Cooperative scheduling method for integrated sponge city water storage and drainage system

Abstract

The invention relates to the technical field of municipal engineering and water resource management, in particular to an integrated sponge city water storage and drainage system collaborative scheduling method, which comprises the steps of acquiring multi-source heterogeneous sensing data and extracting a state difference vector, constructing a dynamic response feature combination, judging facility regulation and control attributes, and revising output parameters to generate a scheduling instruction. And the matching control channel issues tasks, and evaluates system scheduling performance in combination with a response process. Structural aggregation is completed by extracting state difference vectors of various facilities and judging the change direction, main and auxiliary attributes are divided in combination with response characteristics, control output is dynamically revised according to the storage and drainage rate and the water level deviation, a control channel is matched to issue a scheduling instruction, and multi-facility linkage response is carried out in a unified rhythm. The regulation adaptability is evaluated in combination with the scheduling holding time and the state deviation, and regulation actions among facilities are promoted to be coordinated, the water level regulation rhythm is consistent, and the water resource distribution process is coordinated in a rapid change scene of the rain condition.

Description

Technical Field

[0001] This invention relates to the field of municipal engineering and water resource management technology, and in particular to a method for coordinated scheduling of an integrated sponge city water storage and drainage system. Background Technology

[0002] With the deepening of the sponge city construction concept, urban water storage and drainage systems are transforming from the traditional "rapid drainage" model to an integrated and coordinated regulation approach encompassing infiltration, retention, storage, purification, utilization, and drainage. The integrated sponge city water storage and drainage system coordinated scheduling method aims to achieve dynamic optimization management of the entire rainfall runoff process by coordinating multiple elements such as the surface, pipe network, storage facilities, and receiving water bodies, thereby improving urban flood control and water resource utilization efficiency. However, existing technologies still have significant shortcomings in terms of system integration, scheduling response accuracy, and multi-objective coordination capabilities. A search revealed a patent, CN111798108B, which discloses a coordinated scheduling method for urban drainage areas. This patent dynamically adjusts the number and frequency of pumps by adjusting the pump station liquid level control value in real time, thereby achieving proactive storage at the pump station and reducing regional overflow pollution. However, this technical solution mainly focuses on the local optimization of drainage pumping stations, without fully incorporating the source retention function of sponge facilities (such as permeable pavement, rain gardens, green roofs, etc.), and also lacks coupled modeling of the entire process of surface runoff generation and collection, pipeline transmission and end-of-pipe discharge. It is difficult to support the coordinated scheduling of the entire chain of "source-process-end", which limits its applicability in the complex multi-source system of sponge cities.

[0003] On the other hand, a scheduling decision-making method and system applicable to integrated management of plants, networks, and rivers was disclosed in patent CN119047724B. This patent constructs an integrated mechanism model of "plant-station-network-river" covering surface runoff, pipe network, river network, sewage treatment plant, and regulating reservoir, realizing full-process simulation and coordinated control of water quantity and quality. Although the solution is relatively comprehensive in terms of system coverage, its core still revolves around traditional sewage and combined sewer overflow management. It does not adequately consider the dynamic response characteristics, storage and discharge conversion mechanisms, and linkage scheduling strategies with gray infrastructure unique to sponge cities, and it does not specifically design for rapid response and multi-objective (flood prevention, water conservation, water quality protection) trade-off optimization under short-duration heavy rainfall events, making it difficult to meet the needs of sponge cities for efficient and flexible operation under extreme weather conditions.

[0004] The aforementioned problems indicate that existing technologies are either limited to the regulation of a single facility level, or, although they have constructed wide-area models, lack refined integration of the dynamic characteristics of sponge city facilities, and have not yet formed an integrated collaborative scheduling method covering the entire chain of "source reduction - process control - end-of-pipe storage - receiving water body protection". Therefore, this invention proposes an integrated collaborative scheduling method for sponge city water storage and drainage systems, aiming to integrate the dynamic response mechanisms of multi-source heterogeneous facilities, construct a high-precision, fast-response, multi-objective collaborative intelligent scheduling system, and comprehensively improve the resilience and resource utilization level of sponge cities under complex rainfall scenarios. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a method for the coordinated scheduling of an integrated sponge city water storage and drainage system. The technical solution is as follows:

[0006] A collaborative scheduling method for an integrated sponge city water storage and drainage system includes the following steps:

[0007] S1: Acquire multi-source heterogeneous sensing data of the target area within a continuous sampling period during a rainfall event. The multi-source heterogeneous sensing data includes rainfall intensity sequence, surface runoff generation and confluence state sequence, pipeline load sequence, and storage facility operation parameter sequence. Extract the state change of each subsystem between the current sampling period and the previous sampling period, construct a state difference vector set, and determine the state change direction of each subsystem through sign discrimination. Perform structured aggregation according to subsystem type to generate system dynamic response feature combination results.

[0008] S2: Based on the combined results of the system dynamic response characteristics, set the conditions for the establishment of LID-grey facility coupling response. When all conditions are met, mark the corresponding facility as having the ability to participate in coordinated scheduling and mark it as the leading control unit. Otherwise, mark it as an auxiliary response unit and obtain the effective flag information of facility coordinated scheduling.

[0009] S3: Based on the effective flag information of the facility coordinated scheduling, determine the storage and discharge conversion rate of the current cycle's dominant control unit and calculate its dynamic adjustment potential, extract the deviation value between the target water level and the current actual water level in the previous cycle of the auxiliary response unit, synchronously correct the control output parameters of the dominant control unit and update the scheduling task instructions, and obtain the content of the dominant side scheduling execution instructions.

