An intelligent dispatching system for waterworks

Abstract

The present invention discloses an intelligent dispatching system for a waterworks, specifically related to the field of waterworks dispatching, including a data acquisition module, a dispatching model calculation module, a water intake adjustment module, and a control instruction issuing module. The data acquisition module is used to obtain dispatching operation data in real time from various devices and sensors in the waterworks, and perform structured processing on the dispatching operation data in a standardized data format, and transmit it to other modules of the system through network communication; the dispatching operation data includes water intake volume, water output volume, sludge discharge volume, backwashing water volume, sampling water volume, pressure water volume, and reservoir liquid level. Integrate and analyze various data of the waterworks, including water intake and output volumes, sludge discharge volume, filter backwashing queue and water volume, pressure water volume, sampling water volume, reservoir liquid level, etc., and predict the change of water volume in the factory and the water volume adjustment requirements through model calculation, so as to optimize the dispatching plan.

Description

Technical Field

[0001] The present invention relates to the technical field of water plant scheduling, and more specifically, to an intelligent scheduling system for a tap water plant. Background Art

[0002] Traditional water plant scheduling mainly relies on manual experience to perceive water usage patterns. By observing the water volume in each process section and the liquid level changes of water purification facilities, an empirical scheduling plan is finally formed; the company's scheduling center issues water output and water pressure requirements to the water plant according to the user's water usage needs. The water plant management personnel put forward requirements for the liquid level control range of the clear water reservoir according to the operation requirements, and the water plant scheduling personnel adjust the water inflow and the operation parameters of each process link according to the water output, water pressure, and reservoir liquid level requirements.

[0003] Centering around the overall goal of the construction of the Jujiaqiao Intelligent Water Plant, it is planned to introduce an intelligent scheduling mode, establish a whole-process scheduling system from water intake to water output, realize automatic and dynamic regulation of water volume, and replace manual experience with machine calculation. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent scheduling system for a tap water plant. By integrating and analyzing various data of the water plant, including water inflow, water output, sludge discharge water volume, filter backwashing queue and water volume, pressure water volume, sampling water volume, reservoir liquid level, etc., through model calculation, the water volume change situation in the plant is predicted to solve the problems raised in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solution: An intelligent scheduling system for a tap water plant, including a data acquisition module, a scheduling model calculation module, a water inflow adjustment module, and a control instruction issuing module;

[0006] The data acquisition module is used to obtain scheduling operation data in real time from various devices and sensors in the water plant, and perform structured processing on the scheduling operation data using a standardized data format, and transmit it to other modules of the system through network communication; the scheduling operation data includes water inflow, water output, sludge discharge water volume, backwashing water volume, sampling water volume, pressure water volume, reservoir liquid level;

[0007] The scheduling model calculation module is based on the collected scheduling operation data, and performs water volume calculation and liquid level prediction through a preset scheduling evaluation model; the scheduling model calculation module generates corresponding water inflow adjustment instructions according to the water volume calculation and liquid level prediction to keep the reservoir liquid level within a preset target range;

[0008] The water inflow adjustment module is used to judge whether it is necessary to adjust the water inflow according to the calculation result of the scheduling evaluation model, and then control the reservoir liquid level;

[0009] The control instruction issuing module realizes data transfer through communication with the PLC unit of the water plant, and obtains the dispatching operation data of the water plant in real time based on the interaction between the PLC unit and the upper computer; the control instruction issuing module obtains the dispatching calculation result according to the adjustment instruction of the dispatching model calculation module, generates the corresponding control instruction based on the dispatching calculation result, and transmits it to the PLC to execute the automatic adjustment of the water inflow and liquid level.

[0010] In a preferred embodiment, the dispatching evaluation model of the dispatching model calculation module includes a water volume model;

[0011] The water volume model includes:

[0012] Where is the water inflow of the water plant; is the water supply of the water plant; is the calculation time; is the reservoir area; is the change in reservoir liquid level; is the sludge discharge volume; is the sludge discharge time; is the number of filter tanks; is the backwashing water volume; is the sampling water volume; is the water volume for plant use pressure.

