumption process and cost accounting results under the corresponding scenarios. S2. Multi-scenario rainfall simulation and critical rainfall value definition: Based on the local rainstorm intensity formula and the Chicago rain pattern, design rainfall scenarios with different total rainfall are generated. The calibrated drainage model is used to simulate the changes in liquid level, water quality, energy consumption and cost of the inspection wells near the mixing point under each rainfall scenario. The dynamic adjustable storage space of the sewage pipe network downstream of the mixing point is statistically analyzed, the overflow situation and related parameters are analyzed, and the safety threshold P1 and overflow threshold P2 are defined. S3. Develop a hierarchical early warning and control strategy library: Develop three-level control strategies based on P1 and P2, incorporating the goals of optimal energy consumption and controllable cost during the strategy development process; S4. Real-time forecasting and dynamic control: Acquire high-precision quantitative rainfall forecast data and real-time monitoring data for the next 0-2 hours, start the real-time dynamic control mode, and combine energy consumption monitoring data and cost accounting data to correct the forecast results and dynamically decide the gate opening degree or opening and closing timing. S5. Safety Redundancy and Emergency Mandatory Control: Receives real-time data from level gauges, water quality monitoring equipment, and energy consumption monitoring, and establishes mandatory control rules including those for exceeding level limits, water quality deterioration, and exceeding energy consumption limits.
[0020] The local rainstorm intensity formula is derived from statistical analysis of long-term local meteorological observation data. It is used to calculate the rainstorm intensity under a specific rainfall recurrence period and duration. It is a core formula for urban drainage system design and rainfall scenario simulation. Specifically: ; or ; in, The intensity of the rainstorm, The two can be correlated through unit conversion, representing rainfall intensity.
[0021] Design rainfall scenarios for different rainfall amounts: by adjusting the return period and duration of rainfall It can calculate the intensity of rainstorms under different combinations, and then deduce the total rainfall, providing a quantitative basis for rainfall input for multi-scenario simulation.
[0022] The Chicago rainfall pattern is an asymmetric design rainfall time-history distribution pattern. Its core characteristic is an asymmetric distribution of rainfall intensity over time, characterized by an initial increase followed by a decrease. It exhibits a distinct rainfall peak, the location of which can be flexibly adjusted to better reflect the actual temporal patterns of urban rainfall. Actual rainfall rarely shows a uniform distribution; it is more often an asymmetric process where the peak is concentrated in a specific period.
[0023] A single rainfall event is divided into an "rising phase" and a "falling phase." The rising phase is short and its intensity increases rapidly, while the falling phase is longer and its intensity decreases gradually. Key parameters include: Peak value factor: The ratio of the time of peak rainfall to the total duration of rainfall; Peak intensity: The maximum instantaneous intensity during a rainfall event; Time-history allocation calculation: The peak intensity is allocated to each period of the rainfall duration using a specific formula, generating a time-by-time rainfall intensity sequence, and finally forming a complete rainfall time-history curve.
[0024] When used in conjunction with local rainstorm intensity formulas: Rainstorm intensity formulas only provide quantitative data on total intensity and total duration, while the Chicago Rain Pattern transforms these data into "time-by-time changing rainfall processes" through time-history allocation, enabling drainage models to simulate the temporal dynamic changes in pipe network liquid level, water quality, and energy consumption during rainfall, which is more consistent with the response patterns of actual drainage systems.
[0025] Local rainstorm intensity formulas determine rainfall intensity levels, providing a quantitative benchmark for rainfall scenarios. Chicago rain patterns determine the temporal distribution of rainfall, providing temporal details for rainfall scenarios. By combining these two methods, multiple sets of design rainfall scenarios with different total rainfall amounts, intensity levels, and temporal distributions can be generated. This ensures that subsequent drainage models can comprehensively simulate system responses under various scenarios, including light rain, moderate rain, heavy rain, and rainstorms, providing sufficient data support for defining the safety threshold P1 and the overflow threshold P2.
[0026] Preferably, the cost parameters in step S1 include the cost of daily inspection and maintenance of the pipeline network, the cost of pipeline dredging, the cost of electricity for pump station operation, the cost of chemical consumption at the sewage treatment plant, and the cost of sludge disposal.
[0027] Preferably, the energy consumption parameters in step S1 are calculated based on the rated power of the pump station motor, the running time, the power and operating frequency of the gate drive device, the energy consumption of the sewage treatment plant aeration system, and the energy consumption of the booster pump.
