[0053] The present invention will be further described below in conjunction with the drawings and embodiments.
[0054] It should be pointed out that the following detailed descriptions are all illustrative and are intended to provide further explanations for the application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.
[0055] It should be noted that the terms used here are only for describing specific implementations, and are not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and/or "including" are used in this specification, they indicate There are features, steps, operations, devices, components, and/or combinations thereof.
[0056] Such as figure 1 As shown, this embodiment also provides a method for real-time scheduling of rainwater storage facilities based on real-time weather information, including the following steps:
[0057] Step S1: Establish a regional SWMM model based on the remote sensing image data of the construction area, project planning and design data, measured data, and regional DEM data;
[0058] Step S2: Use the provided historical rainfall data to calibrate the parameters of the regional SWMM model;
[0059] Step S3: Set up information collection components and actuators in the rainwater storage facilities, and combine the information collection components and actuators installed in the existing or newly installed rainwater storage facilities with the lower computer (PLC or single-chip) in the electrical control cabinet Connected, the lower computer is provided with a support module for communicating with the upper computer; the lower computer is generally set in an electrical control cabinet next to the storage facility.
[0060] Step S4: Establish a software dispatching control platform for the upper computer of the rainwater storage facilities in the construction area, and at the same time carry out the communication connection between the lower computer and the upper computer;
[0061] Step S5: In the scheduling process, relying on the upper computer software scheduling platform to make decision analysis on the real-time rainfall forecast data obtained regularly; or make decision analysis for different meteorological warning levels to realize the dispatch of rainwater storage facilities based on real-time weather information plan scheduling control.
[0062] In this embodiment, the specific content of the step S2 is: using more than 3 high-intensity historical rainfall for analysis, and comparing the calculation results of the pipe flow, water level, and water depth of the SWMM model with actual values Differences: adjust the parameters in the SWMM model so that the difference between the model calculation result and the historical measured data is less than 10% to complete the parameter calibration.
[0063] In this embodiment, the decision analysis for different weather warning levels in step S5 specifically includes the following steps:
[0064] Step SA: Combining the existing historical hydrological statistical data of the construction area and the relevant national weather warning regulations, establish the corresponding SWMM model rainfall sequence under different weather warning levels, and write it into the .inp input file of the SWMM model, and execute Simulation analysis
[0065] Step SB: Use the analysis results of the SWMM model under different weather warnings to formulate corresponding rainwater storage facilities operation plans under different weather warning levels or different real-time weather conditions;
[0066] Step SC: Determine whether the weather warning information is valid according to the real-time weather warning information obtained by the upper computer software dispatch control platform in step S4, if it is valid, execute step SD; otherwise, continue to obtain real-time weather warning information regularly;
[0067] Among them, the weather warning is issued by the national and local meteorological departments, and it is determined whether the weather warning is effective according to the weather warning information issued by the national and local meteorological departments.
[0068] Step SD: Through the call of the plan made in step SB, issue an execution instruction to the lower computer to realize the control of rainwater storage facilities based on the weather warning plan scheduling, and finally return to step SC;
[0069] Step SE: Adjust the parameters of the SWMM model based on historical operating data, and adjust the content of the plan based on the adjusted model simulation results to ensure the reliability of the dispatch plan.
[0070] In this embodiment, the step S5 relies on the upper computer software scheduling platform to make a decision analysis on the real-time rainfall forecast data obtained regularly, which specifically includes the following steps:
[0071] Step Sa: Use the upper computer software scheduling control platform constructed in S4 to obtain the nowcast weather forecast data regularly. The specific requirements are that the time span of the nowcast rainfall forecast is greater than 5 min and the forecast value interval is less than 10 min; after the occurrence of rain is judged, when the forecast rain starts, Write the rainfall forecast value as the rainfall sequence into the .inp input file of the SWMM model; when the forecast rainfall is not over, add the nowcast forecast data to the actual rainfall sequence of this field to complete the rainfall sequence input;
[0072] Step Sb: Use genetic algorithm to optimize the scheduling parameters in the SWMM model to reduce the peak runoff in the construction area in the SWMM model or reduce the water level in the rainwater pipe network at the point of flooding;
[0073] Step Sc: According to the optimization result in step Sb, a real-time scheduling plan is established, and the upper computer software scheduling control platform constructed in S4 controls the actions of the lower computer to complete the execution of the plan.