[0013] In a preferred embodiment, the dispatching logic of the dispatching model calculation module includes:

[0014] Obtain the dispatching operation data according to the data acquisition module;

[0015] Judge whether it is necessary to adjust the sludge discharge of the sedimentation tank, the backwashing of the filter tank, the sampling water volume and the pressure water volume in the next cycle;

[0016] Based on the water inflow of the water plant and the water output of the water plant When unchanged, the change trend of the reservoir liquid level is:

[0017]

[0018] Calculate the time when the reservoir liquid level reaches the control limit , through denotes the difference between the water inflow of the water plant and the water supply of the water plant;

[0019]

[0020]

[0021] Determine whether it is necessary to adjust the water inflow of the water plant: according to the preset time parameter of the system , when , a water plant water inflow regulation instruction is issued; when , the water plant water inflow is not adjusted;

[0022] The model obtains the current liquid level , and the target liquid level at the next determination time , and calculates the amount of water that needs to be adjusted for the current liquid level to reach the target liquid level within the set time :

[0023]

[0024] When , the water plant water inflow is not adjusted; when , according to Adjust; when , then according to ; where is the minimum adjustable water volume; is the maximum adjustable water volume;

[0025] The calculation of the current water volume is completed.

[0026] In a preferred embodiment, it further includes a scheduling mode selection module;

[0027] The scheduling mode selection module includes an energy-saving mode and a stable mode;

[0028] The energy-saving mode is used to continuously maintain the reservoir liquid level at a high level with the goal of reducing the energy consumption of the water outlet;

[0029] The stable mode is used to keep the water inflow stable and make the water treatment process operate stably.

[0030] In a preferred embodiment, it further includes a user interface module, a data analysis and optimization module, and a network communication module;

[0031] The user interface module is used to provide the operator with real-time viewing of the reservoir liquid level changes, the calculation results of the scheduling model, and the sludge discharge and backwashing information; the user sets the target parameters of the energy-saving mode or the stable mode on the interface according to the user interface module, and the system executes the scheduling task;

[0032] The data analysis and optimization module finds out the water volume relationship and liquid level change law of each process link of the water plant through historical data analysis, and optimizes the scheduling model accordingly;

[0033] The network communication module is used for data communication between various devices in the system; the network communication module is connected to the PLC unit through RSLogix5000 to realize real-time data acquisition and instruction issuance, and through network communication, the system adjusts the water inflow in real time.

[0034] In a preferred embodiment, the data analysis and optimization module predicts the change in reservoir water level based on the scheduling operation data of the water plant as input variables through multiple regression analysis, dynamic time window optimization, and real-time feedback mechanism, and optimizes the adjustment of the water inflow according to the prediction results;

[0035] The data analysis and optimization module formulates the change in reservoir water level through Indicates at time Predicted change in reservoir water level;

[0036]

[0037] Where Is the regression coefficient; Is the number of input variables; Is the Th input variable; Is the dynamic adjustment term;

[0038] Optimize the regression coefficient by minimizing the mean square error MSE , The expression is:

[0039]

[0040] Where Is the actual change in reservoir water level; Is the number of historical data points; Are the parameter sets of the regression coefficient and the adjustment term respectively.

[0041] In a preferred embodiment, for the calculation of the regression coefficient in the data analysis and optimization module, the optimization of the regression coefficient is calculated by the normal equation:

[0042]

[0043]

[0044] Where Is the regression coefficient vector, which represents the influence degree of each input variable on the change in reservoir water level; Is the input matrix, Contains the data of all time steps, each column represents an input variable, and the shape is , Where Is the number of data points; Is the transpose of the input matrix; Is the output vector, and the output vector contains the actual water level change data of each time step, and the shape is , That is, the water level change amount corresponding to each time step.