[0028] Preferably, in step S2, during the multi-scenario rainfall simulation, the unit water volume treatment energy consumption, total energy consumption, and total cost of the drainage system under different rainfall scenarios are analyzed simultaneously, and the threshold values of P1 and P2 are optimized in combination with the overflow risk assessment results.
[0029] Preferably, in the three-level control strategy of step S3, the second-level strategy selects the closing time node with the smallest energy consumption increment when determining the gate closing time based on the energy consumption change trend of the pumping station; the third-level strategy calculates the short-term operating costs under different opening and closing states simultaneously when judging the gate opening and closing status based on water quality, and prioritizes the control method with the best cost and that meets the pollution control requirements.
[0030] Preferably, in the real-time dynamic control of step S4, the deviation between the real-time energy consumption data and the preset energy consumption benchmark value, and the deviation between the real-time cost accounting value and the budgeted cost are used as model correction factors to dynamically adjust the gate control command.
[0031] Preferably, the mandatory control rule in step S5 is added as follows: when the real-time energy consumption of the drainage system is detected to exceed 120% of the preset energy consumption threshold, the system automatically starts the energy consumption optimization mode, adjusts the gate opening without causing the risk of overflow, and reduces the operating load of the pumping station and related equipment.
[0032] Preferably, the water quality indicators involved in steps S1 and S3 are one or more combinations of chemical oxygen demand, ammonia nitrogen, total suspended solids, or conductivity.
[0033] Preferably, the criteria for determining the calibration and verification of model parameters in step S1 are: the relative error between the simulated liquid level value and the measured value is ≤10%, the relative error between the simulated water concentration value and the measured value is ≤15%, the relative error between the simulated energy consumption value and the measured value is ≤8%, and the relative error between the cost accounting result and the actual statistical value is ≤12%.
[0034] Preferably, in step S4, the gate opening adjustment accuracy is 0.5%-1%, and the opening and closing speed is controlled according to the energy consumption optimization target during the gate opening and closing process, with the opening and closing time controlled within the range of 30s-60s.
[0035] Example 2 This embodiment is applied to the drainage system of an old urban area. The pipe network in this area is old, with significant issues of combined sewer overflows and limited storage capacity. Therefore, it is urgent to achieve integrated sewage and flood control and low-cost operation and maintenance through refined regulation. The following details the implementation process, including core steps and key issues: 1. Construction of a precise drainage model: The model construction focuses on the integration of data across all dimensions and the calibration of parameters with high precision. First, geophysical information such as the topology, pipe diameter, and pipe material of the 320-kilometer drainage pipe network in the study area is collected using professional pipeline inspection equipment. Simultaneously, data such as the spatial location of the pipe network, topographic elevation, and catchment area from the GIS geographic information system are integrated. In terms of operational data, the system accesses real-time data such as start-up and shutdown records, motor rated power, and operating time of three pumping stations, as well as data on daily treatment capacity, chemical dosage, aeration system operating parameters, and booster pump energy consumption of one wastewater treatment plant. Cost parameters are detailed as follows: per capita labor cost and annual coverage frequency calculation for daily pipeline inspection and maintenance; dredging cost graded according to pipeline length and siltation level; electricity cost of pumping stations calculated based on peak and off-peak electricity prices; unit water consumption and purchase price of chemical consumption (PAC, PAM) at the wastewater treatment plant; and ton cost of sludge dewatering and disposal. Energy consumption parameters are accurately calculated based on the product of pumping station motor rated power and actual operating time, gate drive device power and daily opening and closing frequency statistics, and the air-to-water ratio of the wastewater treatment plant's aeration system and booster pump operating load. Based on this, real-time water quality data of chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and total suspended solids (TSS) from 28 monitoring points within the drainage unit, as well as liquid level monitoring data from 15 key inspection wells, were integrated, and the model was calibrated and validated using a stepwise calibration method. During the calibration process, the relative error between the simulated and measured values of liquid level is strictly controlled to ≤10%. This standard stems from the measurement accuracy of the liquid level monitoring equipment and the simulation requirements of the hydraulic characteristics of the pipeline network, ensuring accurate capture of changes in pipeline water level. The relative error of the simulated water quality concentration is ≤15%. Due to the influence of multiple factors such as rainfall dilution and pollutant degradation on water quality indicators, there is some interference during the monitoring process. Referring to the calibration practice of similar models in the industry, the error threshold is relaxed, while meeting the judgment requirements for pollution prevention and control. The relative error of the simulated energy consumption is ≤8%. This is due to the fact that energy consumption data of pumping stations and sewage treatment plants can be directly collected through electricity meters and sensors, resulting in high data accuracy, and the energy consumption calculation model has strong single-variable characteristics. The relative error of the cost accounting results is ≤12%. Since costs involve multiple fluctuating factors such as labor, materials, and electricity prices, they need to be allocated and calibrated in the statistical accounting. This threshold not only ensures the effectiveness of cost control but also accommodates reasonable deviations in actual accounting, ultimately enabling the model to accurately replicate the changes in pipeline hydraulics and water quality under different rainfall intensities, as well as the corresponding energy consumption and cost processes.