[0010] S4: Based on the content of the dominant side scheduling execution instruction, match the scheduling target with the various facility control channel identifiers recorded in the preset facility control mapping table, locate the current effective control channel and complete the instruction issuance, and obtain the multi-facility collaborative response content;

[0011] S5: Based on the multi-facility coordinated response content, determine the dynamic matching relationship between the scheduling hold time and the range of system state deviation changes within the current cycle, and output the system coordinated scheduling performance evaluation record.

[0012] As a further aspect of the present invention, the conditions for the establishment of the LID-grey facility coupling response are as follows: First, the facility status activity is determined when the absolute value of the change in the status of the corresponding facility in the current period is greater than a preset threshold; Second, the LID-pipeline network coordination relationship is determined when the direction of change in the storage status of the LID facility is negatively correlated with the direction of change in the load of the downstream pipeline network; Third, the regulation-discharge coordination relationship is determined when the rate of change in the water level of the regulation facility is logically consistent with the change in the start-stop status of the terminal discharge facility.

[0013] As a further aspect of the present invention, the effective control channel specifically refers to a corresponding channel whose facility type, as indicated by the channel identifier, matches the facility function category specified in the dominant side dispatch instruction.

[0014] As a further aspect of the present invention, the combined results of the system dynamic response characteristics include rainfall driving intensity characteristics, surface response lag index, pipeline load fluctuation characteristics, and storage facility capacity utilization trend. The effective indicator information of facility collaborative scheduling includes facility status activity label, coupled response capability index, and scheduling intervention priority. The content of the dominant side scheduling execution instruction includes the dominant facility control weight, flow allocation ratio, and water level regulation bias. The content of the multi-facility collaborative response includes instruction execution delay time, facility action trajectory, and regulation path activation status. The system collaborative scheduling performance evaluation record includes multi-objective balance index, state deviation convergence rate, and duration of continuous effectiveness of scheduling strategy.

[0015] As a further aspect of the present invention, the specific steps for obtaining the system dynamic response feature combination result are as follows:

[0016] S111: Obtain the rainfall intensity sequence of the target area within a continuous sampling period during the rainfall event, extract the rainfall intensity values ​​of the current period and the previous period respectively, construct the rainfall intensity difference vector, and determine the rainfall intensity change trend by judging the sign of the difference, and generate a rainfall-driven feature set;

[0017] S112: Based on the surface runoff generation and collection state sequence, pipeline load sequence, and storage facility operation parameter sequence, extract the corresponding state values ​​between the current cycle and the previous cycle, construct the surface state difference set, pipeline load difference set, and storage parameter difference set, and represent the state change direction of each subsystem by comparing the difference signs, and jointly output the direction marking information of each subsystem in the current cycle to obtain the subsystem state direction determination set;

[0018] S113: Based on the rainfall-driven feature set and the subsystem state direction determination set, the state change directions of the four types of elements—rainfall, surface, pipeline, and storage—are structurally aggregated to form a four-element state vector for each element in the current cycle. The multi-element state vectors are then sequentially concatenated into a system-level dynamic response sequence to generate a system dynamic response feature combination result.

[0019] As a further aspect of the present invention, the specific steps for obtaining the effective flag information for facility coordinated scheduling are as follows:

[0020] S211: Based on the combined results of the system dynamic response features, extract the absolute value of the state change of various facilities within the current sampling period, determine whether it is greater than a preset threshold, output the facility active state flag if it is greater than the threshold, otherwise output the facility silent state flag, and obtain the facility active state judgment set by setting the state activity judgment of various facilities respectively.

[0021] S212: Based on the combined results of the system dynamic response features, extract the direction of change of LID facility storage capacity and the direction of change of downstream pipeline load, perform a sign negative correlation test, if the negative correlation is satisfied, mark it as the LID-pipeline network coordination relationship is established, otherwise mark it as not established, combine the multi-point test results to generate an LID-pipeline network coordination consistency flag sequence.

[0022] S213: Based on the facility activity determination set and the LID-pipeline network coordination consistency flag sequence, extract the logical relationship between the rate of change of water level of the storage facility and the start-stop status change of the terminal discharge facility. If the three conditions of facility activity, LID-pipeline network coordination, and storage-discharge logic consistency are met simultaneously, then mark the corresponding facility as the leading control unit; otherwise, mark it as an auxiliary response unit and obtain the effective flag information of facility coordinated scheduling.

[0023] As a further aspect of the present invention, the specific steps for obtaining the content of the dominant side scheduling execution instruction are as follows:

[0024] S311: Based on the facilities marked as the dominant control unit in the facility coordinated scheduling effective flag information, extract the water storage and drainage volume data of the corresponding facilities in two consecutive cycles, perform differential processing based on the data of the current cycle and the previous cycle, and calculate the ratio of the difference with the unit time to obtain the water storage and drainage conversion rate and the direction of change, and generate a set of dynamic adjustment potential parameters for the dominant unit.

[0025] S312: Based on the water level data corresponding to the facilities marked as auxiliary response units in the effective flag information of facility coordinated scheduling, extract the target water level of the previous period and the actual water level of the current period, calculate the water level deviation through the difference between the two, and obtain the auxiliary unit state error characteristic quantity.

[0026] S313: Based on the dynamic adjustment potential parameter set of the leading unit and the state error characteristic quantity of the auxiliary unit, calculate the flow redistribution ratio and correct the current control output of the leading control unit. At the same time, update the facility scheduling task instruction set, aggregate the current control weight and scheduling bias parameter, and obtain the content of the leading side scheduling execution instruction.