[0074] In this embodiment, the content of the rainwater storage facility operation plan formulated in step SB includes:
[0075] In response to rainfall under the corresponding warning level, the storage capacity required by the storage facility, the pre-drainage of the rainwater storage facility, the opening and flood storage time of the rainwater storage facility, the gate opening of the rainwater storage facility, and after the rainwater storage facility is drained The water level, the range of water accumulation in the construction control area, the prediction of the depth of water accumulation, and the work plan and process of the executive components in the rainwater storage facility.
[0076] In this embodiment, the steps of the rainwater storage facility operation plan formulated in step SB are:
[0077] Extract the initial water level, gate opening time, gate opening and other parameters of the regulation and storage facility in the SWMM model simulation scheme, and determine the post-drainage water level of the rainwater regulation and storage facility, the required regulation storage capacity of the facility, the pre-discharge water volume of the rainwater regulation and storage facility, and the rainwater regulation and storage The opening and flood storage time of the facility, the opening of the gate of the rainwater storage facility; according to the calculation results of the model, the scope and depth of the water accumulation in the construction control area are predicted. In summary, complete the work plan and process formulation of the executive components in the rainwater storage facility.
[0078] In this embodiment, the genetic algorithm used in step Sb to optimize the scheduling parameters in the SWMM model specifically includes the following steps:
[0079] Step Sb1: Load the genetic algorithm optimization model into the host computer, and set the optimization objective function as the water level in the rainwater pipe network at the upstream or downstream of the storage tank, or the peak runoff flow at the confluence outlet of the regional rainwater main pipe, and use Construct fitness function based on grade division method;
[0080] Step Sb2: Determine the number of individual offspring according to the parallel computing ability of the host computer, specifically according to the number of CPU cores and the number of threads;
[0081] Step Sb3: Under the genetic algorithm optimization model, generate multiple sets of feasible solutions about the opening time and gate opening of each storage facility, and input each set of solutions into the SWMM model for operation to obtain the fitness function value;
[0082] Step Sb4: Evaluate and compare the fitness function values under each set of solutions, use the roulette algorithm to select the plan according to the fitness function value, randomly exchange or change the gate opening time and gate opening between the remaining plans, and generate a new feasible solution For the next round of optimization;
[0083] Step Sb5: Repeat step Sb3 and step Sb4. After the optimization round reaches the target number of runs or the judgment is converged, stop the optimization, save the opening time and gate opening of each storage facility, and execute step Sc.
[0084] In this embodiment, the information collection element described in step S3 includes a water level information collection element for monitoring the water level of a rainwater storage tank or rainwater storage facility, and a rainwater drainage pipeline downstream of the access point of the storage facility Metering equipment for measuring pipeline flow and water level.
[0085] In this embodiment, the actuator described in step S3 includes a water pump for drainage or rainwater reuse in a rainwater storage tank or rainwater storage facility, a gate for controlling the water intake of the storage facility, and a relay for the control circuit.
[0086] In this embodiment, the form of constructing the upper computer software scheduling control platform in step S4 includes:
[0087] Relying on the three-dimensional simulation entity information model of drainage facilities (such as AutoCAD Civil 3D, Autodesk Revit, etc.) to construct the upper computer software scheduling control platform, specifically through the development of the API interface of AutoCAD Civil 3D, Autodesk Revit and other software, and linking to the SWMM model Information such as simulation data and real-time dispatch data, real-time operation status of rainwater storage facilities in the area and the content of the plan are displayed based on the three-dimensional model data of the storage facilities in the area;
[0088] Or, relying on regional geographic information systems (such as QGIS, ArcGIS, etc.) for the construction of the upper computer software scheduling control platform, specifically through the secondary development of the API interface of the QGIS and ArcGIS software, and linking the SWMM model simulation data and real-time scheduling The data, the real-time operation status of stormwater facilities in the area and the content of the plan are displayed through a two-dimensional map or a three-dimensional geographic model.
