A remote control method and system for a smart pump station, a medium and a product

Abstract

A remote control method and system of a smart pump station, a medium and a product, wherein the method comprises: acquiring running state data of each first water pump in a target pump station, a water pump flow-efficiency characteristic curve, drainage state data of each second water pump in an upstream pump station of the target pump station, and precipitation prediction data of an area where the target pump station is located within a preset time period; calculating a basic flow rate demand value of the target pump station; determining a target water pump start-stop combination; calculating a lift demand value based on water outlet pipe network pressure data, and determining a single pump flow rate demand value of each running water pump in the target water pump start-stop combination based on the basic flow rate demand value; calculating a reference running frequency of each running water pump; calculating a target running frequency of the running water pump; generating a control instruction of the running water pump based on the target running frequency, and controlling the running water pump to execute the control instruction. The application can improve the running efficiency of the pump station.

Description

Technical Field

[0001] This application relates to the field of remote control technology, specifically to a remote control method, system, medium, and product for a smart pumping station. Background Technology

[0002] With the acceleration of urbanization, municipal drainage pumping stations are playing an increasingly important role in urban flood control and disaster reduction. Modern pumping station systems typically consist of multiple pumps and are equipped with automated devices such as level sensors and pressure sensors, achieving basic automated control.

[0003] In existing technologies, pump station control systems generally adopt a start-stop control scheme based on liquid level thresholds. This scheme sets liquid level thresholds for pump start-stop; when the liquid level in the collection tank exceeds the start-up level, the pump is turned on, and when the liquid level falls below the stop level, the pump is turned off. This often involves a fixed pump start-stop sequence and a fixed operating frequency for pump control.

[0004] However, in actual operation, due to the uncertainty of rainfall and the changing drainage conditions of upstream pumping stations, relying solely on fixed start-up and shutdown strategies is insufficient to cope with complex and ever-changing operating conditions. Especially under extreme weather conditions such as heavy rain, pumping stations often experience excessively high dispatching energy consumption, thereby reducing their operating efficiency. Summary of the Invention

[0005] This application provides a remote control method, system, medium, and product for intelligent pumping stations, which solves the problem that fixed start-stop strategies are difficult to cope with complex and variable operating conditions, thereby improving the operating efficiency of pumping stations.

[0006] The first aspect of this application provides a remote control method for a smart pumping station, the method comprising: The system acquires the operating status data and flow-efficiency characteristic curve of each first pump in the target pumping station, the drainage status data of each second pump in the upstream pumping station of the target pumping station, and the precipitation forecast data of the area where the target pumping station is located within a preset time period. The operating status data includes the water level value of the collection tank and the pressure data of the outlet pipeline network. Calculate the level deviation between the water level in the collection tank and the preset target level in each of the multiple consecutive preset time periods, and calculate the basic flow rate requirement of the target pumping station based on the level deviation. The target pump start-stop combination is determined based on the basic flow rate requirement and the flow-efficiency characteristic curve of each of the first water pumps. Calculate the required head value based on the pressure data of the water outlet network; Based on the aforementioned basic flow rate requirement, the single-pump flow rate requirement for each operating pump in the target pump start-stop combination is determined. Based on the single pump flow requirement and the head requirement, calculate the reference operating frequency of each of the operating pumps; The target operating frequency of the operating water pump is calculated based on the baseline operating frequency, the drainage status data, and the precipitation trend prediction data. Based on the target operating frequency, control commands are generated for the operating water pump, and the operating water pump is controlled to execute the control commands.

[0007] Optionally, the basic flow rate requirement of the target pumping station is calculated based on the liquid level deviation value, specifically including: The rate of change of liquid level between any two adjacent preset time periods is calculated based on the liquid level deviation value. If the absolute value of the liquid level change rate is greater than the preset disturbance judgment threshold, the current state is determined as a suspected disturbance state, and the predicted disturbance time period is determined based on the difference between the liquid level change rate and the preset disturbance judgment threshold. If, during the predicted disturbance period, the rate of change of the liquid level changes from a positive value to a negative value, and the absolute value of the negative rate is greater than a preset amplitude change threshold, then a liquid level pulse disturbance event is confirmed to have occurred. In this case, the peak liquid level within the predicted disturbance period is removed, and data is completed for the removed position based on a preset data completion rule. Calculate the average liquid level after data completion within the predicted disturbance time period, calculate the difference between the average liquid level and the preset target liquid level, and calculate the basic flow rate requirement based on the difference and the preset proportional-integral control algorithm.

[0008] Optionally, the target pump start-up and shutdown combination is determined based on the basic flow rate requirement and the flow-efficiency characteristic curve of each of the first pumps, specifically including: The efficiency deviation of the first water pump is calculated based on the actual operating efficiency in the operating status data of the first water pump and the flow-efficiency characteristic curve corresponding to the first water pump. The first water pump whose efficiency deviation is greater than the preset efficiency fluctuation threshold is identified as a performance fluctuation water pump, and the first water pump whose efficiency deviation is less than or equal to the preset efficiency fluctuation threshold is identified as a normal performance water pump. The rated flow rate of the water pump with normal performance is determined as the effective flow rate of the water pump with normal performance. The efficiency attenuation coefficient of the performance-fluctuating water pump is calculated based on the efficiency deviation corresponding to the performance-fluctuating water pump. The product of the rated flow rate and the efficiency attenuation coefficient is determined as the effective flow rate of the performance fluctuation pump; The target pump start / stop combination is determined based on the effective flow rate.

[0009] Optionally, determining the target pump start-stop combination based on the effective flow rate specifically includes: All the first water pumps are sorted from largest to smallest according to their effective flow rate to obtain a dynamic performance ranking list; Starting from the first first pump in the dynamic performance ranking list, the effective flow rate of each first pump is accumulated one by one until the total effective flow rate after accumulation is greater than or equal to the basic flow rate requirement value for the first time. Then, all the first pumps included in the accumulation process are identified as the running pumps in the target pump start-stop combination, and all the first pumps other than the running pumps are identified as the stopped pumps.

[0010] Optionally, the target operating frequency of the operating water pump is calculated based on the baseline operating frequency, the drainage status data, and the precipitation trend prediction data, specifically including: The predicted lag time for the upstream water to reach the target pumping station is calculated based on the drainage status data of the upstream pumping station. Within a preset time period before the lag time point, the predicted total inflow volume within the preset time period is calculated based on the drainage status data and the precipitation trend prediction data. Monitor the remaining capacity of the water collection tank of the target pumping station. When the remaining capacity of the water collection tank is less than the predicted total inflow, the difference between the predicted total inflow and the remaining capacity of the water collection tank is determined as the buffer demand. The target operating frequency of each operating water pump is calculated based on the baseline operating frequency and the required water volume of the buffer.

[0011] Optionally, within a preset time period before the lag time point, based on the drainage status data and the precipitation trend prediction data, the predicted total inflow volume within the preset time period is calculated, specifically including: The drainage flow rate data within the preset time period is determined as the basic inflow rate; Based on the precipitation trend prediction data, the predicted precipitation within the preset time period is calculated, and the product of the predicted precipitation and the preset water collection coefficient is determined as the precipitation inflow. The sum of the baseline inflow and the precipitation inflow is determined as the predicted total inflow.

[0012] Optionally, the target operating frequency of each operating pump is calculated based on the baseline operating frequency and the required buffer water volume, specifically including: Calculate the ratio of the buffer water demand to the preset duration to obtain the pre-increased flow demand; Calculate the ratio of the pre-increased flow demand to the single pump flow demand value to obtain the flow regulation coefficient; The sum of one and the flow rate regulation coefficient is determined as the frequency regulation factor; When the frequency adjustment factor is less than the preset upper limit threshold for frequency adjustment and greater than the preset lower limit threshold for frequency adjustment, the product of the reference operating frequency and the frequency adjustment factor is determined as the target operating frequency. When the frequency adjustment factor is greater than or equal to the preset frequency adjustment upper limit threshold, the product of the preset frequency adjustment upper limit threshold and the reference operating frequency is determined as the target operating frequency; When the frequency adjustment factor is less than or equal to the preset lower limit threshold, the product of the preset lower limit threshold and the reference operating frequency is determined as the target operating frequency.

[0013] Secondly, embodiments of this application provide a remote control system for a smart pumping station. The remote control system for the smart pumping station includes: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the remote control system of the smart pumping station to perform the method described in the first aspect and any possible implementation thereof.

[0014] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a remote control system of a smart pumping station, cause the remote control system of the smart pumping station to perform the method described in the first aspect and any possible implementation thereof.