[0045] In a preferred embodiment, based on the prediction result of the liquid level change in the data analysis and optimization module, by representing the water inflow rate that needs to be adjusted at time , the water inflow rate is calculated;

[0046]

[0047] where represents the output of the regression analysis; is the number of input variables used in the regression analysis; is the index of the input variable;

[0048] Constraints are implemented on the adjustment of the water inflow rate based on the data analysis and optimization module;

[0049]

[0050] where represents taking the valley value between and ; represents taking the peak value between and ;

[0051] Real-time adjustment of the regression coefficients based on the feedback mechanism;

[0052]

[0053] where is the learning rate.

[0054] Technical effects and advantages of the present invention:

[0055] The present invention adopts network communication to integrate and analyze various data of the waterworks, including water inflow and outflow, sludge discharge volume, filter backwash queue and volume, pressure water volume, sampling water volume, reservoir liquid level, etc. Through model calculation, it predicts the water volume change situation in the factory and the water volume adjustment demand, so as to optimize the dispatching plan.

[0056] Utilizing algorithms and control decisions, the artificial experience is summarized into a mathematical model. Through data acquisition, model calculation, and automatic control, it can adjust the water inflow rate in real time and accurately according to the requirements of the company's dispatching center and the operation demand of the waterworks, control the height of the reservoir liquid level, achieve precise regulation of the water volume, improve the dispatching efficiency, and achieve the goal of "unmanned dispatching, low-carbon operation".

[0057] Multiple scheduling modes are set, which is conducive to selection and switching: Energy-saving mode and stable mode are set. According to the operation conditions of the water plant, the corresponding scheduling mode is selected and switched to meet the operation requirements in different periods. The energy-saving mode aims to continuously maintain the reservoir liquid level at a high level, which can achieve the effect of reducing the energy consumption of the effluent. The stable mode aims to keep the total water inflow of the whole plant stable and ensure the stability of water treatment process links such as chemical dosing, inlet water and sludge discharge of the clarifier, inlet water and backwashing of the filter. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is the reservoir liquid level control target diagram of the present invention.

[0059] Figure 2 It is the reservoir liquid level trend diagram of the present invention.

[0060] Figure 3 It is the predicted liquid level and actual liquid level trend diagram of the present invention.

[0061] Figure 4 It is the first upper computer development page of the present invention.

[0062] Figure 5 It is the second upper computer development page of the present invention. SPECIFIC EMBODIMENTS

[0063] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0064] Referring to the attached Figures 1-5 drawings, a smart scheduling system for a waterworks according to an embodiment of the present invention includes a data acquisition module, a scheduling model calculation module, a water inflow adjustment module, and a control instruction issuance module;

[0065] The data acquisition module is used to obtain scheduling operation data in real time from various devices and sensors in the water plant, and perform structured processing on the scheduling operation data in a standardized data format, and transmit it to other modules of the system through network communication; the scheduling operation data includes water inflow, water outflow, sludge discharge water volume, backwashing water volume, sampling water volume, pressure water volume, and reservoir liquid level;

[0066] The scheduling model calculation module is based on the collected scheduling operation data, and performs water volume calculation and liquid level prediction through a preset scheduling evaluation model; the scheduling model calculation module generates corresponding water inflow adjustment instructions according to the water volume calculation and liquid level prediction, so that the reservoir liquid level is maintained within a preset target range;

[0067] The water inflow adjustment module is used to calculate the results according to the scheduling evaluation model, and judge whether it is necessary to adjust the water inflow based on the calculated results, so as to control the reservoir water level;

[0068] The control instruction issuing module realizes data transfer through communication with the PLC unit of the water plant, and obtains the scheduling operation data of the water plant in real time according to the interaction between the PLC unit and the upper computer; the control instruction issuing module obtains the scheduling calculation results according to the adjustment instructions of the scheduling model calculation module, generates corresponding control instructions based on the scheduling calculation results, and transmits them to the PLC to execute the automatic adjustment of the water inflow and water level.