[0036] 2. Multi-scenario rainfall simulation and critical threshold definition: Based on local rainfall intensity formulas and the Chicago rainfall pattern, 12 design rainfall scenarios were generated, with total rainfall ranging from 10mm to 150mm and duration from 30min to 180min, covering different intensity levels such as light rain, moderate rain, heavy rain, and rainstorms. Using a calibrated, precise drainage model, the changes in liquid level, water quality, energy consumption, and cost near the connection point were simulated under each scenario. Simultaneously, the dynamic adjustable storage capacity of the downstream sewage network at the connection point was statistically analyzed, and the frequency of overflows and the extent of pollution diffusion under different scenarios were examined.
[0037] There are significant interrelationships among liquid level, water quality, energy consumption, and cost, providing a crucial reference for anomaly analysis: When rainfall intensity increases, a large influx of rainwater into the pipe network causes a rapid rise in liquid level. On the one hand, this dilutes the concentration of pollutants in the sewage, lowering water quality indicators. On the other hand, the increased liquid level increases the boosting pressure of the pumping station, leading to a greater operating load and a significant increase in energy consumption, which in turn drives up electricity costs. If the liquid level is close to full capacity, the pumping station must continue to operate at full capacity to prevent overflow, reaching peak energy consumption and costs. Once an overflow occurs, although energy consumption may decrease slightly in the short term, it will cause water pollution, requiring additional pollution control costs, thus forming a trade-off between "energy consumption, cost, and pollution." Furthermore, if water quality indicators rise abnormally but the liquid level does not rise significantly, it can be determined that the pollution is concentrated in a localized area of the pipe network, rather than a mixing problem caused by rainfall, providing a basis for accurate fault diagnosis.
[0038] The synchronous analysis process centers on data linkage acquisition and multi-dimensional correlation analysis. In each rainfall scenario simulation, energy consumption per unit volume of water treated, total energy consumption, total cost, and overflow risk value are recorded synchronously. The controlled variable method is used to fix the rainfall duration, and the changing patterns of the four indicators under different total rainfall amounts are analyzed. Then, the total rainfall is fixed, and the impact of rainfall duration on the indicators is studied. By plotting energy consumption-overflow risk scatter plots and cost-rainfall intensity curves, extreme abnormal data caused by instantaneous equipment failures are eliminated, and the Pearson correlation coefficients between the indicators are calculated. Finally, combined with the pollution prevention and control requirements of the urban drainage system, energy consumption control targets, and cost budget limits, the safety threshold P and overflow threshold P2 are optimized and defined.
[0039] 3. Development of a tiered early warning and control strategy library: Based on the safety threshold P1 and the overflow threshold P2, a three-level control strategy library is constructed, integrating the objectives of optimal energy consumption and controllable cost. The first-level strategy, for scenarios where total rainfall is ≤ P1, keeps the gates open while fine-tuning the gate opening based on real-time energy consumption data to ensure the pump station's operating energy consumption remains near the baseline value. The second-level strategy, applicable to scenarios where total rainfall is between P1 and P2, determines the gate closing time by real-time monitoring of pump station energy consumption trends, plotting an energy consumption increment curve, and selecting the time node with the smallest curve slope to close part of the gates, avoiding a sudden increase in pump station load due to gate closure and reducing energy waste. The third-level strategy, for high-risk scenarios where total rainfall is ≥ P2, determines the gate opening / closing status based on water quality monitoring data, while simultaneously calculating the short-term operating costs under different opening / closing states. Under the premise of meeting the emission standards for pollutants such as COD and NH3-N, the strategy prioritizes the most cost-effective control method. For example, when water concentration is low, the gates are moderately opened to divert some rainwater, reducing the cost of pump station boosting and sewage treatment.