[0027] As a further aspect of the present invention, the specific steps for obtaining the multi-facility collaborative response content are as follows:

[0028] S411: Based on the scheduling target specified in the content of the dominant side scheduling execution instruction, retrieve the various facility control channel identifiers recorded in the preset facility control mapping table, construct the corresponding mapping relationship between the scheduling target and the channel identifier, and store the mapping relationship in a structured manner as a control channel index unit to obtain the facility control channel mapping index set;

[0029] S412: Based on the facility control channel mapping index set, extract the facility function category information corresponding to each channel identifier, and at the same time read the facility function requirements specified in the main side scheduling execution instruction content. Compare whether the category attributes of the two are consistent. If they are consistent, mark it as a valid control channel and establish a list of current valid control channels.

[0030] S413: Based on the current list of effective control channels, write the control parameters in the execution instruction content of the dominant side scheduling to the execution buffer of the corresponding channel, activate the instruction writing status register to complete the instruction issuance process, update the current channel response status flag set, and obtain the multi-facility collaborative response content.

[0031] As a further aspect of the present invention, the specific steps for obtaining the system collaborative scheduling performance evaluation record are as follows:

[0032] S511: Based on the multi-facility coordinated response content, extract the actual system state trajectory fed back by each control channel in the current scheduling cycle and the target state trajectory set in the scheduling task, perform trajectory overlap segment length statistics according to the time axis, calculate the continuous state matching time value, and obtain the state trajectory matching duration set.

[0033] S512: Based on the facility action parameters in the multi-facility coordinated response content, the actual facility behavior of each channel under the target control direction is judged by the action consistency mark within the period. If the action mark of consecutive sampling points remains the same, it is recorded as consistent action, and a system action response consistency sequence is established.

[0034] S513: Based on the consistency sequence of the state trajectory matching duration and the system action response, combined with the continuous scheduling hold time and the range of system state deviation changes within the current scheduling cycle, evaluate the dynamic trend matching relationship between various parameters, and output them as scheduling execution performance parameters to obtain the system collaborative scheduling performance evaluation record.

[0035] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0036] In this invention, the state difference vectors of various facilities in multi-source heterogeneous data are extracted and combined with the direction of change to complete structural aggregation. The facilities are divided into primary and secondary attributes based on response characteristics. The control output is dynamically revised according to the storage and discharge conversion rate of the dominant unit and the water level deviation of the auxiliary unit. The control channel is matched to complete the command interaction. The response process of multiple facilities is incorporated into the unified scheduling rhythm. The matching of scheduling maintenance time and state deviation is fed back, and a full-process collaborative mechanism is constructed. In the scenario of rapid evolution of rainfall response rhythm, the control actions of various facilities are kept coordinated, the control range is adaptable, and the water resource allocation process is coordinated. Attached Figure Description

[0037] Figure 1 This is a flowchart of the method of the present invention;

[0038] Figure 2 This is a flowchart illustrating the acquisition process of S1 in this invention;

[0039] Figure 3 This is a flowchart illustrating the acquisition process of S2 in this invention;

[0040] Figure 4 This is a flowchart illustrating the acquisition process of S3 in this invention;

[0041] Figure 5 This is a flowchart illustrating the acquisition process of S4 in this invention;

[0042] Figure 6 This is a flowchart of the acquisition process for S5 of the present invention. Detailed Implementation

[0043] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0044] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0045] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0046] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0047] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0048] Please see Figure 1 This invention provides a technical solution: a method for coordinated scheduling of an integrated sponge city water storage and drainage system, comprising the following steps:

[0049] S1: Acquire multi-source heterogeneous sensing data of the target area within a continuous sampling period during rainfall events. The multi-source heterogeneous sensing data includes rainfall intensity sequences, surface runoff generation and confluence state sequences, pipeline load sequences, and storage facility operation parameter sequences. Extract the state change of each subsystem between the current sampling period and the previous sampling period, construct a state difference vector set, and determine the state change direction of each subsystem through sign discrimination. Perform structured aggregation according to subsystem type to generate system dynamic response feature combination results.

[0050] S2: Based on the combined results of the system's dynamic response characteristics, the following conditions are set for the establishment of LID-grey facility coupling response: First, the facility's activity level is determined when the absolute value of the change in the corresponding facility's status within the current period is greater than a preset threshold; Second, the LID-pipeline network coordination relationship is determined when the direction of change in the LID facility's storage status is negatively correlated with the direction of change in the downstream pipeline network load; Third, the regulation-discharge coordination relationship is determined when the rate of change in the water level of the regulation facility and the change in the start-stop status of the terminal discharge facility maintain logical consistency. When all three conditions are met, the corresponding facility is marked as having the ability to participate in coordinated scheduling and is marked as the leading control unit; otherwise, it is marked as an auxiliary response unit, and the effective flag information for facility coordinated scheduling is obtained.

[0051] S3: Based on the effective flag information of facility coordinated scheduling, determine the storage and discharge conversion rate of the current cycle's dominant control unit and calculate its dynamic adjustment potential. Extract the deviation between the target water level and the current actual water level of the auxiliary response unit in the previous cycle. Simultaneously correct the control output parameters of the dominant control unit and update the scheduling task instructions. Obtain the content of the dominant side scheduling execution instructions.