[0069] The scheduling evaluation model of the scheduling model calculation module includes a water volume model, a reservoir water level change model, and a water plant water inflow model;

[0070] The water volume model includes:

[0071] The reservoir water level change model includes:

[0072]

[0073] The water plant water inflow model includes:

[0074]

[0075] Among them is the water inflow of the water plant, with the unit of m³ / h; is the water supply of the water plant, with the unit of m³ / h; is the calculation time, with the unit of h; is the reservoir area, with the unit of m²; is the reservoir water level change, with the unit of m; is the sludge discharge volume, with the unit of m³; is the sludge discharge time, with the unit of h; is the number of filter tanks, which is a pure number without unit; is the backwashing water volume, with the unit of m³; is the sampling water volume, with the unit of m³; is the plant use pressure water volume, with the unit of m³.

[0076] The scheduling logic of the scheduling model calculation module includes:

[0077] Obtain the scheduling operation data based on the data acquisition module; is the calculated value, which is derived from the scheduling model calculation module; is the set value, which is preset by the system or the user; is the collected data, which is obtained by the data acquisition module;

[0078] Determine whether sedimentation tank sludge discharge (according to the set plan), filter backwashing (automatically reading queue data), sampling water volume (constant value), and pressure water volume (constant value) adjustment are required in the next cycle;

[0079] Based on the water intake of the water plant and the water output of the water plant Under the condition of remaining unchanged, the change trend of the reservoir water level is:

[0080]

[0081] Calculate the time when the reservoir water level reaches the control limit , through to represent the difference between the water intake of the water plant and the water supply of the water plant;

[0082]

[0083]

[0084] Determine whether the water intake of the water plant needs to be adjusted: according to the time parameters preset in the system , when , then issue a water intake regulation instruction for the water plant; when , then do not adjust the water intake of the water plant;

[0085] The model obtains the current water level , the target water level at the next determination time , calculate the amount of water that needs to be adjusted for the current water level to reach the target water level within the set time :

[0086]

[0087] When , do not adjust the water intake of the water plant; when , according to Adjust; when , then according to ; where is the minimum adjustable water volume; is the maximum adjustable water volume;

[0088] The calculation of the water volume for this time is completed.

[0089] In the embodiments of the present invention, the acquisition methods of some key parameters used include but are not limited to:

[0090] The water intake of the water plant is collected in real time by an electromagnetic flowmeter installed on the water intake pipeline of the water plant. The collection frequency is 1 time per minute, and the data is transmitted after being standardized by the data acquisition module. The water supply of the water plant is obtained by collecting the flowmeter of the outlet pipe section of the clear water tank of the water plant. The reservoir water level is collected in real time through a reservoir water level sensor with an accuracy of ±1mm. Auxiliary parameters such as backwashing water volume, sludge discharge water volume, sampling water volume, and pressure water volume are predicted by the control program or generated by on-site preset values, and compared and corrected with the actual sampling data.

[0091] It also includes a scheduling mode selection module;

[0092] The scheduling mode selection module includes an energy-saving mode and a stable mode;

[0093] The energy-saving mode is used to continuously maintain the reservoir water level at a high level with the goal of reducing the energy consumption of the outlet water;

[0094] The stable mode is used to keep the water intake stable and make the water treatment process operate stably.

[0095] It also includes a user interface module, a data analysis and optimization module, and a network communication module;

[0096] The user interface module is used to provide the operator with real-time viewing of the reservoir water level changes, the calculation results of the scheduling model, and the sludge discharge and backwashing information. The user sets the target parameters of the energy-saving mode or the stable mode on the interface according to the user interface module, and the system executes the scheduling task;

[0097] The data analysis and optimization module finds out the water volume relationship and water level change law of each process link of the water plant through historical data analysis, and optimizes the scheduling model accordingly to improve the scheduling accuracy of the system;

[0098] The network communication module is used for data communication between various devices in the system. The network communication module is connected to the PLC unit by using RSLogix5000 to realize real-time data collection and instruction issuance. Through network communication, the system adjusts the water intake in real time and ensures the stability of the water plant operation.