[0040] 4. Real-time forecasting and dynamic control: High-precision quantitative rainfall forecast data for the next 0-2 hours is obtained through the urban meteorological early warning platform. Simultaneously, real-time liquid level, water quality, energy consumption, and cost data from various monitoring points are collected to initiate a real-time dynamic control mode. Deviations between real-time energy consumption data and preset energy consumption benchmarks, as well as deviations between real-time cost calculations and budgeted costs, are used as model correction factors. These factors are substituted into the precise drainage model to adjust prediction parameters and dynamically determine the gate opening or timing, ensuring that the gate opening adjustment accuracy is controlled within 0.5%-1%, meeting the needs of refined regulation.
[0041] The gate opening and closing speed control is centered on energy consumption optimization and dynamically adjusted in conjunction with real-time energy consumption status: when the real-time energy consumption is lower than the preset benchmark value, the opening and closing speed can be appropriately accelerated, and the opening and closing time can be controlled within the range of 30s-40s to improve the response efficiency to changes in rainfall; when the real-time energy consumption is close to or higher than the preset benchmark value, a smooth opening and closing mode is adopted, and the opening and closing time is extended to 40s-60s to avoid the instantaneous load surge of the equipment caused by the rapid start and stop of the gate, resulting in energy consumption peaks; if the real-time energy consumption is already at a high level, the opening and closing speed is further slowed down to prioritize energy consumption stability and then take into account the liquid level control requirements. Through this "energy consumption-speed" linkage regulation, energy consumption is minimized while ensuring drainage safety.
[0042] 5. Safety redundancy and emergency mandatory control: A three-dimensional mandatory control rule system is constructed, which includes liquid level exceeding limit, water quality deterioration, and energy consumption exceeding limit, and real-time feedback is received from liquid level gauges, water quality monitoring equipment, and energy consumption monitoring data. When the monitored liquid level exceeds 95% of the pipeline network design water level, all standby gates are immediately opened for diversion; when the water quality index suddenly rises to above 500 mg / L, the relevant mixing point gates are closed to prevent high-concentration pollutants from entering the sewage treatment plant; in the newly added mandatory control rules for excessive energy consumption, 120% is set as the energy consumption threshold ratio. The selection of this value is based on the dual requirements of equipment operation safety and energy consumption optimization: through statistical analysis of long-term operating data of equipment such as pump stations and sewage treatment plants, it was found that the equipment can maintain a stable working state when operating below 120% of the rated energy consumption, and the failure rate is less than 0.5%; if this ratio is exceeded, the equipment load is too large, which not only significantly reduces energy efficiency, but may also lead to failures such as motor overheating and pipeline pressure exceeding the standard. At the same time, a 20% adjustment margin is reserved, which can reduce the equipment operating load by adjusting the gate opening without causing the risk of overflow, ensuring that the system achieves a balance between energy consumption and safety. When the real-time energy consumption of the drainage system exceeds 120% of the preset energy consumption threshold, the system automatically starts the energy consumption optimization mode. Through a precise drainage model, it simulates the liquid level changes under different gate openings. Under the premise of ensuring that the liquid level does not exceed the critical water level corresponding to P2 and does not cause the risk of overflow, it gradually adjusts the gate opening, reduces the pump station operating frequency and the aeration intensity of the sewage treatment plant, until the energy consumption returns to the threshold range.
[0043] This embodiment achieves the comprehensive goals of pollution prevention and control, energy consumption optimization, and cost control through multi-dimensional data integration, refined model simulation, hierarchical dynamic control, and three-dimensional emergency prevention and control. While ensuring that no overflow pollution incidents occurred in the drainage system of this old urban area, the energy consumption of the pumping station was reduced by 18%, and the average daily operation and maintenance cost of the drainage system was reduced by 22%. It fully tapped the regulation and operation potential of the existing pipeline network facilities, and met the city's drainage needs without the need for additional civil engineering projects. It provides a practical and feasible reference for the refined and low-cost operation and maintenance of drainage systems in similar old urban areas.
