Multi-station Cooperative Scheduling Method and System for Abnormal Power Failure of Pumping Stations in Long-distance Pipeline Networks

Abstract

The present invention provides a multi-station collaborative scheduling method and system for abnormal power failure of pump stations in long-distance pipeline networks, belonging to the technical field of optimal scheduling. Specifically, it includes: taking the other pump stations except the power-failure pump station as adjustment targets, generating multiple sets of adjustment plans with the adjustment ranges of the water pumps in different adjustment targets as constraint conditions, determining the screening and scheduling plans in the adjustment plans based on the pressure wave data and water hammer data of the long-distance pipeline network during the adjustment process, and determining the scheduling processing plans in the screening and scheduling plans based on the matching situation between the heating data of the screening and scheduling plans and the heating demand, and combining the adjustment data of different adjustment targets and the interval distance from the power-failure pump station, thereby improving the operation stability of the heating pipeline network.

Description

Technical Field

[0001] The present invention belongs to the technical field of optimal scheduling, and particularly relates to a multi-station collaborative scheduling method and system for abnormal power failure of pump stations in a long-distance pipeline network. Background Art

[0002] In order to meet the transportation and processing of the heating flow in the long-distance pipeline network, multiple pump stations are often set in different regions of the long-distance pipeline network. However, at the same time, during the operation process, it is inevitable that some pump stations will have abnormal power outages. On this basis, how to achieve the collaborative scheduling of the remaining pump stations and ensure the reliability of heating has become an urgent technical problem to be solved.

[0003] In view of the above technical problems, specifically, the present application provides a multi-station collaborative scheduling method and system for abnormal power failure of pump stations in a long-distance pipeline network. Summary of the Invention

[0004] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0005] In the first aspect, the present application provides a multi-station collaborative scheduling method for abnormal power failure of pump stations in a long-distance pipeline network, specifically including:

[0006] S1: Identify the power-off pump stations based on the analysis results of the power supply data of the pump stations in the long-distance pipeline network, perform flexible power-off processing on the power-off pump stations, obtain the distribution data of the power-off pump stations in the long-distance pipeline network, and when the distribution data meets the requirements, proceed to the next step;

[0007] S2: Determine the matching situation between different power-off pump stations and different types of power-off reasons based on the analysis results of the power-off alarm signals of different power-off pump stations, and combine the power-off processing duration of different power-off reasons. When the power-off duration of the power-off pump stations does not meet the requirements, proceed to the next step;

[0008] S3: Take the other pump stations except the power-off pump stations as the adjustment targets, generate multiple groups of adjustment plans with the adjustment ranges of the water pumps in different adjustment targets as the constraint conditions, and determine the screening and scheduling plans in the adjustment plans based on the pressure wave data and water hammer data of the long-distance pipeline network during the adjustment process;

[0009] S4: Based on the matching situation between the heating data of the screening and scheduling plans and the heating demand, and combining the adjustment data of different adjustment targets and the interval distances from the power-off pump stations, determine the scheduling processing plans in the screening and scheduling plans.

[0010] The beneficial effects of the present invention are as follows:

[0011] Based on the matching situation between different power-off pump stations and different types of power-off causes, and the power-off handling duration of different power-off causes, it is determined that the power-off duration of the power-off pump station does not meet the requirements. Thus, an accurate assessment of the impact duration on the power-off pump station is achieved from the analysis and processing results of the power-off causes of multiple power-off pump stations. This not only ensures the reliability of heat supply processing by generating a scheduling plan in the case of a long power-off duration, but also avoids the impact on the service life of the pump station caused by frequent adjustment processing of the pump station in the case of a short power-off duration.

[0012] Based on the matching situation between the heat supply data of the screened scheduling plan and the heat supply demand, the adjustment data of different adjustment targets, and the interval distance from the power-off pump station, the scheduling processing plan in the screened scheduling plan is determined. This not only ensures that the heat supply data of the screened scheduling plan can meet the required heat supply demand to a certain extent, but also avoids the technical problem of too large an adjustment amplitude for adjustment targets with a relatively short interval distance from the power-off pump station, which may lead to greater difficulty in adjustment processing after the power-off pump station resumes power supply. Thus, the determination of the scheduling processing plan for adjustment targets from multiple dimensions is achieved, ensuring the reliability of heat supply processing.

[0013] A further technical solution is that the power-off pump station is a pump station where the voltage drop depth of the power supply data does not meet the requirements or there is a power-off in the power supply data.