[0089] In this embodiment, the specific process of establishing the SWMM model rainfall sequence in step SA is:
[0090] According to the National Meteorological Warning Regulations, determine the rainfall duration and total rainfall of the rainfall sequence; adopt the Chicago rain pattern or the rain pattern issued by the local meteorological department, and determine the return period of the rainfall sequence through trial calculations to match the corresponding rainfall duration under the corresponding rain pattern Rainfall.
[0091] In this embodiment, the specific steps for establishing the upper computer software dispatching control platform of the rainwater storage facility for the construction area in step S4 are:
[0092] Use wxpython or tkinter to build a GUI interface; use Python’s request and urllib libraries to obtain JSON information on weather data source pages, and use python’s json library to parse the acquired information; use python’s csv library or xlwt library to write platform operating data to csv or Excel storage files; use python-snap7 to communicate with PLC; use numpy to process and calculate internal data of genetic algorithm; use matplotlib to display data.
[0093] Preferably, in this embodiment, the regional SWMM model is established based on the remote sensing image data, project planning and design data, actual measurement data, and regional DEM data of the construction area, specifically: based on the remote sensing image data, planning and design data of the construction area Determine the type of land, combine the layout of drainage facilities to divide the sub-catchment area, determine the average slope in the area according to DEM data, and determine the hydrological parameters in different sub-catchment areas; determine the pipe sections in the model according to the pipe network design data And nodes and related parameters.
[0094] In this embodiment, the upper computer software scheduling control platform specifically includes the following modules:
[0095] Real-time acquisition, storage and display modules of real-time weather conditions in construction areas, real-time acquisition of weather warning information in construction areas from the National Meteorological Warning Center, and storage and display modules of real-time operating data of rainwater storage facilities, The storage and display module of historical operation monitoring data of rainwater storage facilities, the storage and display module of historical operation data of the upper computer software scheduling control platform, the calling and modification module of the regional SWMM model, the content display and modification module of the scheduling plan, the genetic algorithm search The superior module, the lower computer operation control module.
[0096] Preferably, in this embodiment, the operation plans of rainwater storage facilities corresponding to different weather warning levels or different real-time weather conditions can also be artificially adjusted through empirical judgments to adjust the opening time and gate opening of each storage facility, and select the model The plan with a better operational effect was completed.
[0097] Preferably, in this embodiment, by constructing a regional SWMM model, different plans are established according to national weather warning regulations or real-time rainfall forecast data; in the process of putting into operation, an upper computer software scheduling control for rainwater storage facilities is established The platform, in the control center, obtains the weather warning data issued by the relevant national departments in real time, and uses this as a basis to call the corresponding plan to realize the control of rainwater storage facilities based on real-time online plan scheduling; the upper computer software control center also sets up around the aforementioned Functional data storage and display functions. In addition, the platform is equipped with information collection components, actuators and lower-level computers to implement the execution of the platform plan and real-time data collection. After accumulating a certain amount of operating data, the SWMM model parameters are modified, the simulation is performed again, and the plan is adjusted according to the simulation results to ensure the reliability of the plan.
[0098] Preferably, in this embodiment, specific examples are cited for detailed description:
[0099] Example (1):
[0100] This embodiment formulates a plan based on the weather warning.
[0101] First, model the planned area, based on the comprehensive data (2019.01) of the drainage network design of the planned area, combined with the site survey results. After determining the drainage node, use the Tyson polygon method to divide the subcatchment area, and combine the design data and the measured data in the plot to determine the area, width, slope, land type ratio, and catchment calculation mode of the subcatchment area. At the same time, the LID facilities are set in combination with the reconstruction planning and design situation; the existing pipe network data is used to calibrate each parameter of the pipe network node and pipe section parameters.
[0102] After determining the rainfall sequence under different scenarios, the national rainstorm warning issuance standards are shown in the following table:
[0103]
[0104] According to Appendix 4 of "Water Supply and Drainage Design Manual Volume 5 Urban Drainage", find the formula of storm intensity in the reconstruction area, and get:
[0105]
[0106] In the formula: q——heavy rain intensity, L/s·ha;
[0107] T E ——Return period, a;
[0108] t-rainfall duration, min.