[0015] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on the remote control system of a smart pumping station, cause the remote control system of the smart pumping station to execute the method described in the first aspect and any possible implementation thereof. In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. By employing a method that integrates the operating status data of the target pumping station, the pump flow-efficiency characteristic curve, the drainage status data of the upstream pumping station, and precipitation forecast data, the system can comprehensively acquire current and predicted operating condition information. Based on the liquid level deviation in the collection tank, it dynamically calculates the basic flow velocity requirement and, combined with the efficiency characteristics of each pump, determines the optimal start-stop combination and baseline operating frequency to meet this requirement, ensuring that the pumps always operate within the high-efficiency range. Simultaneously, by combining this frequency with upstream inflow and precipitation trends, it further predicts and adjusts the target operating frequency, achieving feedforward control of the pump operation strategy. Through this process, it effectively overcomes the problems of rigid scheduling and excessive energy consumption associated with traditional fixed threshold control when dealing with complex operating conditions. 2. By employing a method that calculates the rate of change of liquid level between adjacent preset time periods based on the liquid level deviation value, and identifies suspected disturbance states when the rate of change exceeds a preset disturbance judgment threshold, the predicted disturbance time period is further determined. Within this time period, liquid level rate reversal and amplitude changes are detected to confirm liquid level pulse disturbance events, thereby eliminating abnormal liquid level peaks and restoring data continuity through data completion rules. Finally, under the premise that the disturbance influence is eliminated, the basic flow velocity requirement value is accurately calculated based on the difference between the completed average liquid level and the target liquid level using a proportional-integral control algorithm. Through the above process, the interference of short-term liquid level disturbances on the flow velocity calculation results is effectively avoided, solving the problems of inaccurate flow velocity judgment and unstable control strategy response in existing technologies, thereby improving the accuracy of basic flow velocity requirement value calculation and system control stability.

[0016] 3. By employing a technology that integrates upstream pumping station drainage status data to calculate the predicted lag time of upstream water arrival at the target pumping station, and within a preset time period before this lag time, combines drainage status data with precipitation trend prediction data to calculate the predicted total inflow during that time period, the system can anticipate the total amount of water that may flow into the target pumping station in the near future. Combined with real-time monitoring of the remaining capacity of the target pumping station's collection tank, it can determine if there is a risk of insufficient capacity. When the predicted total inflow exceeds the remaining capacity, the system calculates the difference to obtain the buffered water demand. Based on this, and combined with the current baseline operating frequency, it dynamically adjusts the target operating frequency of the pumps, thereby achieving feedforward control of changes in inflow. Through this process, the system effectively solves the problems of delayed pumping station operating frequency adjustment and the inability to anticipate sudden increases in drainage pressure caused by the superposition of upstream water and rainfall in existing technologies. This improves the foresight and initiative of pumping station scheduling response and enhances the system's ability to cope with sudden flow shocks. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a remote control method for a smart pumping station according to an embodiment of this application. Figure 2 This is a flowchart illustrating the calculation of the target operating frequency in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0018] Explanation of reference numerals in the attached figures: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0020] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0021] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0022] Figure 1 This is a flowchart illustrating a remote control method for a smart pumping station according to an embodiment of this application.

[0023] Please see Figure 1 This application provides a remote control method for a smart pumping station, the method comprising: S101. Obtain the operating status data and pump flow-efficiency characteristic curve of each first water pump in the target pumping station, the drainage status data of each second water pump in the upstream pumping station of the target pumping station, and the precipitation prediction data of the area where the target pumping station is located within a preset time period. The operating status data includes the water level value of the collection tank and the pressure data of the water outlet pipeline. In this embodiment, to achieve precise flow control and efficient energy consumption scheduling of the smart pumping station, it is first necessary to acquire multi-source data closely related to the pumping station's operating conditions. This includes the operating status data and flow-efficiency characteristic curves of each first pump in the target pumping station, the drainage status data of each second pump in the upstream pumping station of the target pumping station, and the precipitation forecast data for the area where the target pumping station is located within a preset time period. The acquisition of this data is a prerequisite for subsequent calculations of the basic flow velocity, determination of start-stop combinations, and operating frequency. It enables the comprehensive construction of an operating environment model of the pumping station in the current period and the short-term future, thereby providing the control logic with data support and predictive capabilities.

[0024] The operational status data of the first water pump includes real-time collected data on the water level in the collection tank and the pressure data of the outlet pipeline. The water level in the collection tank is acquired through a level sensor installed within the tank. This sensor operates based on the principle of hydrostatic pressure or ultrasonic ranging; that is, it calculates the water level by measuring the hydrostatic pressure of the liquid or the distance between the liquid surface and the sensor, reflecting the current water storage status of the pumping station. The pressure data of the outlet pipeline is collected in real-time by a pressure sensor installed on the main outlet pipe. This sensor, typically based on a strain gauge or piezoelectric element, converts pressure changes into electrical signals, reflecting the current back pressure of the downstream pipeline, which is crucial for subsequent head calculations.

[0025] The flow-efficiency characteristic curve of a water pump reflects the efficiency variation of the pump under different operating conditions (different flow rates). This data can be obtained through experimental data provided by the pump manufacturer or through testing during field operation. This characteristic curve reflects the energy consumption performance of the pump at different flow rates and is an important basis for energy efficiency optimization when determining pump start-up and shutdown combinations.

[0026] The drainage status data of each second pump in the upstream pumping station includes parameters such as its current operating status (on / off), drainage flow rate, and current operating frequency. This data is synchronously transmitted from the upstream pumping station control system to the target pumping station control system via the inter-pumping station communication link. This information is used to predict the timing and flow rate of upstream water entering the target pumping station and is the core input for implementing feedforward control.

[0027] In addition, by accessing meteorological data platforms or deploying regional meteorological stations, precipitation forecast data for the target pumping station's location within a predetermined time period can be obtained, including parameters such as predicted rainfall amount, rainfall intensity, and rainfall duration. Precipitation forecast data can be provided by high-resolution numerical weather prediction models (such as WRF and GRAPES) or short-term nowcasting systems based on radar inversion. This data is crucial for assessing the potential natural water inflow in the near future and for proactively adjusting the pumping station's drainage capacity.

[0028] By acquiring the aforementioned data, a multi-dimensional model of the target pumping station's internal operating status, upstream and downstream related operating conditions, and external environmental influencing factors was achieved. This provides comprehensive data support for subsequent flow rate demand calculations, start-up and shutdown decisions, and frequency scheduling, significantly improving the accuracy and foresight of control strategies. For example, 30 minutes before a heavy rainfall event, the system's rainfall forecast data showed that more than 20 millimeters of rainfall would occur within the next hour. Simultaneously, the three secondary pumps at the upstream pumping station were operating at a high frequency. Combining this with the current high level in the collection tank, the system automatically deduced that the future inflow would exceed the current drainage capacity, generating control commands in advance to increase the operating frequency of the first pump, thereby effectively avoiding overflow of the collection tank due to response lag.

[0029] S102. Calculate the liquid level deviation between the liquid level value of the water collection tank and the preset target liquid level value in each of the multiple consecutive preset time periods, and calculate the basic flow velocity requirement value of the target pumping station based on the liquid level deviation value. After acquiring the operating status data of the target pumping station, to achieve precise adjustment of the pumping station's drainage capacity, it is necessary to further calculate the level deviation value based on the difference between the water level value in the collection tank and the set target level value within multiple consecutive preset time periods. This deviation is then used to determine the degree of deviation between the current system and the ideal drainage state, thereby deriving the basic flow velocity requirement value of the target pumping station. Since the level signal may be interfered with by factors such as sudden water inflow, equipment fluctuations, or sensor errors during actual acquisition, directly calculating the flow velocity based on the original level deviation can easily lead to distorted judgments. Therefore, this step introduces a further analysis mechanism for the level change trend. By identifying abnormal disturbances and eliminating their interference, the stability and accuracy of flow velocity judgment are improved.

[0030] To achieve a refined assessment of the drainage status of the target pumping station, the system calculates the level deviation value for each of multiple consecutive preset time periods based on continuously collected water level values ​​in the collection tank and preset target water level values. The level deviation value refers to the height difference between the actual water level and the target water level at a certain moment or within a certain time period, reflecting the degree of deviation between the current water storage state and the ideal state, and is the core basis for judging the basic flow rate requirement.

[0031] The preset time period refers to the time division unit used for liquid level trend analysis, usually set to equal intervals, such as 5 minutes or 10 minutes per period. The purpose of setting this period is to balance the timeliness of the data with the stability of the calculation: a period that is too short will lead to frequent system adjustments and unstable control; a period that is too long may delay response and reduce adjustment efficiency. At the end of each preset period, the system extracts the liquid level sensor sampling data from the data acquisition module for that period and obtains the representative liquid level value for that period through the median, average, or last value. For example, if the period is 5 minutes, the liquid level reading at the end of those 5 minutes can be directly extracted as the liquid level value for that period.

[0032] The target liquid level is a reference liquid level set by the dispatching system during the pump station operation parameter setting phase. It is usually set uniformly based on factors such as the pump station's design capacity, drainage efficiency, and safety redundancy, for example, 60% of the design liquid level height of the collection tank. This target value remains unchanged during system operation and is used as a benchmark to measure whether the current liquid level is too high or too low.