[0014] A further technical solution is to perform flexible power-off processing on the power-off pump station, which specifically includes:

[0015] Based on the PCS and energy storage system, stabilize the power supply voltage and current of the water pump of the power-off pump station, and perform a downward adjustment process on the power supply voltage and current at a preset downward rate until the power-off is successful.

[0016] A further technical solution is to determine whether the distribution data meets the requirements, which specifically includes:

[0017] Based on the distribution data of the power-off pump stations in the long-distance pipeline network, determine the number of the power-off pump stations;

[0018] Based on the distribution interval situation between different power-off pump stations, determine the distribution data and interval distance of the non-power-off pump stations between different adjacent power-off pump stations, and determine the abnormal impact pump stations among the power-off pump stations;

[0019] According to the average value of the proportion of the number of power-off pump stations and the proportion of the number of abnormal impact pump stations in the long-distance pipeline network, determine the power-off impact coefficient of the long-distance pipeline network, and use the power-off abnormal coefficient to determine whether the distribution data meets the requirements.

[0020] A further technical solution is that the abnormal influence pumping station is a power-off pumping station where there is no non-power-off pumping station between it and the adjacent power-off pumping stations, and the interval distance between it and the adjacent power-off pumping stations is greater than a preset interval distance.

[0021] A further technical solution is that when the power-off influence coefficient is greater than a preset influence coefficient threshold, it is determined that the distribution data does not meet the requirements.

[0022] A further technical solution is that the method for determining the scheduling processing plan in the screening and scheduling plan is as follows:

[0023] Based on the matching situation between the heating data and the heating demand of the screening and scheduling plan, determine the deviation amount between the heat supply of the screening and scheduling plan and the heating demand, and use the ratio of the deviation amount to the heating demand to determine the heating matching deviation coefficient of the screening and scheduling plan;

[0024] According to the adjustment data of different scheduling objectives, determine the adjustment amount of different scheduling objectives, and use the ratio of the adjustment amount of different adjustment objectives to the basic operation data of the adjustment objectives to determine the adjustment amplitude coefficient of different adjustment objectives;

[0025] Based on the interval distance between different adjustment objectives and the power-off pumping stations, determine the adjacent adjustment objectives in the adjustment objectives. Through the average value of the heating matching deviation coefficient of the screening and scheduling plan, the adjustment amplitude coefficients of different adjustment objectives, and the adjustment amplitude coefficients of the adjacent adjustment objectives, determine the adaptation deviation coefficient of the screening and scheduling plan, and use the adaptation deviation coefficient to determine the scheduling processing plan in the screening and scheduling plan.

[0026] A further technical solution is that the adjustment plan is the screening and scheduling plan with the smallest adaptation deviation coefficient.

[0027] A further technical solution is that the adjacent adjustment objective is an adjustment objective whose interval distance from the nearest power-off pumping station is within a preset distance range.

[0028] On the other hand, an embodiment of the present application provides a computer system, on which a computer program is stored. When the computer program is executed on the computer, the computer is made to execute the above-mentioned multi-station collaborative scheduling method for abnormal power-off of pumping stations in a long-distance pipeline network.

[0029] On the other hand, an embodiment of the present application provides a computer program product. The computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above-mentioned multi-station collaborative scheduling method for abnormal power-off of pumping stations in a long-distance pipeline network. Description of the Drawings

[0030] The above and other features and advantages of the present invention will become more apparent by describing its exemplary embodiments in detail with reference to the accompanying drawings.

[0031] Figure 1 is a flowchart of a multi - station collaborative scheduling method for abnormal power outage of pumping stations in a long - distance pipeline network;

[0032] Figure 2 is a flowchart for judging whether the distribution data meets the requirements;

[0033] Figure 3 is a flowchart for determining that the power outage duration of the power - off pumping station does not meet the requirements;

[0034] Figure 4 is a flowchart of a method for determining the screening of scheduling schemes in a scheduling scheme. Detailed Embodiments

[0035] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. Like reference numerals in the figures denote the same or similar structures, and thus their detailed description will be omitted.

[0036] The terms "a", "an", "the", and "said" are used to denote the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to mean an open inclusion and mean that there may be additional elements / components / etc. in addition to the listed elements / components / etc.

