Toughness evaluation method and system of transformer substation rainwater drainage pipe network system and medium

Abstract

The invention provides a toughness evaluation method and system of a transformer substation rainwater drainage pipe network system and a medium, and belongs to the technical field of drainage system simulation evaluation. The toughness evaluation method for the transformer substation rainwater drainage pipe network system comprises the following steps: S1, constructing a drainage pipe network system model; s2, setting rainfall data sets of a plurality of return periods, inputting the rainfall data sets to the drainage pipe network system model for simulation, and obtaining a simulation result; s3, defining a toughness function of the drainage pipe network system according to the change condition of accumulated water of the drainage pipe network system along with time in the simulation result, and calculating a toughness value of the drainage pipe network system according to the toughness function; and S4, comparing the positions of the toughness values in a preset toughness value range, and generating a toughness evaluation result of the drainage pipe network system. According to the method, the toughness value of the drainage pipe network system can be calculated according to the toughness function, so that the toughness evaluation process of the drainage pipe network system is digitized, an accurate evaluation result is favorably provided, and the precision of the toughness evaluation result is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of drainage system simulation and evaluation, and particularly relates to a method, system and medium for evaluating the resilience of a rainwater drainage pipe network system in a substation. Background Art

[0002] A substation is an important link in the safe production of the power grid system, a center and a link connecting the power source and users, and also the core of power grid risk prevention and control. During the flood season, disaster events are extremely likely to have a great impact on the safe operation of the substation, easily cause waterlogging in the substation area, and are extremely likely to trigger secondary and derivative emergencies.

[0003] Currently, the risk assessment of substations during the flood season mainly relies on traditional methods to establish a multi-dimensional risk assessment factor index system to evaluate the safe operation of substations. However, as described in the Chinese invention patent with the application number "202310380832.X" and the Chinese invention patent with the application number "202410411787.4", most of the evaluation methods of traditional methods are fuzzy evaluations, and the accuracy of evaluating the resilience of the rainwater drainage pipe network system in the substation is low, which is not conducive to achieving accurate evaluation of the resilience of the rainwater drainage pipe network system in the substation. Summary of the Invention

[0004] The technical problem to be solved by the present invention is how to improve the accuracy of evaluating the resilience of the rainwater drainage pipe network system in the substation. In view of the deficiencies of the prior art, the present invention provides a method, system and medium for evaluating the resilience of the rainwater drainage pipe network system in the substation.

[0005] To solve the above technical problems, the technical solutions adopted by the present invention are as follows:

[0006] In the first aspect, the present invention provides a method for evaluating the resilience of a rainwater drainage pipe network system in a substation, including:

[0007] S1. Construct a drainage pipe network system model;

[0008] S2. Set rainfall data sets with multiple return periods, input the rainfall data sets into the drainage pipe network system model for simulation, and obtain simulation results;

[0009] S3. Define a resilience function of the drainage pipe network system according to the change of water accumulation in the drainage pipe network system over time in the simulation results, and calculate the resilience value of the drainage pipe network system according to the resilience function;

[0010] S4. Compare the position of the resilience value within a preset resilience value range to generate a resilience evaluation result of the drainage pipe network system.

[0011] Compared with the prior art, the beneficial effects of the method for evaluating the resilience of the rainwater drainage pipe network system of the substation of the present invention include: First, a drainage pipe network system model is constructed, and the information of the drainage pipe network in the area where the substation is located is digitized, so as to construct the system model for subsequent simulation; Then, rainfall data sets with multiple return periods are set, and the rainfall data over the years in the area where the substation is located are screened, and rainfall data sets with different return periods are selected. The drainage pipe network system model is simulated through the rainfall data sets, so as to obtain the flood drainage situation of the drainage pipe network system under rainfall conditions with different return periods; On this basis, according to the flood drainage situation of the drainage pipe network system, as time changes, the drainage pipe network system will gradually enter a waterlogging state as the rainfall increases. When the drainage pipe network system is in a waterlogging state, it means that the drainage performance of the drainage pipe network system is in a failure state. At this time, as time changes, as the waterlogging slowly drains, the waterlogging state of the drainage pipe network system will gradually return to normal, thereby reflecting the change of its own function in the process of the feedback system resisting and absorbing harmful events, and reflecting the resilience of the drainage pipe network system. In this way, according to the change of the waterlogging of the drainage pipe network system over time, the resilience function of the drainage pipe network system can be defined. After digitization, the resilience function of the drainage pipe network system can be obtained. At this time, the resilience value of the drainage pipe network system can be calculated according to the resilience function, so as to digitize the process of evaluating the resilience of the drainage pipe network system, which is beneficial to providing accurate evaluation results; Finally, the position of the calculated resilience value within the preset resilience value range can be compared, and the specific resilience evaluation result of the drainage pipe network system for resilience evaluation can be generated according to the position, effectively improving the accuracy of the resilience evaluation result.