[0033] The system calculates the difference between the water level in the collection tank for each cycle and the target water level, obtaining the water level deviation value for that cycle. A positive deviation value indicates that the water level is higher than the target value, and the system may need to increase the drainage flow rate; a negative deviation value indicates that the water level is lower than the target value, and the system may not need to activate additional drainage equipment or can reduce its operating frequency. By continuously calculating the deviation values ​​for multiple cycles, the trend of water level changes can be obtained, providing a data basis for subsequent judgment of whether there are abnormal disturbances or whether drainage capacity needs to be adjusted. To further improve the accuracy of the calculation of the basic flow rate requirement, the system calculates the rate of water level change between any two adjacent preset time cycles based on the above water level deviation values, that is, the rate at which the water level rises or falls per unit time. Specifically, this may include the following steps: The rate of change of liquid level between any two adjacent preset time periods is calculated based on the liquid level deviation value. If the absolute value of the liquid level change rate is greater than the preset disturbance judgment threshold, the current state is determined as a suspected disturbance state, and the predicted disturbance time period is determined based on the difference between the liquid level change rate and the preset disturbance judgment threshold. If, during the predicted disturbance period, the rate of change of the liquid level changes from a positive value to a negative value, and the absolute value of the negative rate is greater than a preset amplitude change threshold, then a liquid level pulse disturbance event is confirmed to have occurred. In this case, the peak liquid level within the predicted disturbance period is removed, and data is completed for the removed position based on a preset data completion rule. Calculate the average liquid level after data completion within the predicted disturbance time period, calculate the difference between the average liquid level and the preset target liquid level, and calculate the basic flow rate requirement based on the difference and the preset proportional-integral control algorithm.

[0034] After obtaining the liquid level deviation values ​​over multiple consecutive preset time periods, the system further performs a differential calculation on the liquid level deviation values ​​between any two adjacent time periods to determine the dynamic trend of liquid level changes, thus calculating the liquid level change rate. The liquid level change rate refers to the speed at which the liquid level changes per unit time. It is calculated by subtracting the liquid level deviation value of the previous period from the liquid level deviation value of the subsequent period, and then dividing by the period length. For example, if the preset period is 5 minutes, and the liquid level deviation of the previous period is +0.20 meters, and the deviation of the next period is +0.35 meters, then the change rate is (0.35 - 0.20) / 5 = 0.03 meters per minute. This rate reflects the speed at which the liquid level rises or falls and is crucial basic data for identifying potential system disturbances, sudden water inflows, or abnormal pump station operation. By continuously calculating the rate between multiple periods, the system can perceive the liquid level change trend in real time, providing a basis for determining whether to enter the disturbance identification process.

[0035] When the system detects that the absolute value of the liquid level change rate over a certain period exceeds a preset disturbance judgment threshold, it triggers the logic for determining a suspected disturbance state. The disturbance judgment threshold is an upper limit for the liquid level change rate set by the system before deployment based on historical data analysis or expert experience. It is typically set as an empirical boundary value for the liquid level change rate under normal operating conditions of the pumping station, such as 0.05 m / min. When the liquid level rate exceeds this value, it means that the liquid level is undergoing an abnormal change, which may be caused by sudden upstream water inflow, heavy rainfall, abnormal equipment drainage, etc. To avoid directly using such abnormal changes as the basis for flow rate control, the system marks the current state as a suspected disturbance and calculates the probability of the disturbance duration based on the magnitude by which the liquid level rate exceeds the disturbance judgment threshold.

[0036] After the system detects that the absolute value of the liquid level change rate within a certain time period exceeds the set disturbance judgment threshold, it does not immediately identify it as a liquid level disturbance event, but instead enters the predictive disturbance analysis process. At this point, to more accurately define the possible time range of the disturbance, the system further calculates the difference between the change rate and the disturbance judgment threshold, and estimates the possible duration of the disturbance based on this difference, i.e., determines the predicted disturbance time period. This difference reflects the degree to which the liquid level change amplitude exceeds the normal fluctuation range and is also a quantitative indicator of the disturbance intensity. For example, if the disturbance judgment threshold is 0.05 m / min, and the liquid level change rate in the current period is 0.13 m / min, then the difference is 0.08 m / min. The system maps this difference to a preset disturbance duration judgment model to calculate the length of the predicted disturbance time period. This judgment model is usually trained based on historical data and exhibits a linear or non-linear relationship; for example, it may set an additional disturbance observation period of one cycle for every 0.01 m / min exceeding the threshold. In the example above, the difference is 0.08 m / min, meaning the disturbance is estimated to last for 8 cycles, or 40 minutes (if the cycle is 5 minutes). Based on this, the system continuously monitors the liquid level rate change trend over the next 40 minutes, constructing a disturbance characteristic window to further determine whether the pulse disturbance condition is met. This strategy of inferring the duration of the disturbance by the magnitude of the difference avoids overreacting to minor fluctuations while allowing for early intervention against strong anomalies, providing clear boundaries for subsequent data removal and repair. This not only improves the system's sensitivity to sudden disturbances but also enhances the targeting and accuracy of subsequent processing steps, providing a differentiated response mechanism for disturbances of different intensities, thus improving the algorithm's adaptability and intelligence.

[0037] During the predicted disturbance period, the system continuously tracks the numerical change in the rate of liquid level change. If the rate changes from positive to negative, and the absolute value of this negative rate is greater than a preset amplitude change threshold, a liquid level pulse disturbance event is confirmed. The amplitude change threshold is a speed indicator used to determine whether a rapid rise in liquid level followed by a rapid fall constitutes an abnormal fluctuation; for example, it is set to -0.07 m / min. Liquid level pulse disturbances are a typical short-term anomaly, commonly seen when a sudden increase in upstream water volume during heavy rainfall is followed by rapid discharge, or when frequent start-ups and shutdowns of pumps at pumping stations cause short-term, drastic fluctuations in liquid level. After confirming the disturbance, the system removes peak liquid level data from the liquid level curve within the predicted disturbance period to prevent such anomalies from misleading subsequent flow rate judgments. The peak liquid level refers to the maximum liquid level reading or inflection point during this period, which is usually far from the normal trend line. After removal, the system completes the missing data according to preset data completion rules. The completion rules can include linear interpolation, moving average, or fitting algorithms based on historical similar curves. The purpose is to maintain the continuity and smoothness of the liquid level data and ensure the accuracy of subsequent average calculations. For example, if the peak liquid level in a certain segment is 3.25 meters, and the surrounding normal values ​​are 2.80 meters and 2.78 meters, the system will discard 3.25 meters and interpolate 2.79 meters as the completion value.

[0038] After data removal and completion, the system re-statistically analyzes the liquid level data within the disturbance period to obtain the completed average liquid level. This average liquid level, representing a stable change in liquid level during that period, reflects the true water storage state after eliminating disturbance factors. The system then calculates the difference between this average liquid level value and the preset target liquid level value to obtain a corrected liquid level deviation value. This deviation value no longer includes the impact of sudden disturbances and is closer to the operating state of the pumping station under normal hydrological conditions. Subsequently, the system calculates the basic flow velocity requirement value for the target pumping station based on this difference and a preset proportional-integral control algorithm.

[0039] In this embodiment, to achieve dynamic response and long-term correction of the system to liquid level deviation, a proportional-integral (PI) control algorithm is used to calculate the basic flow rate requirement. The parameter settings of the proportional and integral terms directly affect the accuracy and stability of the control output. The proportional term reflects the immediate impact of the current liquid level deviation on the control result; its function is to quickly adjust the control quantity based on the distance between the current liquid level and the target liquid level. The integral term reflects the cumulative effect of historical accumulated deviations on the control result, used to eliminate potential steady-state errors in the system and ensure that the liquid level can stably return to the target value.

[0040] The gain parameter of the proportional term, i.e., the proportional coefficient, is usually set based on the actual operating conditions of the system or the results of simulation debugging. A higher value results in a faster system response to level deviations, but setting it too high may lead to system oscillations or over-adjustment; conversely, a proportional coefficient that is too low may result in a slow control response and a slow level recovery speed. In practical applications, the proportional coefficient is generally set empirically or optimized through simulation based on the pumping station scale, pump start-up and shutdown response characteristics, and level fluctuation range. For example, in small and medium-sized municipal drainage pumping stations, the proportional coefficient can be set in the range of 0.5 to 1.0, and fine-tuned using trial operation data during the initial stage of system operation.

[0041] The gain parameter of the integral term, i.e., the integral coefficient, is usually determined based on the proportional coefficient and a preset integral time constant. The integral time constant indicates how long the system expects to fully compensate the accumulated deviation back to the target state, and is usually set to a time length several times the control cycle, such as 5 to 15 minutes. Setting the integral coefficient requires a trade-off between response speed and system stability. If the integral action is too strong, it may lead to "integral saturation" or "overshooting" in the control system, meaning the system will exhibit a reverse deviation due to overcompensation. If the integral action is too weak, the liquid level may deviate from the target value for an extended period without correction. Therefore, the integral term is usually set in coordination with the proportional term, adjusted through simulation models or field data playback to ensure stable operation of the system under different operating conditions.