[0099] The data analysis and optimization module predicts the change of the reservoir water level through multiple regression analysis, dynamic time window optimization and real-time feedback mechanism, taking the scheduling operation data of the water plant as input variables, and optimizes the adjustment of the water intake according to the prediction results;

[0100] Through the data analysis and optimization module, the change of the reservoir water level is carried out to draw up Indicating at time The predicted change amount of the reservoir water level;

[0101]

[0102] Where is the regression coefficient, which represents the degree of influence of each input variable on the change of reservoir water level. will change dynamically over time and reflects the relationship between the real-time system state and historical data; is the number of input variables; is the th input variable, representing the input factor of a certain scheduling operation data at time ; is the dynamic adjustment term, which includes the error of the system or unpredictable external factors;

[0103] The regression coefficient is optimized by minimizing the mean squared error MSE , and its expression is:

[0104]

[0105] where is the actual change in reservoir water level, that is, the change in reservoir water level actually observed at time ; is the number of historical data points, that is, the number of time steps used to train the regression model; are the parameter sets of the regression coefficient and the adjustment term respectively. Their values will be adjusted when optimizing the objective function to minimize the error.

[0106] For the calculation of the regression coefficient in the data analysis and optimization module, the optimization of the regression coefficient is calculated by the normal equation:

[0107]

[0108]

[0109] where is the regression coefficient vector, which represents the degree of influence of each input variable on the change of reservoir water level; is the input matrix, which contains the data of all time steps. Each column represents an input variable, and its shape is , where is the number of data points; is the transpose of the input matrix, which is used to calculate the regression coefficient; is the output vector, and the output vector contains the actual water level change data of each time step, with a shape of , that is, the water level change amount corresponding to each time step.

[0110] Based on the prediction result of the water level change in the data analysis and optimization module, through represents at time The water inflow that needs to be adjusted at all times for calculating the water inflow;

[0111]

[0112] Among them Represents the output of the regression analysis, which is the weighted sum of the influence of each process water volume on the reservoir water level in the dispatching operation data after adjustment by the regression coefficient; Is the number of input variables used in the regression analysis; Is the index of the input variable;

[0113] Constraints are implemented on the adjustment of the water inflow based on the data analysis and optimization module;

[0114]

[0115] Among them Represents taking and The valley value between; Represents taking and The peak value between;

[0116] Real-time adjustment of the regression coefficient based on the feedback mechanism;

[0117]

[0118] Among them Is the learning rate, which is used to control the speed of the regression coefficient adjustment, and its value ranges from 0 to 1;

[0119] Regarding the above solution, it should be noted that the role of the data acquisition module is to collect relevant operation data from various equipment and sensors in the water plant in real time through the network communication system, such as water inflow, water supply volume, sludge discharge volume, backwashing water volume, etc.; these data will be transmitted to other modules of the system after being standardized to provide accurate basic data for subsequent calculations; the timeliness and accuracy of data acquisition are the premise for the effective operation of the entire dispatching system. Especially in a complex water plant environment, the real-time update of data enables the system to quickly respond to changes and make adjustments;

[0120] The dispatching model calculation module calculates the water volume and predicts the water level based on the collected data. It predicts the change of the reservoir water level by using complex algorithms and models and generates corresponding water inflow adjustment instructions; the prediction of the water level not only ensures that the reservoir water level is always maintained within a safe range, but also can dynamically adjust the water volume according to different process requirements to improve the operation efficiency of the water plant; for example, in certain periods, the water plant may need more water inflow to cope with the peak demand, and in the energy-saving mode, the control of the water inflow is more precise to reduce energy consumption;

[0121] The water inflow adjustment module determines whether to adjust the water inflow based on the results of the scheduling model calculation module; it not only automatically calculates the water inflow but also determines whether adjustment is needed according to actual situations (such as sludge discharge, backwashing, etc.); for situations where the reservoir water level changes significantly, the system can automatically adjust the water inflow, avoiding manual intervention, reducing the occurrence of human errors, avoiding water resource waste, and ensuring the stable operation of the water plant;