[0044] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A real-time control method for the combined stormwater and sewage connection point in an urban drainage system based on integrated sewage and flood control, characterized in that, Includes the following steps: S1. Utilizing geophysical information of the drainage network within the study area, combined with GIS geographic information system data, pump station operation data, sewage treatment plant operation data and energy consumption data, daily maintenance cost data of the network, and sewage treatment cost data, and integrating existing water quality and liquid level monitoring data within the drainage unit, the model is calibrated and validated to enable the model to accurately simulate the time-series liquid level changes and water quality concentration changes of the network under different intensity rainfall events, as well as the energy consumption process and cost accounting results under the corresponding scenarios; S2. Based on the local rainstorm intensity formula and the Chicago rain pattern, design rainfall scenarios with different total rainfall are generated. The calibrated drainage model is used to simulate the changes in liquid level, water quality, energy consumption and cost of the inspection wells near the mixing point under each rainfall scenario. The dynamic adjustable storage space of the sewage pipe network downstream of the mixing point is statistically analyzed, the overflow situation and related parameters are analyzed, and the safety threshold and overflow threshold are defined. S3. Develop a three-level control strategy based on the safety threshold and the overflow threshold, incorporating the goals of optimal energy consumption and controllable cost in the strategy development process; S4. Obtain high-precision quantitative rainfall forecast data and real-time monitoring data for a specific future period, start the real-time dynamic control mode, and combine energy consumption monitoring data and cost accounting data to correct the forecast results and dynamically decide the gate opening degree or opening and closing timing. S5. Receive real-time data from level gauges, water quality monitoring equipment, and energy consumption monitoring, and establish mandatory control rules that include exceeding level limits, water quality deterioration, and exceeding energy consumption limits.
2. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... The cost parameters in step S1 include the cost of daily inspection and maintenance of the pipeline network, the cost of pipeline dredging, the cost of electricity for pump station operation, the cost of chemical consumption at the sewage treatment plant, and the cost of sludge disposal.
3. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... The energy consumption parameters in step S1 are calculated based on the rated power of the pump station motor, the running time, the power and operating frequency of the gate drive device, the energy consumption of the sewage treatment plant aeration system, and the energy consumption of the booster pump.
4. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... In step S2, during the multi-scenario rainfall simulation, the unit water volume treatment energy consumption, total energy consumption, and total cost of the drainage system under different rainfall scenarios are analyzed simultaneously, and the threshold values of P1 and P2 are optimized based on the overflow risk assessment results.
5. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... In the three-level control strategy of step S3, the second-level strategy selects the closing time node with the smallest energy consumption increment when determining the gate closing time based on the energy consumption change trend of the pumping station; the third-level strategy calculates the short-term operating costs under different opening and closing states simultaneously when judging the gate opening and closing status based on water quality, and prioritizes the control method with the best cost and that meets the pollution control requirements.
6. The real-time control method for combined sewer and stormwater connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... In the real-time dynamic control of step S4, the deviation between real-time energy consumption data and preset energy consumption benchmark value, and the deviation between real-time cost accounting value and budgeted cost are used as model correction factors to dynamically adjust the gate control command.
7. The real-time control method for combined sewer and stormwater connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... The mandatory control rule for step S5 is as follows: When the real-time energy consumption of the drainage system is detected to exceed 120% of the preset energy consumption threshold, the system will automatically start the energy consumption optimization mode to adjust the gate opening and reduce the operating load of the pumping station and related equipment without causing the risk of overflow.
8. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... The water quality indicators involved in steps S1 and S3 are one or more combinations of chemical oxygen demand, ammonia nitrogen, total suspended solids, or conductivity.
9. The real-time control method for combined sewer and stormwater connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... The criteria for model parameter calibration and verification in step S1 are as follows: the relative error between the simulated liquid level value and the measured value is ≤10%, the relative error between the simulated water concentration value and the measured value is ≤15%, the relative error between the simulated energy consumption value and the measured value is ≤8%, and the relative error between the cost accounting result and the actual statistical value is ≤12%.
10. The real-time control method for combined stormwater and sewage connection points in urban drainage systems based on integrated sewage and flood control, as described in claim 1, is characterized in that... In step S4, the gate opening adjustment accuracy is 0.5%-1%, and the opening and closing speed is controlled according to the energy consumption optimization target during the gate opening and closing process, with the opening and closing time controlled within the range of 30s-60s.