[0042] For example, in a pumping station, if the proportional coefficient is set to 0.8 and the integral time constant is 10 minutes, then the integral coefficient can be set to 0.08. If the deviation between the current liquid level and the target liquid level is 0.3 meters, and the historical cumulative deviation is 2.5 meters per minute, then the impact value calculated by the proportional term is 0.24, and the impact value calculated by the integral term is 0.2, resulting in a base flow rate requirement of 0.44 cubic meters per second at the current moment. This value will serve as the basis for the next step of pump start-up and shutdown and frequency control, ensuring that the liquid level is effectively pushed back to the target level without causing system overload.

[0043] S103. Determine the target pump start-stop combination based on the basic flow rate requirement value and the flow-efficiency characteristic curve of each of the first water pumps. After calculating the basic flow velocity requirement, to achieve efficient allocation and energy optimization control of the pumping station's drainage capacity, the system further determines the start-up and shutdown combinations of the target pumps based on this basic flow velocity requirement and the flow-efficiency characteristic curves corresponding to each first pump. Since different pumps exhibit varying efficiency under different operating conditions, blindly combining them according to rated parameters may lead to a decrease in the overall operating efficiency of the pumping station, or even cause abnormal loads or inefficient operation of some pumps. Therefore, when determining the start-up and shutdown combinations, the system fully considers the real-time efficiency performance of each operating pump and evaluates it in conjunction with its characteristic curves, thereby achieving dynamic optimization of the pump start-up and shutdown strategy. Specifically, this may include the following steps: The efficiency deviation of the first water pump is calculated based on the actual operating efficiency in the operating status data of the first water pump and the flow-efficiency characteristic curve corresponding to the first water pump. The first water pump whose efficiency deviation is greater than the preset efficiency fluctuation threshold is identified as a performance fluctuation water pump, and the first water pump whose efficiency deviation is less than or equal to the preset efficiency fluctuation threshold is identified as a normal performance water pump. The rated flow rate of the water pump with normal performance is determined as the effective flow rate of the water pump with normal performance. The efficiency attenuation coefficient of the performance-fluctuating water pump is calculated based on the efficiency deviation corresponding to the performance-fluctuating water pump. The product of the rated flow rate and the efficiency attenuation coefficient is determined as the effective flow rate of the performance fluctuation pump; The target pump start / stop combination is determined based on the effective flow rate.

[0044] In calculating the target pump start-stop combination, the system first calculates the efficiency deviation of each pump based on its actual operating efficiency and corresponding flow-efficiency characteristic curve in the operational status data. The "actual operating efficiency" refers to the ratio between the actual outflow rate per unit energy consumption and the theoretical energy efficiency under the current operating frequency and load conditions. This is typically derived by back-calculating data from pump station current, voltage, frequency, and flow monitoring. The "flow-efficiency characteristic curve" refers to the optimal operating efficiency at different flow points under factory or measured conditions, serving as a standard curve for evaluating pump performance. By comparing the actual efficiency value under current operating conditions with the theoretical efficiency value of this characteristic curve at the corresponding flow point, the system calculates the efficiency deviation, reflecting whether the pump is currently operating at high efficiency. For example, if a pump's current flow rate is 120 L / s and its actual efficiency is 65%, while the theoretical efficiency of the corresponding characteristic curve is 75%, its efficiency deviation is -10%. This deviation provides a basis for subsequent identification of the pump's performance status.

[0045] After acquiring the efficiency deviation, the system marks the first pump with an efficiency deviation exceeding a preset efficiency fluctuation threshold as a performance fluctuation pump, while pumps with efficiency deviations within this threshold are marked as normal performance pumps. The "efficiency fluctuation threshold" refers to the upper limit of the system's allowable efficiency deviation, used to distinguish between normally operating pumps and performance-degraded pumps. It is generally set based on historical operating data or expert experience, for example, ±5%. The purpose of setting this threshold is to remove pumps that may have internal wear, impeller aging, or inlet blockage from the high-efficiency scheduling combination, preventing their inefficient operation from affecting the overall drainage efficiency. Through this step, the system can quickly identify pumps with abnormal performance in the current operating state and reduce their weight in subsequent control, thereby improving the overall operating efficiency of the pump combination.

[0046] For pumps identified as operating normally, since their efficiency is within the normal range, the system directly determines their rated flow rate as the effective flow rate for subsequent start-stop combination calculations. Rated flow rate refers to the standard water output capacity of the pump at its rated head and rated frequency, generally provided by the equipment manufacturer or determined through on-site testing. Because pumps operating normally tend to consistently approach their optimal efficiency point during actual operation, their rated flow rate can be considered their effective output capacity in start-stop combinations. This approach simplifies the scheduling calculation process while ensuring that the pumps selected for the system have predictable flow output capabilities, thus improving the reliability of the combination configuration.

[0047] For pumps with fluctuating performance, since their operating efficiency is significantly lower than the theoretical value, the system needs to further calculate an efficiency attenuation coefficient based on the efficiency deviation to correct their flow capacity. The efficiency attenuation coefficient is a correction factor less than 1, representing the reduction ratio of the pump's actual output capacity to its rated capacity under current operating conditions. The calculation formula can be expressed as: Attenuation coefficient = Actual efficiency / Theoretical efficiency. For example, if a pump's current efficiency is 60% and its theoretical efficiency is 75%, then the attenuation coefficient is 0.80. This coefficient reflects the degree of pump performance degradation and is thus used to adjust its output contribution in the overall system. This mechanism avoids the system overestimating the drainage capacity of pumps with degraded performance, improving the execution effect of control commands and actual response capabilities.

[0048] After obtaining the efficiency decay coefficient, the system multiplies the rated flow rate of the pump with the performance fluctuation by this coefficient to obtain its effective flow rate under the current condition. This effective flow rate represents the actual usable drainage capacity of the pump under the current operating conditions, and is a dynamic assessment of its rated capacity combined with its current performance state. For example, if a pump has a rated flow rate of 100 L / s and a decay coefficient of 0.8, then its effective flow rate is 80 L / s. In this way, the system can quantify the actual drainage capacity of pumps in different performance states and allocate weights in subsequent combinations to ensure that the control strategy is based on the actual usable capacity rather than the theoretical capacity.

[0049] Based on the effective flow rates of all pumps with normal and fluctuating performance, the system comprehensively evaluates the flow contribution capacity of all available pumps and, combined with the currently calculated baseline flow rate requirement, determines the optimal target pump start-stop combination. Specifically, this may include the following steps: sorting all the first pumps according to their effective flow rates from largest to smallest to obtain a dynamic performance ranking list; starting from the first first pump in the dynamic performance ranking list, accumulating the effective flow rate of each first pump until the total accumulated effective flow rate is first greater than or equal to the baseline flow rate requirement; then, identifying all the first pumps included in the accumulation process as operating pumps in the target pump start-stop combination, and identifying all first pumps other than the operating pumps as shut-down pumps.

[0050] After calculating the effective flow rate, to automatically optimize the pump start-up and shutdown strategy, the system further sorts the pumps based on their effective flow rates, creating a dynamic performance ranking list to assist in selecting the optimal combination of pumps. The "effective flow rate" refers to the actual drainage capacity that each pump can stably output under its current operating conditions, considering its actual efficiency. This value has been dynamically corrected in the preceding steps using efficiency deviation or efficiency decay coefficients. Because different pumps have different operating conditions, wear levels, and response characteristics, their effective drainage capacities may differ even if their rated parameters are the same. Therefore, the system sorts all the pumps from highest to lowest effective flow rate and stores the results in a dynamic performance ranking list. This list reflects the overall performance level of each pump in the pumping station and is a key foundation for achieving intelligent scheduling and maximizing operational efficiency. Through this ranking, the system can prioritize the operation of high-efficiency, stable pumps, effectively avoiding the problems of increased overall energy consumption or insufficient drainage capacity caused by the participation of inefficient pumps.

[0051] After obtaining the dynamic performance ranking list, the system starts with the first pump in the list and sequentially accumulates its effective flow rate value until the total accumulated value first exceeds or equals the current basic flow rate requirement. The purpose of this operation is to select the fewest possible pump combinations with the highest efficiency while meeting drainage requirements, thereby reducing operating energy consumption and equipment wear. The basic flow rate requirement is the current drainage target value calculated using the liquid level deviation and proportional-integral control algorithm, representing the theoretical drainage capacity required by the pumping station under current operating conditions. By progressively comparing this accumulated value with the effective flow rate, the system dynamically determines which pumps can be activated to meet the drainage capacity. When the accumulated value first meets or exceeds the requirement, it indicates that the number of pumps currently added is sufficient to complete the task, and subsequent pumps do not need to be activated, thus avoiding unnecessary energy consumption. This process does not require exhaustively listing all combinations, has high computational efficiency, and is suitable for real-time control.