[0052] S4: Based on the content of the dispatch execution instruction from the master side, match the dispatch target with the various facility control channel identifiers recorded in the preset facility control mapping table, locate the currently effective control channel and complete the instruction issuance, and obtain the multi-facility collaborative response content;

[0053] S5: Based on the multi-facility coordinated response content, determine the dynamic matching relationship between the scheduling hold time and the range of system state deviation changes within the current cycle, and output the system coordinated scheduling performance evaluation record.

[0054] The combined results of the system's dynamic response characteristics include rainfall driving intensity characteristics, surface response lag index, pipeline load fluctuation characteristics, and storage facility capacity utilization trend. Effective information for facility coordinated scheduling includes facility status activity labels, coupled response capability index, and scheduling intervention priority. The content of the dominant side's scheduling execution instructions includes the dominant facility control weight, flow allocation ratio, and water level regulation bias. The content of multi-facility coordinated response includes instruction execution delay time, facility action trajectory, and regulation path activation status. The system coordinated scheduling performance evaluation record includes multi-objective balance index, state deviation convergence rate, and duration of continuous effectiveness of scheduling strategy.

[0055] Please see Figure 2 The specific steps of S1 are as follows:

[0056] S111: Obtain the rainfall intensity sequence of the target area within a continuous sampling period during the rainfall event, extract the rainfall intensity values ​​of the current period and the previous period respectively, construct the rainfall intensity difference vector, and determine the rainfall intensity change trend by judging the sign of the difference, and generate a rainfall-driven feature set;

[0057] Data is collected through IoT sensor nodes deployed within the target area. The data collection targets include meteorological monitoring stations, surface runoff monitoring points, key nodes in underground pipe networks, and the control center of water storage reservoirs. The collection frequency is set to a 5-minute cycle to ensure data continuity and timeliness. For processing the rainfall intensity sequence, the current rainfall data is first read using a high-precision tipping bucket rain gauge and converted into an intensity value in millimeters per hour. Simultaneously, the rainfall intensity record from the previous sampling cycle is retrieved from memory. Before entering the processing flow, the data undergoes a data cleaning process, using Z-score standardization to remove abnormal jump values ​​caused by sensor malfunctions. Specifically, this process calculates the mean and standard deviation within a sliding window. If the deviation between the current reading and the mean exceeds three times the standard deviation, the data from the previous moment is used for smoothing. Subsequently, the process performs a difference calculation, subtracting the rainfall intensity value from the previous cycle from the current cycle's rainfall intensity value. If the difference is positive, rainfall is considered to be increasing; if the difference is negative, rainfall is considered to be decreasing; if the difference is 0, rainfall is considered to be continuing. This series of judgments is encoded into a rainfall-driven feature vector. For example, if the current period's rainfall intensity is 30 mm / hour and the previous period's was 20 mm / hour, the difference obtained after subtraction is 10 mm / hour, the sign is determined to be positive, and the generated rainfall driving feature value is 1.

[0058] S112: Based on the surface runoff generation and collection state sequence, pipeline load sequence, and storage facility operation parameter sequence, extract the corresponding state values ​​between the current cycle and the previous cycle, construct the surface state difference set, pipeline load difference set, and storage parameter difference set, and represent the state change direction of each subsystem by comparing the difference signs, and jointly output the direction marking information of each subsystem in the current cycle to obtain the subsystem state direction determination set;

[0059] For surface runoff generation, the depth of surface water is monitored using a level radar, and the difference between the current water depth and the previous cycle's water depth is extracted. For pipeline load, the internal pressure value of the pipeline is obtained through a pressure transmitter, and the pressure change is calculated. For water storage facilities, the water level height of the storage tank fed back by an ultrasonic level gauge is read, and the water level change is calculated. This process extracts symbols from the above three sets of differences. If the water depth difference is positive, it indicates an increase in surface runoff; if the pipeline pressure difference is negative, it indicates a release of pipeline load; if the water storage level difference is positive, it indicates that the facility is storing water. This symbolic information is summarized to generate a subsystem state direction determination set.

[0060] S113: Based on the rainfall-driven feature set and the subsystem state direction determination set, the state change directions of the four types of elements, namely rainfall, surface, pipeline, and storage, are structurally aggregated to form a four-element state vector of each element in the current cycle. The multi-element state vectors are sequentially spliced ​​into a system-level dynamic response sequence to generate the system dynamic response feature combination result.

[0061] A quaternary state vector is constructed, with its four dimensions corresponding to rainfall trend, surface runoff trend, pipeline load trend, and water storage operation trend, respectively. This process involves concatenating the quaternary vectors at each moment according to timestamp indexes to form a long-term, system-level dynamic response sequence. Table 1 shows the monitoring data and processing results for three consecutive cycles during a rainfall event.

[0062] Table 1: Multi-source sensing data and state feature extraction table for urban drainage system

[0063]

[0064] As shown in Table 1, at time T2, the rainfall intensity increased by 10 mm / h compared to T1, the pipeline pressure increased by 15 kPa, and the storage water level rose by 0.30 meters. All components showed positive growth, therefore the state vector was encoded as a sequence of all 1s, representing the system being in a full-load loading phase. At time T3, the rainfall weakened, the pipeline pressure decreased, but the storage water level continued to rise, reflecting the lag effect after the rainfall peak. This combined result constitutes the system's dynamic response characteristic combination, providing a quantitative state basis for subsequent scheduling decisions.