[0012] Optionally, S3 includes:

[0013] S31. Define the function function of the drainage pipe network system according to the waterlogging situation of the drainage pipe network system in the simulation result. The function function is as follows:

[0014]

[0015] S32. Define the resilience function according to the integral of the function function with respect to the time. The resilience function is as follows:

[0016]

[0017] Wherein, t0 is the starting time of the harmful external impact, and t E is the final moment of the selected research period;

[0018] S33. Calculate the resilience value of the drainage pipe network system according to the resilience function.

[0019] Optionally, S33 includes:

[0020] S331. Define the failure function of the drainage pipe network system according to the functional function. The failure function is as follows:

[0021] I v (t) = 1 - F v (t);

[0022] S332. Replace the functional function with the failure function and substitute it into the resilience function to obtain the resilience function as follows:

[0023]

[0024] S333. Calculate the resilience value of the drainage pipe network system according to the resilience function obtained in S332.

[0025] Optionally, S331 includes:

[0026] S3311. Define the failure function as the proportion of the number of pipe segments in the failed state at time t to the total number of pipe segments under the rainfall pattern with a preset recurrence period P.

[0027] S3312. Obtain the total number of pipe segments and the number of water - logged pipe segments of the drainage pipe network system under the recurrence period P according to the simulation results.

[0028] S3313. Obtain the failure function according to the total number of pipe segments and the number of water - logged pipe segments.

[0029] Optionally, S3313 includes:

[0030] S33131. Perform importance weighting on the number of pipe segments of the drainage pipe network system under the recurrence period P.

[0031] S33132. Obtain the calculation formula for the boundary centrality. The calculation formula for the boundary centrality is as follows:

[0032]

[0033] where is the number of the shortest paths passing through the edge element v in the set of shortest paths s - t, the P s is the set of catchment nodes except the drainage outlets, and the P t is the set of drainage outlet nodes;

[0034] S33133. Obtain the failure function according to the boundary centrality and the sub - catchment area of the pipe segment. The failure function is as follows:

[0035]

[0036] wherein, A(v) is the area of the sub-catchment, and N floor (P) is the number of weighted product pipeline segments under the recurrence interval P, and N total is the total number of weighted pipeline segments, and L is the set of all pipeline segments in the drainage pipe network system.

[0037] Optionally, S2 includes:

[0038] S21. Obtain the rainfall intensity formula, and the rainfall intensity formula is as follows:

[0039]

[0040] wherein, q is the designed rainfall intensity, t is the precipitation time, t = 0 represents the initial time of the corresponding rainfall event, P is the recurrence interval of the rainstorm, A1 is the rainwater parameter, C is the rainwater variation parameter, b is the precipitation duration correction parameter, and n is the rainstorm attenuation index;

[0041] S22. Design the rainfall pattern according to the rainfall intensity formula, and obtain the data of multiple rainfall patterns;

[0042] S23. Generate the rainfall dataset of the recurrence interval according to the data of the rainfall pattern, input the rainfall dataset into the drainage pipe network system model for simulation, and obtain the simulation result.

[0043] Optionally, S22 includes:

[0044] S221. Set the duration time and the rain peak coefficient of the rainfall process, and obtain the time when the rainfall intensity reaches the peak according to the duration time and the rain peak coefficient;

[0045] S222. Calculate the rainfall intensity curves of multiple recurrence intervals respectively according to the time when the rainfall intensity reaches the peak and the rainfall intensity formula;

[0046] S223. Discretize the rainfall intensity curve to obtain the data of the rainfall pattern.

[0047] Optionally, S1 includes:

[0048] S11. Construct an initial model of the drainage pipe network system in the area where the substation is located;

[0049] S12. Obtain the historical rainstorm records of the area, and set the training dataset according to the historical rainstorm records;

[0050] S13. Train the initial model according to the training dataset to obtain the training result, and generate a drainage pipe network system model when the training result is within a preset range.