[0052] After determining the set of pumps that cumulatively meet the basic flow rate requirement, the system defines the first pump participating in the accumulation process as the operating pump in the target pump start-stop combination, while defining the remaining pumps not included as shut-off pumps. Operating pumps will serve as the actual working units participating in the drainage task in the current cycle, and their control parameters (such as frequency and start-stop sequence) will be further refined in subsequent steps; while shut-off pumps remain in standby mode to avoid ineffective operation. This strategy achieves optimal allocation of pump station resources through a data-driven approach, significantly improving system operating efficiency and equipment lifespan while ensuring drainage capacity. For example, when the basic flow rate requirement is 350 L / s, and the effective flow rates of the first pumps after sorting are 160, 120, 100, 90, and 80 L / s respectively, the system will sequentially accumulate the first two pumps to obtain 280 L / s. If this is insufficient, a third pump will be added, reaching a cumulative total of 380 L / s, exceeding the requirement. Therefore, the first three pumps are identified as operating pumps, and the remaining two are marked as shut-off pumps.

[0053] The above implementation method ensures that the pump start-stop combination is dynamically adjusted based on the current performance status in each control cycle, avoiding energy waste caused by fixed configuration. It achieves the optimal balance between pump station drainage capacity and energy consumption under varying conditions of rainfall, upstream drainage and liquid level disturbance, providing a high-quality foundation for subsequent frequency control and scheduling strategies.

[0054] S104. Calculate the head requirement value based on the pressure data of the water outlet network, and determine the single pump flow requirement value of each operating pump in the target pump start-stop combination based on the basic flow velocity requirement value. After determining the target pump start-stop combination, in order to achieve refined control of the operating status of each operating pump and ensure that the selected pump combination meets the overall drainage requirements while also meeting the system's dual requirements for head and flow matching, the system calculates the head requirement value based on the outlet pipeline pressure data in step S104. Based on this, and combined with the basic flow velocity requirement value, the system determines the single pump flow requirement value of each operating pump in the target pump start-stop combination.

[0055] In practice, pressure sensors deployed in the outlet pipes of the target pumping station are used to acquire real-time pressure data of the current outlet network. These sensors typically employ strain gauge bridges or piezoelectric elements, converting the pressure exerted by the liquid in the pipe on the sensor diaphragm into an electrical signal. The system then digitizes this signal using a sampling module to obtain the pressure value per unit area. The outlet network pressure reflects the back pressure state of the pumping station's drainage channel, directly affecting whether the pumps can successfully deliver water to the downstream network. Therefore, its value change is a key indicator for determining the required head.

[0056] After obtaining the outlet water pressure value, the system combines the geometric parameters of the pump station's outlet pipeline (such as pipe diameter and installation elevation) with the terrain elevation of the target drainage location, and uses hydraulic formulas to calculate the head requirement in reverse. The head requirement is equal to the pressure head (in meters of water column) corresponding to the outlet water pressure value, plus the sum of the static lift height and friction loss along the flow path. The pressure head calculation formula is: H_p = P / (ρ × g) Where H_p is the pressure head (unit: meters), P is the outlet water pressure (unit: Pascals), ρ is the density of water (approximately 1000 kg / m³), and g is the acceleration due to gravity (9.81 m / s²). The system adds the above pressure head to the friction loss and static lift height calculated through the flow-pipe model to obtain the head requirement that the pumping station must meet for current operation.

[0057] For example, if the outlet water pressure is 29430 Pa, the head is 3 meters. If there is a friction loss of 2 meters in the pipeline system, and the pump station needs to be raised to a downstream node 4 meters above the pump shaft centerline, then the head requirement is 3+2+4=9 meters.

[0058] After determining the required head, the system begins allocating the required flow rate for each pump. The base velocity requirement is the overall drainage capacity target of the pumping station, calculated in the previous steps using the level deviation and proportional-integral controller, and is typically expressed in cubic meters per hour (m³ / h) or liters per second (L / s). Since the target pump start-stop combination, i.e., the set of pumps participating in the drainage task of this cycle, has been determined in the previous stage, the system needs to reasonably allocate the base velocity within this combination to calculate the required flow rate for each operating pump.

[0059] To ensure reasonable allocation, the system adopts an allocation strategy based on the proportion of effective flow rate. First, the effective flow rate of each operating pump in the target start-stop combination is extracted. Effective flow rate refers to the stable output flow capacity of the pump after considering its current performance state (whether there is efficiency degradation). Then, the system calculates the proportion of each operating pump's effective flow rate to the total effective flow rate, which serves as its weight for undertaking the total drainage task. Subsequently, the basic flow velocity requirement is allocated according to this weight, resulting in the single-pump flow rate requirement for each operating pump.

[0060] Assuming a base flow rate requirement of 420 L / s, and the target start-stop combination includes three pumps with effective flow rates of 160 L / s, 140 L / s, and 100 L / s respectively, the total effective flow rate is 400 L / s. The allocation ratios for each pump are 0.4, 0.35, and 0.25, respectively. Based on this, the system calculates the single-pump flow rate requirements to be 168 L / s, 147 L / s, and 105 L / s.

[0061] S105. Based on the single pump flow requirement value and the head requirement value, calculate the reference operating frequency of each of the operating pumps; In step S105, to achieve refined control of each operating pump in the target pump start-stop combination, the system calculates the reference operating frequency of each operating pump based on the single pump flow demand value determined in step S104 and the head demand value derived from the current pump station outlet network pressure data. Specifically, the system first extracts the rated operating parameters of each operating pump, including the rated frequency f. n Rated flow rate Q n and rated head H n Based on the target flow rate Q_d of the water pump and the system head requirement H_d, calculations are performed using the physical relationship between the pump operating parameters and frequency: According to the characteristic that the pump flow rate is approximately proportional to the frequency and the head is proportional to the square of the frequency, the target frequency f_Q = f_d based on the flow rate is calculated. n ×(Q_d / Q n ) and target frequency based on head The system then selects the larger of the two values ​​as the current reference operating frequency for the water pump. This ensures that the pump meets both the flow output requirements and has sufficient head capacity, avoiding insufficient head leading to poor water flow or idling losses. For example, if a water pump has a rated frequency of 50Hz, a rated flow rate of 150L / s, and a rated head of 10 meters, while its current single-pump flow requirement is 120L / s and the system head requirement is 7.5 meters, then the frequency calculated based on flow rate is 40Hz, and the frequency calculated based on head is 43.3Hz. The system ultimately determines its reference operating frequency to be 43.3Hz. Using this method, the system calculates the frequency of each operating pump in the target start-stop combination, generating a set of reference frequencies that match the current drainage target. This serves as the basis for subsequent frequency fine-tuning and frequency conversion control command generation, ensuring that the pumping station system operates at its optimal energy efficiency while meeting the drainage load.

[0062] S106. Calculate the target operating frequency of the operating water pump based on the reference operating frequency, the drainage status data, and the precipitation trend prediction data; After calculating the target pump start-stop combination and its reference operating frequency, to further enhance the dispatch response capability of the smart pump station in a dynamic hydrological environment, the system introduces drainage status data and precipitation trend prediction data in step S105 to correct the reference operating frequency in real time, thereby calculating a more forward-looking and adaptive target operating frequency. Because the actual operation of the pump station is affected not only by changes in current liquid level and pressure, but also by nonlinear external factors such as the time lag of water inflow from upstream pump stations and sudden inflows from regional heavy rainfall, control based solely on the static reference frequency may not be able to respond promptly to sudden increases in water volume, leading to a sudden rise in the water level in the collection tank or even drainage failure. Therefore, in this step, the system uses the reference operating frequency as the control benchmark, superimposing the time lag characteristics of upstream water inflow, changes in rainfall intensity during the prediction period, and the remaining capacity of the target pump station's current collection tank. By calculating the difference between the inflow trend and the drainage capacity, the system dynamically adjusts the frequency output to form the final target operating frequency used for control execution. Figure 2 This is a flowchart illustrating the calculation of the target operating frequency in an embodiment of this application. The following is a summary of the process. Figure 2 A detailed explanation of step S105 is provided below: S201. Calculate the predicted lag time point for the upstream water to reach the target pumping station based on the drainage status data of the upstream pumping station. In the remote control process of intelligent pumping stations, in order to achieve proactive adjustment and advanced control of the target operating frequency of the pumps, the system needs to know in advance the timing of the impact of the drainage process of the upstream pumping station on the target pumping station. Therefore, in step S201, the system calculates the predicted lag time point for the upstream water to reach the target pumping station based on the drainage status data of the upstream pumping station. The predicted lag time point refers to the time delay required for the discharged water to be transmitted to the target pumping station through the connecting waterway system after the upstream pumping station starts its drainage behavior. It is used to characterize the time response characteristics in the hydraulic transmission path and is a key parameter for advance scheduling. Since the upstream water often has sudden and inertial characteristics, if the target pumping station cannot predict and adjust its drainage capacity in time, it is very easy to cause the water level in the collection tank to rise rapidly, resulting in local overload or even overflow risk of the drainage system. Therefore, it is necessary to model and dynamically calculate the lag effect of the upstream drainage behavior.