[0065] Please see Figure 3 The specific steps of S2 are as follows:

[0066] S211: Based on the combined results of the system dynamic response features, extract the absolute value of the state change of various facilities within the current sampling period, determine whether it is greater than the preset threshold, output the facility active state flag if it is greater than the preset threshold, otherwise output the facility silent state flag, and obtain the facility active state judgment set by setting the state activity judgment of various facilities respectively.

[0067] The system reads the absolute value of the status change for each type of facility in the current cycle and compares it with a preset silence threshold. This threshold is determined based on the facility's historical operating noise level; for example, by analyzing the liquid level fluctuation data during rainless periods in the past year, its standard deviation is calculated, and three times the standard deviation is set as the silence threshold. For the water level of the regulating reservoir, if the absolute value of the current change is less than 0.05 meters, it is judged as silent, considered as sensor jitter or minor natural fluctuations; if it is greater than or equal to 0.05 meters, it is judged as active. Only facilities in an active state have the value and urgency to be regulated. For example, if the soil moisture content change of a rain garden is 2%, which is greater than the set threshold of 1.5%, the facility is marked as active.

[0068] S212: Based on the combined results of system dynamic response characteristics, extract the direction of change of LID facility storage capacity and the direction of change of downstream pipeline load, perform a sign negative correlation test, if the negative correlation is satisfied, mark it as the LID-pipeline network coordination relationship is established, otherwise mark it as not established, combine the test results of multiple points to generate the LID-pipeline network coordination consistency flag sequence.

[0069] Extract the sign of the change in storage capacity of the LID facility and the sign of the change in load of the downstream pipeline network. A "negative correlation" means that the trends of the two changes can cancel each other out or alleviate each other. The specific judgment logic is as follows: If the LID facility is in a "water absorption" state, i.e., the storage capacity increases, and the change direction is positive; if the downstream pipeline network load is in a "increasing" state, and the change direction is also positive, then the two are moving in the same direction, indicating that the LID absorption has failed to effectively curb the increase in pipeline network load, or that the two have not formed an effective complementarity, and the synergy is not established. Conversely, if the LID facility strongly absorbs water, while the downstream pipeline network load begins to decrease, and the change direction is negative, then the positive and negative signs multiply to a negative value, and the negative correlation is established, i.e., the LID-pipeline network synergy relationship is established. This logic is implemented through XOR operations or product sign judgment to ensure that the source facility is effectively sharing the pressure at the end.

[0070] S213: Based on the facility activity judgment set and the LID-pipeline network coordination consistency flag sequence, extract the logical relationship between the rate of change of water level of the storage facility and the start-stop status change of the terminal discharge facility. If the three conditions of facility activity, LID-pipeline network coordination, and storage-discharge logic consistency are met at the same time, the corresponding facility is marked as the dominant control unit; otherwise, it is marked as the auxiliary response unit, and the effective flag information of facility coordinated scheduling is obtained.

[0071] The process extracts the rate of water level change in the storage and regulation facilities and the start / stop status of the terminal discharge pumping stations. Logical consistency means that when the water level in the storage and regulation facilities rises rapidly, if the strategy is "storage," the terminal discharge facilities should be in a "shutdown" or "reduced opening" state; if the strategy is "discharge," the water level drop should correspond to the "opening" of the discharge facilities. This process establishes a logical truth table. For example, when the rate of water level change is a positive value of 0.2 meters per minute and the discharge pumping station is in a "shutdown" state, it is determined to meet the logical consistency of "peak shaving and water storage." A facility is marked as a "dominant control unit" only when it simultaneously meets the three conditions of "being in an active state," "having a negative correlation with the downstream pipe network," and "having internal storage and regulation logic consistency." This means that the facility has both control space and is at a critical coordination node. If any condition is not met, it is marked as an "auxiliary response unit." For example, a water level in a storm storage tank fluctuates actively and is currently storing water (logically consistent), but the load on its downstream pipeline network not only fails to decrease but actually increases dramatically (non-negative correlation). This indicates that the current operation of the storm storage tank is not controlling the pipeline network status. Therefore, it is downgraded to an auxiliary unit, providing only data reference and not undertaking core control tasks. This screening result constitutes effective indicator information for facility coordinated scheduling.

[0072] Please see Figure 4 The specific steps of S3 are as follows:

[0073] S311: Based on the facilities marked as the dominant control unit in the effective flag information of facility coordinated scheduling, extract the water storage and drainage volume data of the corresponding facilities in two consecutive cycles, perform differential processing based on the data of the current cycle and the previous cycle, and calculate the ratio of the difference with the unit time to obtain the water storage and drainage conversion rate and the direction of change, and generate a set of dynamic adjustment potential parameters for the dominant unit.

[0074] The process involves retrieving the current water storage level of the facility from the previous water storage level and performing a subtraction operation to obtain the increase in water storage. This increase is then divided by the sampling time interval to obtain the current storage-discharge conversion rate. This rate reflects the facility's capacity to handle rainwater. Next, the process calculates the dynamic adjustment potential by subtracting the current actual rate from the facility's designed maximum storage-discharge rate. For example, if a storage tank has a designed maximum discharge rate of 5000 cubic meters per hour and the current actual discharge rate is 3000 cubic meters per hour, then its dynamic adjustment potential is 2000 cubic meters per hour. This value represents how much additional dispatching work the facility can handle without overloading.

[0075] S312: Based on the water level data corresponding to the facilities marked as auxiliary response units in the effective flag information of facility coordinated scheduling, extract the target water level of the previous period and the actual water level value of the current period, and calculate the water level deviation through the difference between the two to obtain the auxiliary unit state error characteristic quantity.