[0051] In a second aspect, the present invention further provides a resilience assessment system for a substation rainwater drainage pipe network system, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the resilience assessment method for the substation rainwater drainage pipe network system as described above is implemented.

[0052] Compared with the prior art, the beneficial effects of the resilience assessment system for the substation rainwater drainage pipe network system of the present invention are the same as those of the resilience assessment method for the substation rainwater drainage pipe network system as described above, and will not be elaborated here.

[0053] In a third aspect, the present invention further provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the resilience assessment method for the substation rainwater drainage pipe network system as described above is implemented.

[0054] Compared with the prior art, the beneficial effects of the computer storage medium of the present invention are the same as those of the resilience assessment method for the substation rainwater drainage pipe network system as described above, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The following further elaborates the present invention in detail with reference to the drawings.

[0056] Figure 1 : Flow chart of the resilience assessment method for the substation rainwater drainage pipe network system in an embodiment of the present invention;

[0057] Figure 2 : Sub - flow chart of the resilience assessment method for the substation rainwater drainage pipe network system in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] To better understand the present invention, the following further clarifies the content of the present invention in combination with embodiments. However, the protected content of the present invention is not limited to the following embodiments. In the following description, a large number of specific details are given to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details.

[0059] It should be noted that in the accompanying drawings, the Z-axis represents the vertical direction, that is, the up-and-down position, and the positive direction of the Z-axis represents the upper side, while the negative direction of the Z-axis represents the lower side; the Y-axis in the accompanying drawings represents the horizontal direction and is specified as the front-and-back position, and the positive direction of the Y-axis represents the front side, while the negative direction of the Y-axis represents the back side; the X-axis in the accompanying drawings represents the left-and-right position, and the positive direction of the X-axis represents the right side, while the negative direction of the X-axis represents the left side. At the same time, it should be noted that the above-mentioned meanings represented by the Z-axis, Y-axis and X-axis are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0060] As used herein, the term "comprising" and its variants are open-ended, that is, "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "optional embodiment". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0061] It should be noted that the modifications of "one" and "plural" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly specified in the context, it should be understood as "one or more".

[0062] In a first aspect, an embodiment of the present invention provides a method for evaluating the resilience of a rainwater drainage pipe network system in a substation, including: S1, constructing a drainage pipe network system model; S2, setting rainfall data sets with multiple return periods, inputting the rainfall data sets into the drainage pipe network system model for simulation, and obtaining simulation results;

[0063] S3, defining a resilience function of the drainage pipe network system according to the change of the water accumulation in the drainage pipe network system over time in the simulation results, and calculating the resilience value of the drainage pipe network system according to the resilience function; S4, comparing the positions where the resilience values are within the preset resilience value range, and generating a resilience evaluation result of the drainage pipe network system.

[0064] In this optional embodiment, as Figure 1As shown, first, a drainage pipe network system model is constructed, and the information of the drainage pipe network in the area where the substation is located is digitized to construct the system model for subsequent simulation; then, rainfall data sets with multiple recurrence periods are set, and the rainfall data over the years in the area where the substation is located are screened to select rainfall data sets with different recurrence periods, and the drainage pipe network system model is simulated through the rainfall data sets to obtain the flood drainage conditions of the drainage pipe network system under rainfall conditions with different recurrence periods; on this basis, according to the flood drainage conditions of the drainage pipe network system, as time changes, the drainage pipe network system will gradually enter a waterlogging state as the rainfall increases. When the drainage pipe network system is in a waterlogging state, it indicates that the drainage performance of the drainage pipe network system is in a failure state. At this time, as time changes, as the waterlogging slowly drains, the waterlogging state of the drainage pipe network system will gradually return to a normal state, thereby reflecting the change of its own function in the process of resisting and absorbing harmful events and embodying the resilience of the drainage pipe network system. In this way, the resilience function of the drainage pipe network system can be defined according to the change of the waterlogging of the drainage pipe network system over time, and the resilience function of the drainage pipe network system can be obtained after digitization. At this time, the resilience value of the drainage pipe network system can be calculated according to the resilience function, so as to digitalize the resilience assessment process of the drainage pipe network system, which is conducive to providing accurate assessment results; finally, the position of the calculated resilience value within the preset resilience value range can be compared, and the specific resilience assessment result of the drainage pipe network system for resilience assessment can be generated according to the position, effectively improving the accuracy of the resilience assessment result.