[0122] The control instruction issuing module realizes the automatic adjustment of the water inflow and water level through the communication interface with the PLC unit; as the core of the water plant automation control system, the PLC unit can receive instructions from the scheduling model calculation module and adjust the opening degree of the water flow valve in real time, thereby controlling the water inflow and water level;

[0123] The settings of the energy-saving mode and stable mode in the scheduling mode selection module can be automatically switched according to different operation requirements; for example, during the peak demand period, the system will switch to the stable mode to ensure the stable operation of various water treatment processes in the water plant; while during the non-peak period, the energy-saving mode reduces the energy consumption of the effluent by maintaining a high reservoir water level. This mode switching not only improves the flexibility of the water plant operation but also optimizes the utilization of resources;

[0124] The data analysis and optimization module can not only predict the changes in the reservoir water level through multiple regression analysis, dynamic time window optimization, and real-time feedback mechanism but also optimize the scheduling model according to historical data, making the adjustment of the water inflow relatively more accurate; when long-term scheduling optimization is required, it can use historical data to find the operation rules of the water plant and make real-time adjustments to the scheduling strategy;

[0125] The network communication module ensures the data interaction of each device in the system through the connection between RSLogix5000 and the PLC unit; this module provides efficient communication support for the system, making the transmission of real-time data and the issuance of instructions possible, and further enhancing the automation level of the system;

[0126] In addition, regarding network communication and scheduling logic programming, it should be noted that according to the determined scheduling logic, a scheduling model is established. First, through an Ethernet connection, RSLogix5000 is used to connect to the raw water PLC (L32E series), and an MSG instruction is added to establish communication between PLCs, and relevant parameters of the filter PLC (L61 series) and alum addition PLC (L551C series) are read to achieve real-time acquisition of the parameters required for model calculation;

[0127] After establishing the communication, programming is carried out in the raw water PLC, with a total of 6 programs, divided into 1 main program that calls a subroutine and 5 subroutines that implement functions:

[0128] 1) Main program: Call the sub-function program;

[0129] 2) Mode Selection: It is divided into automatic mode and manual mode. The automatic mode means using the scheduling model for automatic calculation, and the stable mode or energy-saving mode can be selected. The energy-saving mode aims to continuously maintain the reservoir water level at a high level to reduce the energy consumption of the effluent. The stable mode aims to keep the total water inflow of the whole plant stable. Through the regulation function of the clear water tank, it ensures the stability of water treatment processes such as chemical dosing, inlet water of the clarifier and sludge discharge, inlet water of the filter and backwashing; The manual mode means switching to the traditional manual scheduling.

[0130] 3) Parameter Setting: Manually set the target parameters and limit parameters of the energy-saving mode / stable mode; According to the operation situation, set the sludge discharge plan half an hour in advance; Read the operation time of the filter, and consider the backwashing water consumption in advance for model calculation.

[0131] 4) Backwashing Water Volume Calculation: When the filter runs for 48 hours, start to lift the backwashing water to the water tower. By reading the operation time of the filter, consider the required backwashing water volume half an hour in advance.

[0132] 5) Sludge Discharge Water Volume Calculation: Half an hour before sludge discharge, the operator inputs the sludge discharge signal on the upper computer, and the model starts to calculate the sludge discharge water consumption half an hour later.

[0133] 6) Valve Opening Calculation and Control: Through the backwashing water consumption and sludge discharge water consumption in the backwashing water volume calculation and sludge discharge water volume calculation, as well as parameters such as the inlet and outlet water flow rates and the reservoir water level, calculate the time t1 when the reservoir water level reaches the target water level and the water inflow that needs to be adjusted, control the valve opening, and adjust multiple times to gradually approach this water inflow, so as to achieve the goal of automatically scheduling the water inflow according to the water supply volume, the reservoir water level target, and the intermediate process loss water volume, reducing the workload of the operators, and effectively improving the scheduling accuracy and water supply efficiency.