[0076] The system reads the target water level set by the auxiliary unit in the previous scheduling cycle, as well as the actual water level currently reported by the sensors. The water level deviation is obtained by subtracting the actual water level from the target water level. For example, if the target control water level for auxiliary unit B is 3.5 meters, and the actual water level is 3.8 meters, the deviation is -0.3 meters, indicating that the water level exceeds the limit and there is a risk of overflow. This deviation is quantified as a characteristic quantity of the auxiliary unit's state error.

[0077] S313: Based on the dynamic adjustment potential parameter set of the leading unit and the state error characteristic quantity of the auxiliary unit, calculate the flow redistribution ratio and correct the parameters of the current control output of the leading control unit. At the same time, update the facility scheduling task instruction set, aggregate the current control weight and scheduling bias parameters, and obtain the content of the leading side scheduling execution instruction.

[0078] The flow redistribution algorithm first sets a flow redistribution ratio coefficient. The calculation logic for this coefficient is as follows: multiply the water level deviation of the auxiliary unit by a preset conversion factor, which is determined by the hydraulic distance between the auxiliary unit and the main unit. For example, the closer the distance, the larger the factor. Assuming a conversion factor of 1000 cubic meters per meter, the aforementioned deviation of -0.3 meters corresponds to a flow adjustment requirement of -300 cubic meters. Subsequently, this requirement is applied to the main control unit, correcting its original control output parameters (such as pump station frequency). If the main unit originally planned to discharge 3000 cubic meters per hour, considering the need to assist the auxiliary unit in depressurizing (i.e., slower discharge to free up network capacity, or faster discharge to empty itself, depending on the upstream and downstream relationship), assuming the logic is to increase the discharge of the downstream main unit to empty the network, the target is corrected to 3300 cubic meters per hour. Finally, the process encapsulates the corrected parameters into specific hardware instructions, such as "start pump 2 at a frequency of 45 Hz", and combines them with the current control weights to generate the final dominant side scheduling execution instruction.

[0079] Please see Figure 5 The specific steps of S4 are as follows:

[0080] S411: Based on the scheduling target specified in the execution instruction of the master side, retrieve the various facility control channel identifiers recorded in the preset facility control mapping table, construct the corresponding mapping relationship between the scheduling target and the channel identifier, and store the mapping relationship in a structured manner as a control channel index unit to obtain the facility control channel mapping index set;

[0081] First, the execution instruction from the master side is parsed to extract the "scheduling target" field. This field typically contains the logical ID of the target facility (e.g., "LID_05_Node") and its functional type (e.g., "Inlet_Valve"). Next, the process retrieves a "facility control mapping table" pre-stored in the database. This table records a one-to-one correspondence between logical IDs and physical control channel identifiers (e.g., PLC address, Modbus register address). The process iterates through the mapping table, searching for records matching the scheduling target and extracting the corresponding physical channel identifier. For example, the logical ID "Tank_A_Pump_1" corresponds to the physical channel "PLC_01_DO_03". This process transforms the abstract scheduling target into a concrete hardware address, generating a facility control channel mapping index set.

[0082] S412: Based on the facility control channel mapping index set, extract the facility function category information corresponding to each channel identifier, and at the same time read the facility function requirements specified in the main side scheduling execution instruction. Compare whether the category attributes of the two are consistent. If they are consistent, mark it as a valid control channel and establish a list of current valid control channels.

[0083] The "Facility Function Category" attribute of the channel in the mapping table is read and compared with the "Facility Function Requirements" specified in the instruction. This step is to prevent the risk of instruction type mismatch, such as preventing an analog instruction for "adjusting frequency" from being sent to a digital channel that only supports "switching". If the instruction requires adjusting the opening degree (0 to 100%), and the channel attribute is identified as an "analog input channel", then the two attributes are considered to match, and the channel is marked as a valid control channel. If they do not match, an alarm is triggered and the channel is removed. This process ultimately establishes a rigorously validated list of currently valid control channels.

[0084] S413: Based on the current list of effective control channels, write the control parameters in the execution instruction of the dominant side into the execution buffer of the corresponding channel, activate the instruction writing status register to complete the instruction issuance process, update the current channel response status flag set, and obtain the multi-facility collaborative response content.

[0085] The specific control parameters (such as the digital value 3276 corresponding to "opening degree 80%)" in the execution command of the master-side scheduling are written into the execution buffer pointed to by the effective control channel list. Subsequently, this process sends a high-level pulse or a specific trigger code to the command write status register, activating the hardware-level command transmission process. Upon receiving the command, the device returns an acknowledgment signal or the current action status. This process captures these feedback signals in real time and updates the current channel response status flag set. For example, if the feedback signal indicates that the valve is in action after the command is issued, the channel is marked as "responding". This series of feedback information constitutes the multi-facility coordinated response content.

[0086] Please see Figure 6 The specific steps of S5 are as follows:

[0087] S511: Based on the multi-facility coordinated response content, extract the actual system state trajectory fed back by each control channel in the current scheduling cycle and the target state trajectory set in the scheduling task, perform trajectory overlap segment length statistics according to the time axis, calculate the continuous state matching time value, and obtain the state trajectory matching duration set.