[0063] In practice, the system first obtains drainage status data from the upstream pumping station, including the drainage start time, drainage duration, drainage flow rate, and basic information about the downstream pipeline connection path of the target pumping station at each time point. Based on the established hydraulic path topology model, and combined with hydraulic parameters such as path length, waterway cross-sectional shape, water surface slope, and roughness, the system uses a simplified Saint-Venant equations or an empirical propagation model to calculate the hydraulic propagation time, obtaining an estimated propagation delay from the upstream drainage point to the inlet of the target pumping station's collection tank. To improve prediction accuracy, the system can incorporate historical monitoring data and train a machine learning regression model to study the relationship between different drainage flows and actual arrival times, thereby achieving adaptive lag time prediction under different water level conditions. The final predicted lag time point serves as the time window boundary for calculating the total inflow volume in subsequent steps, ensuring that the system can reserve sufficient drainage buffer capacity before the actual arrival of the incoming water.

[0064] For example, if the upstream pumping station starts drainage at 12:00 with a drainage flow rate of 280 L / s, and the system calculates the water transport time to be 18 minutes based on path parameters, then the predicted lag time is 12:18. At this point, the target pumping station needs to complete frequency adjustment before 12:18 to ensure the operating pumps have sufficient drainage capacity to cope with the subsequent large flow, thereby achieving a proactive response to sudden inflows and effectively improving the overall scheduling safety and operational stability of the pumping station system.

[0065] S202. Within a preset time period before the lag time point, calculate the predicted total inflow within the preset time period based on the drainage status data and the precipitation trend prediction data. After calculating the predicted lag time of upstream water inflow, the system, in order to achieve advance assessment of the future inflow to the target pumping station and dynamically adjust the target operating frequency of the pumps, uses a preset duration as the predicted time window for assessing the future inflow to the target pumping station. This preset duration is primarily based on the hydraulic propagation lag characteristics of upstream water inflow, the response time of regional rainfall and surface runoff, and the minimum adjustment cycle of the pumping station scheduling system. Specifically, this duration is usually determined through statistical analysis of historical hydrological data. For example, analyzing the average time difference of the target pumping station's level response after upstream pumping station drainage, and the average time delay of surface runoff flowing into the pumping station after regional rainfall, yields a representative time span, often set to 15 minutes, 30 minutes, or 60 minutes. The purpose of this duration is to provide sufficient pre-adjustment time for the pumping station, enabling the dispatching system to complete the adjustment of operating frequency and drainage capacity matching before the future load arrives, ensuring the forward-looking and stable operation of the system. Specifically, it includes the following steps: determining the drainage flow data within the preset duration as the base inflow; calculating the predicted rainfall within the preset duration based on the rainfall trend prediction data, and determining the rainfall inflow as the product of the predicted rainfall and the preset water collection coefficient; and determining the total predicted inflow as the sum of the base inflow and the rainfall inflow.

[0066] To achieve dynamic matching between the pumping station's drainage capacity and future inflow volume, and to ensure the pumping station can respond promptly and maintain operational stability during sudden inflow scenarios, the key operation in step S202 is the calculation of the predicted total inflow volume. In this process, the system first uses the drainage flow data acquired within a preset time period before the lag point as the base inflow volume. The "drainage flow data" refers to the time-series drainage flow data collected and uploaded in real time by the upstream pumping station, typically in units of L / s or m³ / h, reflecting the actual discharge behavior of the upstream pumping station within a given time period. This data directly reflects the impact of artificial drainage behavior on the future inflow volume of the target pumping station and is therefore considered a fundamental component of the total inflow. The system integrates the drainage flow data over time within the preset prediction period to obtain the cumulative drainage volume during that period, and then uses this volume as the base inflow volume input into the prediction model.

[0067] Building upon this foundation, the system incorporates precipitation trend forecast data to supplement the inflow impact of natural rainfall. This "precipitation trend forecast data" is a short-term rainfall intensity forecast generated based on a meteorological prediction model, typically containing information such as rainfall amount and spatiotemporal distribution for the next tens of minutes to several hours. To transform this meteorological data into effective inflow for water volume calculation, the system introduces a "catchment coefficient" as a key conversion factor. This coefficient indicates the proportion of rainfall in a given area that ultimately flows into the catchment basin of the target pumping station. The value of the catchment coefficient is determined based on factors such as regional topography, surface type, and drainage facility density, and is usually obtained through fitting measured data or empirical formulas. In actual calculations, the system multiplies the rainfall amount (in mm) corresponding to the precipitation trend forecast data by the catchment area (in km²) to obtain the potential catchment volume, and then multiplies this by the catchment coefficient to obtain the expected precipitation inflow into the pumping station during that period.

[0068] Finally, the system sums the baseline inflow and precipitation inflow to obtain the predicted total inflow. This value serves as the basis for determining whether the pumping station's catchment area can accommodate future inflows, and is further used to calculate buffer demand and adjust the target operating frequency of the pumps. In this way, the system effectively integrates the dual effects of artificial drainage and natural rainfall, constructing a more comprehensive future load prediction model and improving the adaptability of smart pumping stations to complex hydrological situations. For example, in a certain scheduling cycle, if the upstream pumping station's drainage flow is 300 L / s for 10 minutes, the baseline inflow is 180 m³; simultaneously, the predicted rainfall in the area within 10 minutes is 5 mm, the catchment area of ​​the pumping station's service area is 2 km², and the catchment coefficient is 0.6, then the precipitation inflow is 5 × 2 × 1000 × 0.6 = 6000 m³, and the final predicted total inflow is 6180 m³. This result will be directly used to determine whether the current pumping station has sufficient drainage capacity and adjust the operating frequency accordingly, achieving advance control.

[0069] S203. Monitor the remaining capacity of the water collection tank of the target pumping station. When the remaining capacity of the water collection tank is less than the predicted total inflow, determine the difference between the predicted total inflow and the remaining capacity of the water collection tank as the buffer demand water volume. To achieve precise scheduling and preventative drainage control, the system needs to further determine whether the drainage capacity of the target pumping station is sufficient, given the known predicted inflow volume. Therefore, in step S203, the system monitors the remaining capacity of the target pumping station's collection tank in real time and compares it with the predicted total inflow volume to determine if there is any buffered water demand. Essentially, this operation assesses whether the target pumping station's carrying capacity over a predicted period can cover the entire incoming water volume. If insufficient, the drainage pace needs to be accelerated in advance to release storage space.

[0070] In the implementation process, the system acquires the liquid level value of the collection tank in real time through a liquid level sensor, and calculates the currently usable remaining volume, i.e., the remaining capacity of the collection tank, by combining the structural parameters of the collection tank (such as the tank geometry, effective depth, and cross-sectional area). This value is usually expressed in cubic meters (m³), reflecting the volume of water that the collection tank can continue to hold without overflowing. Simultaneously, the system has already calculated the predicted total inflow in the previous step. This data includes the basic inflow formed by the drainage from the upstream pumping station and the precipitation inflow from rainfall, representing the total amount of water that may flow into the target pumping station in the future. By comparing the predicted total inflow with the current remaining capacity of the collection tank, if the predicted total inflow is greater than the remaining capacity, it indicates that the target pumping station will face the risk of overload inflow. The system calculates the difference between the two, which is the buffer demand water volume.

[0071] The introduction of buffered water demand aims to quantify the amount of water that the target pumping station needs to discharge in advance to avoid future overload, and it is a core input parameter for subsequent frequency regulation calculations. The system uses this value to determine whether the current drainage capacity needs to be increased and dynamically adjusts the operating frequency of the pumps accordingly. This method can significantly improve the foresight and proactivity of pumping station scheduling, avoiding drainage delays, sudden increases in water level, and even safety accidents caused by passive responses.

[0072] For example, during a certain scheduling cycle, real-time monitoring shows that the water level in the collection tank is 3.8 meters. The tank has a rectangular cross-section, is 30 meters long and 10 meters wide, and has a maximum water level of 5.0 meters. Therefore, the remaining capacity is (5.0 - 3.8) × 30 × 10 = 360 m³. If the predicted total inflow is 500 m³, then the buffer demand is 500 - 360 = 140 m³. Based on this, the system determines that the current drainage capacity is insufficient and needs to increase the drainage frequency of the operating pumps in advance to release at least 140 m³ of storage space before the incoming water arrives, thereby ensuring the safe operation of the pumping station.

[0073] S204. Calculate the target operating frequency of each of the operating water pumps based on the baseline operating frequency and the required water volume of the buffer.