[0065] Optionally, S3 includes: S31. Define the function function of the drainage pipe network system according to the waterlogging situation of the drainage pipe network system in the simulation result. The function function is as follows:

[0066]

[0067] S32. Define resilience according to the integral of the function function with respect to time. The resilience function is as follows

[0068]

[0069] where t0 is the starting time of the harmful external impact, and t E is the final moment of the selected research period; S33. Calculate the resilience value of the drainage pipe network system according to the resilience function.

[0070] In this alternative embodiment, in the process of defining the resilience function of the drainage pipe network system, the function function of the drainage pipe network system can be defined first according to the waterlogging situation of the drainage pipe network system in the simulation results. The function function specifically reflects whether the function of the drainage pipe network system is normal or fails. The lowest point of the change curve of the function function over time can reflect the robustness of the drainage pipe network system, and the recovery time for the curve to recover upward also reflects the resilience of the drainage pipe network system. Among them, when the drainage pipe network system is working properly, regardless of whether it is full-flow along the way, the total water head upstream of the drainage pipe network system should be higher than that downstream. When water accumulates at the downstream node of a certain pipeline section, the water head at the downstream end is too high, which generally makes it difficult for the water head at the upstream end to maintain a higher level. According to the principle of communicating vessels, at this time, the pipes of the drainage pipe network system are extremely likely to fall into a full-flow state of the pipes, but the flow rate approaches zero and enters a failure state. Therefore, the function function can be defined by whether there is water accumulation at the downstream node. The relational expression of the function function is shown in Equation (1.1); correspondingly, the integral of the function function with respect to time can reflect the change of the function of the drainage pipe network system over time, and the change of the recovery function of the drainage pipe network system over time after being affected by external disturbances can reflect the resilience of the drainage pipe network system, that is, the resilience function. At this time, the resilience function can be defined according to the integral of the function function with respect to time. The relational expression of the resilience function is shown in Equation (1.2), where t0 is the starting time of the harmful external shock, and t E is the final moment of the selected research period. Then, the resilience value of the drainage pipe network system can be calculated through the resilience function, which is convenient for subsequent accurate resilience assessment.

[0071] Optionally, S33 includes: S331. Define the failure function of the drainage pipe network system according to the function function. The failure function is:

[0072] I v (t) = 1 - F v (t) (1.3);

[0073] S332. Replace the function function with the failure function and substitute it into the resilience function to obtain the following resilience function:

[0074]

[0075] S333. Calculate the resilience value of the drainage pipe network system according to the resilience function obtained in S332. In this alternative embodiment, since the drainage pipe network system is in a normal functional state, it means that the drainage pipe network system is in a non-failure state, and when the drainage pipe network system is in a functional failure state, it means that the drainage pipe network system is in a failure state. Therefore, the failure function of the drainage pipe network system can be defined through the function function, and the relational expression of the failure function is shown in Equation (1.3); correspondingly, the failure function can be used to replace the function function and substituted into the resilience function to obtain the resilience function, and the relational expression of the resilience function is shown in Equation (1.4); finally, the resilience value of the drainage pipe network system can be calculated according to the resilience function, which is convenient for subsequent accurate resilience assessment.

[0076] Optionally, S331 includes: S3311. Define the failure function as the proportion of the number of pipe segments in the failure state at time t to the total number of pipe segments under the rainfall pattern with a preset recurrence period P; S3312. Obtain the total number of pipe segments and the number of waterlogged pipe segments in the drainage pipe network system under the recurrence period P according to the simulation results; S3313. Obtain the failure function according to the total number of pipe segments and the number of waterlogged pipe segments.

[0077] In this alternative embodiment, in order to further improve the calculation convenience of the failure function, first, define the failure function as the proportion of the number of pipe segments in the failure state at time t to the total number of pipe segments under the rainfall pattern with a preset recurrence period P. At this time, the total number of pipe segments and the number of waterlogged pipe segments in the drainage pipe network system under the recurrence period P can be obtained according to the simulation results. Then, the proportion of the number of waterlogged pipe segments to the total number of pipe segments is the failure function. Among them, the determination criterion for the waterlogged pipe segments to be in the failure state can be the waterlogging depth threshold. For example, when the waterlogging depth ≥ 10 cm, the waterlogged pipe segments can be determined to be in the failure state.