[0088] The actual system state trajectory is constructed by collecting the feedback data from each control channel within the current scheduling cycle. Simultaneously, the target state trajectory preset in the scheduling task is read. This process places the two trajectories on the same time axis and calculates their overlap within the allowable error band. An error band width is set, for example, ±5%. Subsequently, the length of time the actual trajectory falls within the target trajectory error band throughout the entire cycle is calculated. For example, if the actual water level closely follows the target water level curve for 8.5 minutes within a 10-minute scheduling cycle (error less than 5%), this 8.5 minutes is the continuous state matching time value. The higher this value, the better the system's following performance. This result is recorded as the state trajectory matching duration set.

[0089] S512: Based on the facility action parameters in the multi-facility coordinated response content, the actual facility behavior of each channel under the target control direction is judged by the action consistency mark within the cycle. If the action mark of consecutive sampling points remains the same, it is recorded as consistent action, and a system action response consistency sequence is established.

[0090] The analysis examines the feedback parameters in the multi-facility coordinated response to check whether the actual actions of the equipment exhibit repeated oscillations when the target control direction remains unchanged. For example, if the command requires a valve to remain continuously open, and the feedback data shows that the valve opening fluctuates frequently between "50%-55%-50%-55%", then the action is considered inconsistent. If the feedback data shows that the valve opening remains stable at 52% or exhibits monotonous changes, then the action is considered consistent. This process assigns a binary label to the action status of each sampling point (1 for consistency, 0 for oscillation). If five consecutive sampling points are all labeled 1, then the action is recorded as consistent. This process generates a system action response consistency sequence.

[0091] S513: Based on the consistency sequence of the state trajectory matching duration set and the system action response, combined with the continuous scheduling hold time and the range of system state deviation changes within the current scheduling cycle, evaluate the dynamic trend matching relationship between various parameters, and output them as scheduling execution performance parameters to obtain the system collaborative scheduling performance evaluation record;

[0092] The process obtains the continuous scheduling hold time for the current scheduling cycle, as well as the range of change in system state deviation (the difference between the actual value and the target value) during this period. This process employs a ratio evaluation logic, dividing the "state trajectory matching duration" by the "continuous scheduling hold time" to obtain the time matching rate. Simultaneously, the root mean square (RMS) value of the system state deviation is calculated. The performance evaluation logic is: the higher the time matching rate and the lower the RMS deviation value, the better the performance. For example, if the time matching rate is 85% and the RMS deviation value is less than 0.1 meters, the evaluation result is "excellent." This process outputs these quantitative indicators to generate the final system collaborative scheduling performance evaluation record, which serves as the basis for the next round of scheduling parameter optimization.

[0093] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A collaborative scheduling method for an integrated sponge city water storage and drainage system, characterized in that, Includes the following steps: S1: Acquire multi-source heterogeneous sensing data of the target area within a continuous sampling period during rainfall events, extract the state change of each subsystem between the current sampling period and the previous sampling period, construct a state difference vector set, determine the state change direction of each subsystem through sign discrimination, perform structured aggregation according to subsystem type, and generate system dynamic response feature combination results; S2: Based on the combined results of the system dynamic response characteristics, set the conditions for the establishment of LID-grey facility coupling response. When all conditions are met, mark the corresponding facility as having the ability to participate in coordinated scheduling and mark it as the leading control unit. Otherwise, mark it as an auxiliary response unit and obtain the effective flag information of facility coordinated scheduling. S3: Based on the effective flag information of the facility coordinated scheduling, determine the storage and discharge conversion rate of the current cycle's dominant control unit and calculate its dynamic adjustment potential, extract the deviation value between the target water level and the current actual water level in the previous cycle of the auxiliary response unit, synchronously correct the control output parameters of the dominant control unit and update the scheduling task instructions, and obtain the content of the dominant side scheduling execution instructions. S4: Based on the content of the dominant side scheduling execution instruction, match the scheduling target with the various facility control channel identifiers recorded in the preset facility control mapping table, locate the current effective control channel and complete the instruction issuance, and obtain the multi-facility collaborative response content; S5: Based on the multi-facility coordinated response content, determine the dynamic matching relationship between the scheduling hold time and the range of system state deviation changes within the current cycle, and output the system coordinated scheduling performance evaluation record.

2. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific conditions for the LID-grey facility coupling response to be established are as follows: First, facility status activity is determined when the absolute value of the change in status of the corresponding facility within the current period is greater than a preset threshold. Secondly, the LID-pipeline network coordination relationship is determined to be negatively correlated with the direction of change in the storage state of LID facilities and the direction of change in the load of the downstream pipeline network; Third, the regulation-discharge synergy is determined by ensuring that the rate of change of water level in the regulation facility and the change of start-up and shutdown status of the end-point discharge facility are logically consistent.

3. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that: The effective control channel specifically refers to the corresponding channel whose facility type matches the facility function category specified in the dominant side dispatch instruction.

4. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that: The combined results of the system's dynamic response characteristics include rainfall driving intensity characteristics, surface response lag index, pipeline load fluctuation characteristics, and storage facility capacity utilization trend. The effective indicator information of facility coordinated scheduling includes facility status activity label, coupled response capability index, and scheduling intervention priority. The content of the dominant side scheduling execution instruction includes the dominant facility control weight, flow allocation ratio, and water level regulation bias. The content of the multi-facility coordinated response includes instruction execution delay time, facility action trajectory, and regulation path activation status. The system coordinated scheduling performance evaluation record includes multi-objective balance index, state deviation convergence rate, and duration of continuous effectiveness of scheduling strategy.

5. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific steps for obtaining the system dynamic response feature combination result are as follows: S111: Obtain the rainfall intensity sequence of the target area within a continuous sampling period during the rainfall event, extract the rainfall intensity values ​​of the current period and the previous period respectively, construct the rainfall intensity difference vector, and determine the rainfall intensity change trend by judging the sign of the difference, and generate a rainfall-driven feature set; S112: Based on the surface runoff generation and collection state sequence, pipeline load sequence, and storage facility operation parameter sequence, extract the corresponding state values ​​between the current cycle and the previous cycle, construct the surface state difference set, pipeline load difference set, and storage parameter difference set, and represent the state change direction of each subsystem by comparing the difference signs, and jointly output the direction marking information of each subsystem in the current cycle to obtain the subsystem state direction determination set; S113: Based on the rainfall-driven feature set and the subsystem state direction determination set, the state change directions of the four types of elements—rainfall, surface, pipeline, and storage—are structurally aggregated to form a four-element state vector for each element in the current cycle. The multi-element state vectors are then sequentially concatenated into a system-level dynamic response sequence to generate a system dynamic response feature combination result.

6. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific steps for obtaining the effective flag information for facility collaborative scheduling are as follows: S211: Based on the combined results of the system dynamic response features, extract the absolute value of the state change of various facilities within the current sampling period, determine whether it is greater than a preset threshold, output the facility active state flag if it is greater than the threshold, otherwise output the facility silent state flag, and obtain the facility active state judgment set by setting the state activity judgment of various facilities respectively. S212: Based on the combined results of the system dynamic response features, extract the direction of change of LID facility storage capacity and the direction of change of downstream pipeline load, perform a sign negative correlation test, if the negative correlation is satisfied, mark it as the LID-pipeline network coordination relationship is established, otherwise mark it as not established, combine the multi-point test results to generate an LID-pipeline network coordination consistency flag sequence. S213: Based on the facility activity determination set and the LID-pipeline network coordination consistency flag sequence, extract the logical relationship between the rate of change of water level of the storage facility and the start-stop status change of the terminal discharge facility. If the three conditions of facility activity, LID-pipeline network coordination, and storage-discharge logic consistency are met simultaneously, then mark the corresponding facility as the leading control unit; otherwise, mark it as an auxiliary response unit and obtain the effective flag information of facility coordinated scheduling.

7. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific steps for obtaining the content of the dominant side scheduling execution instruction are as follows: S311: Based on the facilities marked as the dominant control unit in the facility coordinated scheduling effective flag information, extract the water storage and drainage volume data of the corresponding facilities in two consecutive cycles, perform differential processing based on the data of the current cycle and the previous cycle, and calculate the ratio of the difference with the unit time to obtain the water storage and drainage conversion rate and the direction of change, and generate a set of dynamic adjustment potential parameters for the dominant unit. S312: Based on the water level data corresponding to the facilities marked as auxiliary response units in the effective flag information of facility coordinated scheduling, extract the target water level of the previous period and the actual water level of the current period, calculate the water level deviation through the difference between the two, and obtain the auxiliary unit state error characteristic quantity. S313: Based on the dynamic adjustment potential parameter set of the leading unit and the state error characteristic quantity of the auxiliary unit, calculate the flow redistribution ratio and correct the current control output of the leading control unit. At the same time, update the facility scheduling task instruction set, aggregate the current control weight and scheduling bias parameter, and obtain the content of the leading side scheduling execution instruction.

8. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific steps for obtaining the multi-facility collaborative response content are as follows: S411: Based on the scheduling target specified in the content of the dominant side scheduling execution instruction, retrieve the various facility control channel identifiers recorded in the preset facility control mapping table, construct the corresponding mapping relationship between the scheduling target and the channel identifier, and store the mapping relationship in a structured manner as a control channel index unit to obtain the facility control channel mapping index set; S412: Based on the facility control channel mapping index set, extract the facility function category information corresponding to each channel identifier, and at the same time read the facility function requirements specified in the main side scheduling execution instruction content. Compare whether the category attributes of the two are consistent. If they are consistent, mark it as a valid control channel and establish a list of current valid control channels. S413: Based on the current list of effective control channels, write the control parameters in the execution instruction content of the dominant side scheduling to the execution buffer of the corresponding channel, activate the instruction writing status register to complete the instruction issuance process, update the current channel response status flag set, and obtain the multi-facility collaborative response content.

9. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that, The specific steps for obtaining the system collaborative scheduling performance evaluation record are as follows: S511: Based on the multi-facility coordinated response content, extract the actual system state trajectory fed back by each control channel in the current scheduling cycle and the target state trajectory set in the scheduling task, perform trajectory overlap segment length statistics according to the time axis, calculate the continuous state matching time value, and obtain the state trajectory matching duration set. S512: Based on the facility action parameters in the multi-facility coordinated response content, the actual facility behavior of each channel under the target control direction is judged by the action consistency mark within the period. If the action mark of consecutive sampling points remains the same, it is recorded as consistent action, and a system action response consistency sequence is established. S513: Based on the consistency sequence of the state trajectory matching duration and the system action response, combined with the continuous scheduling hold time and the range of system state deviation changes within the current scheduling cycle, evaluate the dynamic trend matching relationship between various parameters, and output them as scheduling execution performance parameters to obtain the system collaborative scheduling performance evaluation record.

10. The integrated sponge city water storage and drainage system collaborative scheduling method according to claim 1, characterized in that: The sampling period is 1 second. The surface runoff state sequence is collected by a soil moisture sensor and a surface runoff meter. The pipeline load sequence is collected by an ultrasonic flow meter. The storage facility operation parameter sequence is collected by a level gauge and a gate opening sensor.

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