[0074] After determining the required buffer water volume, to achieve dynamic adjustment of the pump operating frequency, ensuring it meets the pump station's real-time drainage needs while avoiding energy waste and equipment overload, the system introduces a target operating frequency calculation mechanism based on the required buffer water volume and the baseline operating frequency in step S204. The core of this step is to convert the required buffer water volume into an incremental requirement for the current drainage capacity, and adjust the baseline operating frequency accordingly to form a target operating frequency that adapts to future inflow pressure, thereby achieving dual optimization of the pump station's drainage efficiency and operational stability. Specifically, this may include the following steps: Calculate the ratio of the buffer water demand to the preset duration to obtain the pre-increased flow demand; Calculate the ratio of the pre-increased flow demand to the single pump flow demand value to obtain the flow regulation coefficient; The sum of one and the flow rate regulation coefficient is determined as the frequency regulation factor; When the frequency adjustment factor is less than the preset upper limit threshold for frequency adjustment and greater than the preset lower limit threshold for frequency adjustment, the product of the reference operating frequency and the frequency adjustment factor is determined as the target operating frequency. When the frequency adjustment factor is greater than or equal to the preset frequency adjustment upper limit threshold, the product of the preset frequency adjustment upper limit threshold and the reference operating frequency is determined as the target operating frequency; When the frequency adjustment factor is less than or equal to the preset lower limit threshold, the product of the preset lower limit threshold and the reference operating frequency is determined as the target operating frequency.

[0075] To achieve precise adjustment of each operating water pump to cope with short-term peaks in future inflow, after obtaining the total buffer water demand, the system allocates the buffer water demand to each operating water pump according to a preset strategy (e.g., proportional or average). The system then calculates the ratio of the buffer water demand allocated to each operating water pump to the preset duration to obtain the pre-increased flow rate demand for each operating water pump. The purpose of this step is to uniformly convert volumetric indicators into the auxiliary flow rate increase for each water pump, thereby providing a time-domain reference for frequency adjustment.

[0076] After obtaining the pre-increased flow demand for each operating pump, the system calculates the ratio of this ratio to the single-pump flow demand value corresponding to the current reference operating frequency of that pump, thus obtaining the flow regulation coefficient for each operating pump. The single-pump flow demand value mentioned here is based on the pump station's basic flow velocity demand value derived from the liquid level deviation and proportional-integral control algorithm in the preceding steps, and decomposed into the single-pump flow target value for that operating pump. The flow regulation coefficient obtained by calculating the ratio between these two values ​​reflects the degree of gap between the individual drainage capacity of the operating pump and the upcoming load, presenting a dimensionless relative regulation amplitude.

[0077] Subsequently, the system adds the value 1 to the flow regulation coefficient of each operating water pump to obtain the frequency regulation factor of each operating water pump. The design logic of this step is to use the reference operating frequency of each operating water pump as a reference baseline for frequency regulation, and linearly amplify or reduce it through its corresponding frequency regulation factor. If the value of the frequency regulation factor of each operating water pump is greater than 1, it means that the operating frequency of the water pump needs to be increased to enhance the drainage capacity; if it is less than 1, it means that the current drainage capacity of the water pump is redundant, and the frequency can be appropriately reduced to save energy and reduce consumption.

[0078] To prevent sudden changes in operating frequency due to excessively large or small frequency adjustment factors, which could affect the safe operation of the water pumps, the system introduces upper and lower frequency adjustment thresholds to limit the effective range of the frequency adjustment factor. These preset upper and lower frequency adjustment thresholds are two boundary parameters set during the design of the system's operating frequency adjustment logic. They limit the adjustment range of the frequency adjustment factor, thereby ensuring the safety of water pump operation and the stability of system scheduling. The setting of these two thresholds is mainly based on the rated frequency range of the water pumps configured in the target pumping station, the allowable variable frequency operation limits of the pump motors, the statistical results of frequency fluctuation amplitude in historical operating data, and the system's desired adjustment response sensitivity.

[0079] Specifically, for example, if the total buffer water demand is 180 m³, and the preset duration is 30 minutes, assuming there are two operating water pumps, according to the allocation strategy, pump A is allocated 100 m³, and pump B is allocated 80 m³. For pump A: the pre-increased flow demand is 100 ÷ 0.5 = 200 m³ / h. If the single-pump flow demand corresponding to the base operating frequency of pump A is 150 m³ / h, then the flow adjustment coefficient of pump A is 200 ÷ 150 ≈ 1.33, and the frequency adjustment factor is 1 + 1.33 = 2.33. If the upper limit threshold for frequency adjustment is set to 1.8 and the lower limit threshold to 0.6, then because the frequency adjustment factor exceeds the upper limit, the system sets the target operating frequency of pump A to the base operating frequency of pump A × 1.8. For pump B: the pre-increased flow demand is 80 ÷ 0.5 = 160 m³ / h. If the single-pump flow demand corresponding to the reference operating frequency of pump B is 130 m³ / h, then the flow adjustment coefficient of pump B is 160 ÷ 130 ≈ 1.23, and the frequency adjustment factor is 1 + 1.23 = 2.23. Similarly, because it exceeds the upper limit, the system sets the target operating frequency of pump B to the reference operating frequency of pump B × 1.8. Through the above method, the system achieves dynamic and flexible adjustment of the operating frequency of each pump, effectively improving the smart pumping station's ability to respond to short-term, high-intensity inflow events.

[0080] Furthermore, to further improve the rationality of threshold settings, the system can also combine historical scheduling records and correlation analysis between frequency and liquid level response, using machine learning or data regression methods to optimize the upper and lower limit settings. This ensures that these two parameters meet equipment protection requirements without affecting the system's rapid response capability to short-term flow surges. By setting upper and lower limit thresholds for frequency adjustment, the system forms a soft-limiting framework, maintaining a certain degree of flexibility during frequency adjustment while effectively avoiding equipment failures or control oscillations caused by extreme frequencies, thus ensuring the overall operational reliability of the smart pumping station.

[0081] The system determines the target operating frequency using a segmented calculation method based on the specific value of the frequency adjustment factor: when the frequency adjustment factor is between the upper and lower limits, it is directly multiplied by the reference operating frequency to obtain the target operating frequency; when the frequency adjustment factor exceeds the upper or lower limits, the upper or lower limit threshold is multiplied by the reference operating frequency to form an operating frequency output within a controlled range, thus avoiding the impact of frequency fluctuations on equipment stability.

[0082] For example, if the buffer water demand is 180 m³ and the preset duration is 30 minutes, then the pre-increased flow demand is 180 ÷ 0.5 = 360 m³ / h. If the base flow rate demand corresponding to the baseline operating frequency is 300 m³ / h, then the flow rate adjustment coefficient is 360 ÷ 300 = 1.2, and the frequency adjustment factor is 1 + 1.2 = 2.2. If the upper limit threshold for frequency adjustment is set to 1.8 and the lower limit threshold is 0.6, then because the frequency adjustment factor exceeds the upper limit, the system sets the target operating frequency to the baseline operating frequency × 1.8, in order to ensure drainage capacity while preventing the risk of equipment damage caused by excessive frequency. Through the above method, the system realizes dynamic and flexible adjustment of the pump operating frequency, effectively improving the response capability of the smart pump station to short-term high-intensity inflow events.

[0083] S107. Generate control instructions for the operating water pump based on the target operating frequency, and control the operating water pump to execute the control instructions.

[0084] After calculating the target operating frequency, in order to achieve precise control of the pumps operating in the target pumping station, the system generates control commands based on the determined target operating frequency in step S106 and sends these commands to the corresponding operating pumps, thereby achieving real-time control of the target pumps' start / stop status and operating frequency. The core purpose of this operation is to transform the theoretical scheduling results calculated in the previous step into specific control actions, thereby ensuring that the pumps operate according to the scheduling requirements, so as to achieve dynamic matching of drainage capacity and precise adjustment of liquid level.

[0085] In practice, the control system first uses the target operating frequency as an input parameter and generates standardized variable frequency control commands based on the water pump's electrical interface protocol (such as Modbus, Profibus, or CAN bus protocol). This command format typically includes fields such as the target frequency value, target water pump number, operating status command (e.g., start or stop), and control cycle identifier. The control commands are then transmitted to the water pump's variable frequency drive via a PLC (Programmable Logic Controller) or industrial control computer. Upon receiving the control commands, the variable frequency drive adjusts its output voltage and frequency according to the target operating frequency, thereby driving the water pump motor to rotate at the corresponding frequency, achieving real-time variable speed operation of the water pump.

[0086] During the generation of control commands, the system also needs to verify whether the target operating frequency is within the equipment's permissible operating range, i.e., between the lower and upper limits of the pump's rated frequency, to avoid the pump failing to start, tripping, or overloading due to abnormal frequency. For example, if the target operating frequency is 47Hz, and the pump's minimum permissible frequency is 45Hz, it is determined to be a valid frequency and a control command is generated; if the target frequency is lower than 45Hz, the system will automatically correct it to 45Hz before generating the control command, and simultaneously record the correction information for subsequent analysis.