[0078] Optionally, S3313 includes: S33131. Perform importance weighting on the number of pipe segments in the drainage pipe network system under the recurrence period P; S33132. Obtain the calculation formula for the boundary centrality. The calculation formula for the boundary centrality is as follows:

[0079]

[0080] Among them, is the number of the shortest paths passing through the edge element v in the shortest path set s-t, P s is the set of sub-catchment nodes except the drainage outlets, P t is the set of drainage outlet nodes; S33133. Obtain the failure function according to the boundary centrality and the sub-catchment area of the pipe segment. The failure function is as follows:

[0081]

[0082] Among them, A(v) is the sub-catchment area, N floor(P) is the number of weighted product pipeline segments under the return period P, N total is the total number of weighted pipeline segments, and L is the set of all pipeline segments in the drainage pipe network system.

[0083] In this alternative embodiment, in order to ensure the accuracy of the failure function, it is necessary to perform importance weighting on the number of pipeline segments in the drainage pipe network system under the return period P. Among them, the importance weight should include two indicators. The first is the structural importance index, which is represented by the betweenness centrality C B (v). The betweenness centrality is an index to measure the importance of edges in a network. It reflects the role of edges in the network information flow. Specifically, it refers to the proportion of the number of paths passing through a certain edge in all the shortest paths to the total number of shortest paths. Correspondingly, the betweenness centrality can also measure the importance of the edges in the area where the drainage pipe network system is located. The specific calculation formula can be seen in Equation (1.5). Among them, б st (v) is the number of shortest paths passing through the edge element v in the set of shortest paths s-t, P s is the set of catchment nodes except the drainage outlets, P t is the set of drainage outlet nodes; the second is the standardization index, which can be represented by the sub-catchment area A(v) at the entrance of the pipeline segment. Then, a further refined failure function can be obtained. The failure function can be seen in Equation (1.6). Among them, A(v) is the sub-catchment area, N floor (P) is the number of weighted product pipeline segments under the return period P, N total is the total number of weighted pipeline segments, and L is the set of all pipeline segments in the drainage pipe network system; finally, substituting the failure function into the R formula, the calculation formula for the resilience R(P) of the substation drainage pipe network under the rainstorm return period P can be obtained.

[0084] Optionally, S2 includes: S21. Obtain the rainstorm intensity formula, and the rainstorm intensity formula is as follows:

[0085]

[0086] Among them, q is the designed rainstorm intensity, t is the precipitation time, t = 0 represents the initial time of the corresponding rainfall event, P is the rainstorm return period, A1 is the rainwater parameter, C is the rainwater variation parameter, b is the precipitation duration correction parameter, and n is the rainstorm attenuation index; S22. Design the rain pattern according to the rainstorm intensity formula, and obtain the data of multiple rain patterns; S23. Generate the rainfall dataset of the return period according to the data of the rain pattern, input the rainfall dataset into the drainage pipe network system model for simulation, and obtain the simulation results.

[0087] Specifically, the rainwater parameter A1, the rainwater variation parameter C, the precipitation duration correction parameter b, and the rainstorm attenuation index n can all be obtained by fitting historical rainfall data.

[0088] In this alternative embodiment, after the drainage pipe network system modeling of the substation area is completed, according to the calculation of the rainfall event-driven model, the time process curve with rainfall intensity as the variable is called the rainfall pattern. Since the substation area is relatively small, it is considered that the entire spatial area follows the unified precipitation law. Referring to the "Urban Rainwater System Planning and Design Standard for Rainstorm Runoff Calculation" (2013), the basic form of the rainstorm intensity formula is shown in Equation (1.7), where q is the design rainstorm intensity, t is the precipitation time, t = 0 represents the initial time of the corresponding rainfall event, P is the return period of the rainstorm, A1 is the rainwater parameter, C is the rainwater variation parameter, b is the precipitation duration correction parameter, and n is the rainstorm attenuation index; the rainfall pattern is designed according to different return periods. Among them, for rainfall with a return period P ≤ 10a and a precipitation duration exceeding 120 min, the rainstorm intensity formula is:

[0089]

[0090] For rainfall with a return period P > 10a and a precipitation duration exceeding 120 min, the rainstorm intensity formula is:

[0091]

[0092] Referring to Equations (1.8) and (1.9), different rainstorm intensity formulas can be selected according to different return periods, so as to obtain data of multiple rainfall patterns. At this time, a rainfall dataset of the return period is generated according to the data of the rainfall pattern, and the rainfall dataset is input into the drainage pipe network system model for simulation to obtain the simulation results.