[0134] Regarding the page development, after completing the scheduling logic programming work, add an intelligent scheduling interface on the upper computer, including the input of "energy-saving mode" and "stable mode" parameters, the relevant calculated values of the model, the sludge discharge and backwashing situations, the reservoir water level trend chart, etc. The operator can set the relevant parameters on the upper computer, and the model automatically calculates and issues control instructions through the PLC to adjust the water inflow.

[0135] For Figures 1-3 the operation data analysis results, it should be noted that the implementation method of the present invention mainly collects production operation data in real time through network communication, establishes a scheduling model through programming in the water plant industrial control network, and performs real-time collection and automatic calculation to replace manual operations.

[0136] Figures 1-3 The abscissa in Figures 1-3 is time,

[0137] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent scheduling system for a waterworks, comprising a data acquisition module, a scheduling model calculation module, a water inflow adjustment module, and a control instruction issuing module, characterized in that: The data acquisition module is used to obtain scheduling operation data in real time from various devices and sensors in the waterworks, perform structured processing on the scheduling operation data in a standardized data format, and transmit it to other modules of the system through network communication; the scheduling operation data includes water inflow, water outflow, sludge discharge volume, backwashing water volume, sampling water volume, pressure water volume, and reservoir liquid level; The scheduling model calculation module calculates the water volume and predicts the liquid level based on the collected scheduling operation data through a preset scheduling evaluation model; the scheduling model calculation module generates corresponding water inflow adjustment instructions according to the water volume calculation and liquid level prediction to keep the reservoir liquid level within a preset target range; The water inflow adjustment module is used to judge whether it is necessary to adjust the water inflow according to the calculation result of the scheduling evaluation model and control the reservoir liquid level based on the calculated result; The control instruction issuing module realizes data transfer through communication with the PLC unit of the waterworks, obtains the scheduling operation data of the waterworks in real time based on the interaction between the PLC unit and the upper computer; the control instruction issuing module obtains the scheduling calculation result according to the adjustment instruction of the scheduling model calculation module, generates corresponding control instructions based on the scheduling calculation result, and transmits them to the PLC to perform automatic adjustment of the water inflow and liquid level; The scheduling evaluation model of the scheduling model calculation module includes a water volume model; The water volume model includes: (Q 进 -Q 供 )×Δt = S 水库 × Δh 水库 + Q 排泥 × t 排泥 + n × Q 反冲 + Q 采样水 + Q 压力水 Among which Q 进 is the water intake of the water plant; Q 供 is the water supply of the water plant; Δt is the calculation time; S 水库 is the reservoir area; Δh 水库 is the change in reservoir water level; Q 排泥 is the sludge discharge volume; t 排泥 is the sludge discharge time; n is the number of filter tanks; Q 反冲 is the backwashing water volume; Q 采样水 is the sampling water volume; Q 压力水 is the water volume for plant use pressure; The scheduling logic of the scheduling model calculation module includes: Obtain the scheduling operation data based on the data acquisition module; Judge whether it is necessary to adjust the sludge discharge of the sedimentation tank, backwashing of the filter, sampling water volume, and pressure water volume in the next cycle; Based on the water intake of the water plant and the water output Q of the water plant 出 Under the condition of unchanged, the changing trend h of the reservoir water level t is as follows: Calculate the time t1 when the reservoir liquid level reaches the control limit, through Q 差值 which refers to the difference between the water intake of the waterworks and the water supply of the waterworks; Q 差值 = Q 进 -Q 供 Determine whether it is necessary to adjust the water intake of the water plant: according to the preset time parameter t of the system 调 , when t1≥t 调 , then issue a water intake regulation instruction for the water plant; when t1<t 调 , then do not adjust the water intake of the water plant; The model obtains the current liquid level h 当前 and the target liquid level h at the next determination time 目标 , and calculates the amount of water Q that needs to be adjusted for the current liquid level to reach the target liquid level within the set time 需 : When |Q 需 | ≤ Q 低 , the water intake of the water plant is not adjusted; when Q 低 ≤ |Q 需 | ≤ Q 高 , it is adjusted according to Q 需 ; when |Q 需 | > Q 高 , then it is according to Q 高 ; where Q 低 is the minimum adjustable water volume; Q 高 is the maximum adjustable water volume; The current water volume calculation is completed; It further includes a user interface module, a data analysis and optimization module, and a network communication module; The user interface module is used to provide the operator with real-time viewing of the reservoir liquid level change, scheduling model calculation result, and sludge discharge and backwashing information; the user sets the target parameters of the energy-saving mode or stable mode on the interface according to the user interface module, and the system executes the scheduling task; The data analysis and optimization module finds out the water volume relationship and liquid level change law of each process link in the waterworks through historical data analysis, and optimizes the scheduling model accordingly; The network communication module is used for data communication between various devices in the system; the network communication module is connected to the PLC unit through RSLogix5000 to realize real-time data acquisition and instruction issuing, and the system adjusts the water inflow in real time through network communication.