[0087] Furthermore, to ensure that the execution results of control commands are consistent with scheduling expectations, the control system monitors real-time data such as the actual operating frequency, operating status, current, and voltage of the water pumps through a feedback mechanism after issuing control commands, determining whether the water pumps are operating stably at the target operating frequency. Once a frequency deviation exceeding the set range or a water pump failing to start as instructed is detected, the system will trigger an alarm or execute a backup water pump switching strategy to ensure the continuity and safety of the entire pumping station system.

[0088] Taking a practical application as an example, within a certain scheduling cycle, the system calculates that the target operating frequency of a certain water pump is 52Hz. The corresponding control command is: "P3, start state, set frequency 52Hz, control cycle T7". The system sends this command to the frequency converter of water pump P3 through the PLC interface. The frequency converter adjusts its output frequency to 52Hz according to the command, driving water pump P3 into the running state. Subsequently, the system detects in real time in the feedback channel that the operating frequency of water pump P3 is 51.9Hz. If the deviation is within the allowable range, the control command is considered to have been executed successfully, thus completing a complete remote precision control scheduling.

[0089] Please see Figure 3 This is a schematic diagram of the structure of a remote control system for a smart pumping station according to an embodiment of this application.

[0090] It should be noted that, Figure 3The structure of a remote control system for a smart pumping station shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0091] like Figure 3 As shown, a remote control system for a smart pumping station includes a central processing unit 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory 302 or a program loaded from a storage section 308 into a random access memory 303, such as executing the methods described in the above embodiments. The random access memory 303 also stores various programs and data required for system operation. The central processing unit 301, the read-only memory 302, and the random access memory 303 are interconnected via a bus 304. An input / output interface 305 is also connected to the bus 304.

[0092] The following components are connected to the input / output interface 305: an input section 306 including audio input devices, push-button switches, etc.; an output section 307 including an LCD display, audio output devices, indicator lights, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the input / output interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 310 as needed so that computer programs read from it can be installed into the storage section 308 as needed.

[0093] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit 301, it performs the various functions defined in the present invention.

[0094] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, flash memory, optical fiber, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0095] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0096] Specifically, the remote control system of a smart pumping station in this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the remote control method of a smart pumping station provided in the above embodiment.

[0097] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the remote control system of a smart pumping station described in the above embodiments; or it may exist independently and not assembled into the remote control system of the smart pumping station. The storage medium carries one or more computer programs, which, when executed by a processor of the remote control system of the smart pumping station, cause the remote control system of the smart pumping station to implement the remote control method of the smart pumping station provided in the above embodiments.

Claims

1. A remote control method for a smart pumping station, characterized in that, The method includes: The system acquires the operating status data and flow-efficiency characteristic curve of each first water pump in the target pumping station, the drainage status data of each second water pump in the upstream pumping station of the target pumping station, and the precipitation prediction data of the area where the target pumping station is located within a preset time period. The operating status data includes the water level value of the collection tank and the pressure data of the water outlet pipeline. Calculate the level deviation between the water level in the collection tank and the preset target level in each of the multiple consecutive preset time periods, and calculate the basic flow rate requirement of the target pumping station based on the level deviation. The target pump start-stop combination is determined based on the basic flow rate requirement and the flow-efficiency characteristic curve of each of the first water pumps. The head requirement is calculated based on the pressure data of the water outlet network, and the single pump flow requirement of each operating pump in the target pump start-stop combination is determined based on the basic flow velocity requirement. Based on the single pump flow requirement and the head requirement, calculate the reference operating frequency of each of the operating pumps; The target operating frequency of the operating water pump is calculated based on the baseline operating frequency, the drainage status data, and the precipitation trend prediction data. Based on the target operating frequency, control commands are generated for the operating water pump, and the operating water pump is controlled to execute the control commands.

2. The method according to claim 1, characterized in that, The calculation of the basic flow velocity requirement value of the target pumping station based on the liquid level deviation value specifically includes: The rate of change of liquid level between any two adjacent preset time periods is calculated based on the liquid level deviation value. If the absolute value of the liquid level change rate is greater than the preset disturbance judgment threshold, the current state is determined as a suspected disturbance state, and the predicted disturbance time period is determined based on the difference between the liquid level change rate and the preset disturbance judgment threshold. If, during the predicted disturbance period, the rate of change of the liquid level changes from a positive value to a negative value, and the absolute value of the negative rate is greater than a preset amplitude change threshold, then a liquid level pulse disturbance event is confirmed to have occurred. In this case, the peak liquid level within the predicted disturbance period is removed, and data is completed for the removed position based on a preset data completion rule. Calculate the average liquid level after data completion within the predicted disturbance time period, calculate the difference between the average liquid level and the preset target liquid level, and calculate the basic flow rate requirement based on the difference and the preset proportional-integral control algorithm.

3. The method according to claim 1, characterized in that, The determination of the target pump start-up and shutdown combination based on the basic flow rate requirement and the flow-efficiency characteristic curve of each of the first water pumps specifically includes: The efficiency deviation of the first water pump is calculated based on the actual operating efficiency in the operating status data of the first water pump and the flow-efficiency characteristic curve corresponding to the first water pump. The first water pump whose efficiency deviation is greater than the preset efficiency fluctuation threshold is identified as a performance fluctuation water pump, and the first water pump whose efficiency deviation is less than or equal to the preset efficiency fluctuation threshold is identified as a normal performance water pump. The rated flow rate of the water pump with normal performance is determined as the effective flow rate of the water pump with normal performance. The efficiency attenuation coefficient of the performance-fluctuating water pump is calculated based on the efficiency deviation corresponding to the performance-fluctuating water pump. The product of the rated flow rate and the efficiency attenuation coefficient is determined as the effective flow rate of the performance fluctuation pump; The target pump start / stop combination is determined based on the effective flow rate.

4. The method according to claim 3, characterized in that, The determination of the target pump start / stop combination based on the effective flow rate specifically includes: All the first water pumps are sorted from largest to smallest according to their effective flow rate to obtain a dynamic performance ranking list; Starting from the first first pump in the dynamic performance ranking list, the effective flow rate of each first pump is accumulated one by one until the total effective flow rate after accumulation is greater than or equal to the basic flow rate requirement value for the first time. Then, all the first pumps included in the accumulation process are identified as the running pumps in the target pump start-stop combination, and all the first pumps other than the running pumps are identified as the stopped pumps.

5. The method according to claim 1, characterized in that, The calculation of the target operating frequency of the pump based on the baseline operating frequency, the drainage status data, and the precipitation trend prediction data specifically includes: The predicted lag time for the upstream water to reach the target pumping station is calculated based on the drainage status data of the upstream pumping station. Within a preset time period before the lag time point, the predicted total inflow volume within the preset time period is calculated based on the drainage status data and the precipitation trend prediction data. Monitor the remaining capacity of the water collection tank of the target pumping station. When the remaining capacity of the water collection tank is less than the predicted total inflow, the difference between the predicted total inflow and the remaining capacity of the water collection tank is determined as the buffer demand. The target operating frequency of each operating water pump is calculated based on the baseline operating frequency and the required water volume of the buffer.

6. The method according to claim 5, characterized in that, Within a preset time period before the lag time point, the predicted total inflow volume within the preset time period is calculated based on the drainage status data and the precipitation trend prediction data, specifically including: The drainage flow rate data within the preset time period is determined as the basic inflow rate; Based on the precipitation trend prediction data, the predicted precipitation within the preset time period is calculated, and the product of the predicted precipitation and the preset water collection coefficient is determined as the precipitation inflow. The sum of the baseline inflow and the precipitation inflow is determined as the predicted total inflow.

7. The method according to claim 5, characterized in that, The calculation of the target operating frequency for each operating water pump based on the baseline operating frequency and the required buffer water volume specifically includes: Calculate the ratio of the buffer water demand to the preset duration to obtain the pre-increased flow demand; Calculate the ratio of the pre-increased flow demand to the single pump flow demand value to obtain the flow regulation coefficient; The sum of one and the flow rate regulation coefficient is determined as the frequency regulation factor; When the frequency adjustment factor is less than the preset upper limit threshold for frequency adjustment and greater than the preset lower limit threshold for frequency adjustment, the product of the reference operating frequency and the frequency adjustment factor is determined as the target operating frequency. When the frequency adjustment factor is greater than or equal to the preset frequency adjustment upper limit threshold, the product of the preset frequency adjustment upper limit threshold and the reference operating frequency is determined as the target operating frequency; When the frequency adjustment factor is less than or equal to the preset lower limit threshold, the product of the preset lower limit threshold and the reference operating frequency is determined as the target operating frequency.

8. A remote control system for a smart pumping station, characterized in that, The remote control system of the smart pumping station includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the remote control system of the smart pumping station to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the remote control system of the smart pumping station, the remote control system of the smart pumping station performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the remote control system of the smart pumping station, the remote control system of the smart pumping station performs the method as described in any one of claims 1-7.

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