[0093] Optionally, S22 includes: S221, setting the duration time and the rain peak coefficient of the rainfall process, and obtaining the time when the rainfall intensity reaches the peak according to the duration time and the rain peak coefficient; S222, calculating the rainfall intensity curves of multiple return periods respectively according to the time when the rainfall intensity reaches the peak and the rainstorm intensity formula; S223, discretizing the rainfall intensity curve to obtain the data of the rainfall pattern.

[0094] In this alternative embodiment, referring to the method of adjusting the rainfall peak position in the Chicago rainfall pattern, referring to the rainfall records of extremely heavy rainstorms in the study area, setting the duration time of the rainfall process, and the rain peak coefficient is 0.2, that is, duration time · rain peak coefficient = the time when the rainfall intensity reaches the peak. Calculate the rainfall intensity curves with return periods of 0.5, 1, 2, 5, 10, and 100 years respectively according to the time when the rainfall intensity reaches the peak and the rainstorm intensity formula, and discretize them into a time series at intervals of 1 min, which can be used as the data of different rainfall patterns, that is, the input module of the drainage pipe network system model of the substation area.

[0095] Optionally, S1 includes: S11, constructing an initial model of the drainage pipe network system in the area where the substation is located; S12, obtaining historical heavy rain records of the area and setting a training data set according to the historical heavy rain records; S13, training the initial model according to the training data set to obtain a training result, and generating a drainage pipe network system model when the training result is within a preset range.

[0096] In this optional embodiment, to ensure the accuracy of the subsequent simulation of the drainage pipe network system model, as Figure 2 shown, an initial model of the drainage pipe network system in the area where the substation is located can be constructed first, a training data set can be set through the historical heavy rain records of the area, and the initial model can be trained through the training data set to obtain a training result. When the training result is within a preset range, it means that the simulation result output by the drainage pipe network system is within the required accuracy. At this time, a drainage pipe network system model can be generated.

[0097] Specifically, the drainage pipe network system model is constructed through the SWMM model. First, the drainage pipe network information of the substation is preprocessed. The one-dimensional pipe network model is a topological structure that parameterizes spatial data. The basic components include point elements and line elements. The point elements include confluence nodes such as rain inspection wells, rain grates, etc. and drainage outlets. The line elements are square or circular pipes. The relevant information of each element is the main basis for the SWMM model calculation. Since there is a part of unavailable data in the original data, such as repeatedly collected model data, pipe diameter or elevation, etc., incorrect flow direction markings, and sewage pipes irrelevant to this study, it is necessary to process the original data, and at the same time merge and simplify the pipe network elements to reduce the complexity of model operation. Then, the data is imported into SWMM for modeling to obtain the total number of junction nodes, the number of pipe connections, the number of drainage outlets, and the total length of the pipes in the study area. Among them, the boundary condition of the drainage outlet is free outfall. Then, the sub-catchments are divided. The sub-catchments divide the study area into smaller independent areas. The area of the basin determines the inflow of each confluence node. The division of the catchment area is completed based on the line elements of the pipe network. The principle of its algorithm is that the flow rate of any point on the plane of the study area is all introduced from the upstream end of the pipe connection with the shortest straight-line distance. According to this principle, the number and distribution of sub-catchments corresponding to the node elements are obtained. On this basis, according to the underlying surface of the city where the study area belongs, the attribute parameters of the sub-catchments are uniformly set to the default values of the general urban area. The specific parameters include the slope of the sub-catchment, the characteristic width of the sub-catchment, the proportion of non-depressed storage impervious surface, the proportion of depressed storage impervious surface, the proportion of pervious surface, the Manning coefficient of impervious surface, the Manning coefficient of pervious surface, the depth of depression storage, the maximum infiltration rate, the stable infiltration rate, the Horton decay constant, the surface drainage time, etc. Finally, different rainfall models are added to the preliminarily constructed drainage pipe network system model for simulation. When the engineering simulation report shows that generally the runoff continuity error of the model is 0.01%, the pipe network flow calculation continuity error is less than 0.1%, and the continuity error of the node flow does not exceed 10%, it meets the general requirements of the SWMM model. Use the swmmtoolbox library of Python to read the binary result file output by the model again for further result analysis to verify the reliability of the model. That is, whether there is a positive correlation between the number of flooded nodes, the flooding time and the rainstorm recurrence period in the simulation results, and whether the maximum value of the pipe flow is at the typical rainstorm flooding point.