2. An intelligent scheduling system for a waterworks according to claim 1, characterized in that: It further includes a scheduling mode selection module; The scheduling mode selection module includes an energy-saving mode and a stable mode; The energy-saving mode is used to continuously maintain the reservoir liquid level at a high level with the goal of reducing the energy consumption of the effluent; The stable mode is used to keep the water inflow stable and make the water treatment process operate stably.

3. An intelligent scheduling system for a waterworks according to claim 2, characterized in that: The data analysis and optimization module, through multiple regression analysis, dynamic time window optimization, and real-time feedback mechanism, uses the scheduling operation data of the water plant as input variables to predict the change of the reservoir water level and optimize the adjustment of the water inflow according to the prediction results; The reservoir liquid level change is carried out by the data analysis and optimization module, and it is proposed that represents the predicted change amount of the reservoir liquid level at time t; where β i (t) is the regression coefficient; s is the number of input variables; X i (t) is the i-th input variable; α(t) is the dynamic adjustment term; Optimize the regression coefficient β by minimizing the mean square error MSE i (t), and its expression is: wherein is the actual reservoir liquid level change; S is the number of historical data points; β(t) and α(t) are the parameter sets of the regression coefficient and the adjustment term, respectively.

4. A smart scheduling system for a waterworks according to claim 3, wherein: For the calculation of the regression coefficients in the data analysis and optimization module, the optimization of the regression coefficients is calculated by the normal equation: β = (X T X) -1 X T Y β＝[β0,β1,…,β6] T where β = [β0, β1, …, β6] T is the regression coefficient vector, which represents the influence degree of each input variable on the change of reservoir water level; X is the input matrix, X contains the data of all time steps, each column represents an input variable, and the shape is n×7, where n is the number of data points; X T is the transpose of the input matrix; Y is the output vector, and the output vector contains the actual water level change data of each time step, and the shape is n×1, that is, the water level change amount corresponding to each time step.

5. A smart scheduling system for a waterworks according to claim 4, wherein: Based on the prediction results of the liquid level change in the data analysis and optimization module, through Q 进 (t) represents the water inflow that needs to be adjusted at time t to calculate the water inflow; wherein represents the output of the regression analysis; m is the number of input variables used in the regression analysis; i is the index of the input variable; Based on the data analysis and optimization module, constraints are imposed on the adjustment of the water inflow; Q 进 = min(Q 进 , Q 高 ) if Q 进 > Q 高 Q 进 = max(Q 进 , Q 低 ) if Q 进 < Q 低 where min represents taking the valley value between Q 进 and Q 高 ; max represents taking the peak value between Q 进 and Q 低 ; Based on the feedback mechanism, real-time adjustment of the regression coefficients; where γ is the learning rate.

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