[0109] Combining the national meteorological warning regulations, the rainstorm intensity formula, the meteorological warning release data in the past five years and related rainfall statistics, the relevant parameters for formulating the plan are determined as follows:
[0110]
[0111] Combining relevant parameters, the Chicago rain pattern is used for the minute-by-minute distribution of rainfall, and the crest factor r = 0.4, the distribution result is as follows Figure 2-Figure 5 Shown
[0112] Input the allocated rainfall under different early warning plans into rain gauges in different files, and run the model. By artificially setting the initial water volume (water level) in the rainwater storage structure, the water volume and rainwater control effect under different pre-drainage scheduling scenarios are simulated. Use the simulation results to export the execution data of the plan to complete the establishment of the plan.
[0113] After completing the above modeling process, the early warning acquisition program is set. By screening and screening the data of the weather data provider, find the location of the corresponding weather warning data and real-time rainfall data storage, write Python code, build the GUI interface, and complete the functions of the upper computer software scheduling control platform. At the same time, complete the settings of the hardware facilities of the lower-level computer, including the installation and debugging of information collection components and actuators.
[0114] The following is an analysis of the extreme heavy rainfall response plan under the red warning. The SWMM is used to construct three situations in which there is no regulation and storage facility, the regulation and storage facility that has not been optimized by dispatching, and the regulation and storage facility optimized by this platform. running result. When the red warning is triggered, the water storage of rainwater storage and utilization facilities in the area is completely emptied, freeing up all storage capacity for rainwater storage.
[0115] Taking the rainstorm red warning as an example, when no storage facilities are set up, the peak flow obtained from the simulation of the corresponding rainfall sequence is 1579.61 L/s. In accordance with the design requirements, a total of six rainwater storage and utilization facilities are set up under the green belts and lawns of the reconstruction area, with a total storage capacity of 1245m 3. When the rainwater storage facilities are not optimized, see the flow process of the main rainwater main pipe confluent discharge point in the reconstruction area Image 6 , The peak flow rate is 1351.41L/s, and the peak runoff reduction ratio is only 14.45%. After optimization, when the rainfall sequence in the embodiment reaches 1.23h, the gate is opened, and different gate openings are set according to the design position and operating conditions of different storage facilities to reduce the peak runoff. See the effect after scheduling optimization Figure 7 , The peak flow rate is 820.03L/s, and the peak runoff reduction ratio reaches 48.09%. Through the optimization of the dispatching operation of the storage tank, the peak flow of the rainwater main pipe was reduced by 39.30% compared with the situation without storage. For comparison of running effects, see Figure 8. The plan makes full use of the storage capacity of the regulation and storage, so that the runoff peak has been significantly reduced, greatly reducing the drainage pressure of the existing rainwater pipe network in the face of extreme rainfall scenarios, and ensuring the safety of drainage in the area.
[0116] Example (two):
[0117] This embodiment formulates a plan based on real-time rainfall nowcasting.
[0118] After completing the settings of the upper computer platform and the lower computer hardware, including the installation and debugging of the information acquisition components and actuators, perform the following steps:
[0119] Firstly, the data provided by the meteorological data provider is screened. If the forecast value of near-rainfall is not zero, construct a rainfall sequence under near-rainfall conditions; if the rainfall has already started, add the forecast sequence to the back of the cumulative rainfall sequence. After completing the construction of the rainfall sequence, load the rainfall sequence into the SWMM model.
[0120] Then load the genetic algorithm optimization model, and set the fitness function to the water level of the rainwater pipe network at the upstream or downstream of the reservoir at the flood-prone point, or the peak runoff flow at the confluence outlet of the regional rainwater main pipe.
[0121] Under the genetic algorithm optimization model, generate multiple sets of feasible solutions about the opening time and gate opening of each storage facility, and input each set of solutions into SWMM to run to obtain the fitness function value; evaluate and compare the fitness of each set of solutions The value of the degree function, the program is screened, and then the gate opening time and gate opening between the remaining programs are randomly exchanged or changed, and the next round of optimization is performed; the foregoing steps are repeated, and the optimization is stopped after the optimization round reaches 30 or the convergence is determined. Save the relevant values and execute the plan.
[0122] According to the forecast value span, read the updated forecast information in time after the forecast is updated, and repeat the above steps.
[0123] The foregoing descriptions are only preferred embodiments of the present invention, and all equivalent changes and modifications made in accordance with the scope of the patent application of the present invention shall fall within the scope of the present invention.