[0098] It should be noted that for the resilience assessment of the substation drainage pipe network, the functional state of the drainage pipe network system is first described. Taking a single pipe segment in the substation area as an example, the functional function and failure function of the drainage pipe network are proposed, and a resilience assessment model for the drainage pipe network in the substation area is constructed by calculating the time integral of the resilience curve. The specific content includes two aspects: the functional function of the drainage pipe segment; the resilience curve and the resilience function. The functional function of the drainage pipe segment is the total flow Q that converges to the pipe network node during the flood discharge process of the pipe network system, which includes two parts. One part of Q pipe enters the pipe network system and is discharged into the receiving water body through the pipe hydraulic process; the other part forms the flow Q flood of the manhole overflow, causing surface flooding. Refer to whether the ground surface at the confluence node is in a waterlogged state to define whether the function of the pipe segment is complete or failed. Taking the behavior of a single pipe segment as an investigation, when the drainage pipe is working properly, regardless of whether it is full-flow along the way, the total water head upstream should be higher than that downstream. When the downstream node of a certain pipeline forms waterlogging, the water head at the downstream end is too high, which generally makes it difficult for the water head at the upstream end to maintain at a higher level. According to the principle of communicating vessels, the pipeline is extremely likely to fall into a full-flow state at this time, but the flow rate approaches zero. In this case, it can be considered that the drainage performance of the pipeline is in a failed state.

[0099] For example, taking the rainfall with a return period of 1 year as an example, the result data of the rainstorm simulation is extracted to obtain the "function-time" curve and the distribution map of the integration duration of the drainage pipe network system. If the line width is larger and the color is darker in the figure, it means that the waterlogging time of the pipe segment is longer. According to the peak value of the instantaneous waterlogging ratio of the pipe network, select the moment when F(t) first drops back to F(t)>0.999 after passing the peak value as the waterlogging end time t E , substitute it into the integral formula R to obtain the resilience index of the pipe network. Similarly, under rainfall events with different return periods, the robustness of the pipe network can be obtained according to the minimum value of the system function function, and the resilience index of the pipe network can be obtained according to the waterlogging drainage time. This application selects rainfall events designed with return periods of 0.5, 1, 2, 5, 10, and 100 years for simulation. According to the national standard regulations on rainfall levels, the above six-year rainfall events belong to rainstorm, heavy rainstorm, heavy rainstorm, extreme rainstorm, and extreme rainstorm respectively. The longer the waterlogging time at the pipe segment, the darker the color, and the length of the waterlogging time is positively correlated with the peak value of the waterlogging volume. Observe the simulated failure curve and resilience assessment index of the pipe network in the experimental results, observe whether the waterlogging drainage process and recovery time are consistent after the rain peak under different rainfall events for the same drainage pipe network, the characteristics mainly reflected by the differences in the resilience of the pipe network, and the changes in its system over time. Analyze the characteristics shown by the resilience curve, identify the weak links in the planned drainage capacity of the pipe network, and conduct overall planning in the rainwater storage and regulation planning to develop in the direction of improving resilience.

[0100] Second aspect, an embodiment of the present invention provides a resilience evaluation system for a substation rainwater drainage pipe network system, which is characterized by including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the resilience evaluation method for the substation rainwater drainage pipe network system according to any one of claims 1 to 8.

[0101] The technical effect of the resilience evaluation system for the substation rainwater drainage pipe network system in this embodiment is similar to the technical effect of the above-mentioned resilience evaluation method for the substation rainwater drainage pipe network system, and will not be elaborated here.

[0102] Third aspect, an embodiment of the present invention provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the above-mentioned resilience evaluation method for the substation rainwater drainage pipe network system.

[0103] The technical effect of the computer storage medium in this embodiment is similar to the technical effect of the above-mentioned resilience evaluation method for the substation rainwater drainage pipe network system, and will not be elaborated here.

[0104] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for evaluating the resilience of a rainwater drainage pipe network system in a substation, characterized in that, Including: S1. Construct a drainage pipe network system model; S2. Set rainfall datasets with multiple return periods, input the rainfall datasets into the drainage pipe network system model for simulation, and obtain simulation results; S3. Define a resilience function of the drainage pipe network system according to the change of water accumulation in the drainage pipe network system over time in the simulation results, and calculate the resilience value of the drainage pipe network system according to the resilience function; S4. Compare the positions of the resilience values within a preset resilience value range, and generate a resilience assessment result of the drainage pipe network system.

2. The resilience assessment method of the rainwater drainage pipe network system of a substation according to claim 1, characterized in that, The S3 includes: S31. Define a function function of the drainage pipe network system according to the water accumulation situation in the drainage pipe network system in the simulation results. The function function is as follows: S32. Define the resilience function according to the integral of the function function with respect to the time. The resilience function is as follows: Among them, the t0 is the starting time of the harmful external impact, and the t E is the final moment of the selected research period; S33. Calculate the resilience value of the drainage pipe network system according to the resilience function.

3. The resilience evaluation method of the rainwater drainage pipe network system of a substation according to claim 2, characterized in that The S33 includes: S331. Define a failure function of the drainage pipe network system according to the function function. The failure function is: I v F(t) = 1 - v F(t); S332. Replace the function function with the failure function and substitute it into the resilience function to obtain the following resilience function: S333. Calculate the resilience value of the drainage pipe network system according to the resilience function obtained in S332.

4. The resilience assessment method of the rainwater drainage pipe network system of a substation according to claim 3, characterized in that, The S331 includes: S3311. Define the failure function as the proportion of the number of pipe segments in the failure state at time t to the total number of pipe segments under the rainfall pattern with a preset return period P; S3312. Obtain the total number of pipe segments and the number of water-accumulating pipe segments in the drainage pipe network system under the return period P according to the simulation results; S3313. Obtain the failure function according to the total number of pipe segments and the number of water-accumulating pipe segments.

5. The resilience evaluation method of the rainwater drainage pipe network system of a substation according to claim 4, characterized in that The S3313 includes: S33131. Perform importance weighting on the number of pipe segments in the drainage pipe network system under the return period P; S33132. Obtain the calculation formula for the boundary centrality. The calculation formula for the boundary centrality is as follows: Among them, the б st (v) is the number of the shortest paths passing through the edge element v in the shortest path set s-t, and the P s is the set of catchment nodes except the drainage outlet, and the P t is the set of drainage outlet nodes; S33133. Obtain the failure function according to the boundary centrality and the sub-catchment area of the pipe segment. The failure function is as follows: wherein, A(v) is the area of the sub-catchment area, and N floor (P) is the number of weighted product pipe segments under the recurrence interval P, and N total is the total number of weighted pipe segments, and L is the set of all pipe segments in the drainage pipe network system.

6. The resilience evaluation method of the rainwater drainage pipe network system of a substation according to claim 1, characterized in that The S2 includes: S21. Obtain a rainstorm intensity formula. The rainstorm intensity formula is as follows: Where, q is the designed rainstorm intensity, t is the precipitation time, t = 0 represents the initial time of the corresponding rainfall event, P is the return period of the rainstorm, A1 is a rainwater parameter, C is a rainwater variation parameter, b is a precipitation duration correction parameter, and n is a rainstorm attenuation index; S22. Design a rain pattern according to the rainstorm intensity formula and obtain data of multiple rain patterns; S23. Generate a rainfall dataset of the return period according to the data of the rain pattern, input the rainfall dataset into the drainage pipe network system model for simulation, and obtain simulation results.

7. The method for evaluating the resilience of the rainwater drainage pipe network system of a substation according to claim 6, wherein The S22 includes: S221. Set the duration time and rain peak coefficient of the rainfall process, and obtain the time when the rainfall intensity reaches the peak according to the duration time and the rain peak coefficient; S222. Calculate the rainfall intensity curves for multiple recurrence periods respectively according to the time when the rainfall intensity reaches the peak and the rainstorm intensity formula; S223. Discretize the rainfall intensity curves to obtain the data of the rainfall pattern.

8. The resilience assessment method for the rainwater drainage pipe network system of a substation according to claim 1, characterized in that The S1 includes: S11. Construct an initial model of the drainage pipe network system in the area where the substation is located; S12. Obtain the historical rainstorm records of the area, and set a training data set according to the historical rainstorm records; S13. Train the initial model according to the training data set to obtain a training result. When the training result is within a preset range, generate a drainage pipe network system model.

9. A resilience assessment system for the rainwater drainage pipe network system of a substation, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the resilience evaluation method for the substation rainwater drainage pipe network system according to any one of claims 1 to 8.

10. A computer storage medium, characterized in that, A computer program is stored thereon. When the computer program is executed by the processor, it implements the resilience evaluation method for the substation rainwater drainage pipe network system according to any one of claims 1 to 8.

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