[0037] During the operation of a long - distance pipeline network, power outages of pumping stations often occur, which affects the operation reliability of the long - distance pipeline network. Therefore, through the collaborative scheduling of the non - power - off pumping stations in the long - distance pipeline network, the operation reliability of the long - distance pipeline network is satisfied, and at the same time, the impact on the heating plan is reduced.

[0038] Example 1

[0039] To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, a multi - station collaborative scheduling method for abnormal power outage of pumping stations in a long - distance pipeline network is provided, specifically including:

[0040] S1: Identify the power - off pumping stations based on the analysis results of the power supply data of the pumping stations in the long - distance pipeline network, perform flexible power - off processing on the power - off pumping stations, obtain the distribution data of the power - off pumping stations in the long - distance pipeline network, and when the distribution data meets the requirements, proceed to the next step;

[0041] When the proportion of power-off pump stations in the long-distance pipeline network is less than 0.1, it is determined that the distribution data of the power-off pump stations in the long-distance pipeline network meets the requirements.

[0042] S2: Determine the matching situation between different power-off pump stations and different types of power-off causes based on the analysis results of the power-off alarm signals of different power-off pump stations, and combine the power-off handling duration of different power-off causes. When it is determined that the power-off duration of the power-off pump station does not meet the requirements, proceed to the next step;

[0043] When there is a power-off pump station with a power-off handling duration of more than 2 hours, it is determined that the power-off duration of the power-off pump station does not meet the requirements.

[0044] S3: Take the other pump stations except the power-off pump stations as adjustment targets, generate multiple groups of adjustment plans with the adjustment ranges of the water pumps in different adjustment targets as constraint conditions, and determine the screening scheduling plan in the scheduling plan based on the pressure wave data and water hammer data of the long-distance pipeline network during the adjustment process;

[0045] The screening scheduling plan is an adjustment plan where there is no position in the long-distance pipeline network where the pressure wave data and water hammer data do not meet the requirements.

[0046] S4: Based on the matching situation between the heating data of the screening scheduling plan and the heating demand, and combine the adjustment data of different adjustment targets and the distance from the power-off pump station to determine the scheduling processing plan in the screening scheduling plan.

[0047] Determine the heating matching deviation coefficient of the screening scheduling plan by taking the ratio of the deviation between the heat supply of the screening scheduling plan and the heating demand to the heating demand. Determine the adjustment amplitude coefficient of different adjustment targets by taking the ratio of the adjustment amount of different adjustment targets to the basic operation data of the adjustment targets. Take the adjustment targets with a distance from the power-off pump station less than the preset distance as adjacent adjustment targets. Determine the adaptation deviation coefficient of the screening scheduling plan through the average value of the heating matching deviation coefficient of the screening scheduling plan, the average value of the adjustment amplitude coefficients of different adjustment targets, and the average value of the adjustment amplitude coefficients of adjacent adjustment targets. Take the screening scheduling plan with the smallest adaptation deviation coefficient as the scheduling processing plan.

[0048] Furthermore, the power-off pump station is a pump station where the voltage drop depth of the power supply data does not meet the requirements or there is a power-off in the power supply data.

[0049] Specifically, the flexible power-off treatment of the power-off pump station is carried out, which specifically includes:

[0050] Based on the PCS and energy storage system, stabilize the power supply voltage and current of the water pumps in the power-off pumping station, and perform a down-regulation process on the power supply voltage and current at a preset decreasing rate until the power-off is successful.

[0051] PCS is the Power Conversion System, which is used to convert the electric energy of the energy storage system and maintain the power supply voltage and current of the water pumps in the power-off pumping station.

[0052] It should be noted that, as Figure 2 shown, determining that the distribution data meets the requirements specifically includes:

[0053] Based on the distribution data of the power-off pumping stations in the long-distance pipeline network, determine the number of the power-off pumping stations;

[0054] Based on the distribution intervals between different power-off pumping stations, determine the distribution data and interval distances of the non-power-off pumping stations between different adjacent power-off pumping stations, and determine the abnormal influence pumping stations among the power-off pumping stations;

[0055] According to the average values of the proportion of the number of power-off pumping stations and the proportion of the number of abnormal influence pumping stations in the long-distance pipeline network, determine the power-off influence coefficient of the long-distance pipeline network, and use the power-off abnormal coefficient to determine whether the distribution data meets the requirements.

[0056] Furthermore, the abnormal influence pumping station is a power-off pumping station that has no non-power-off pumping station between it and the adjacent power-off pumping station and the interval distance between it and the adjacent power-off pumping station is greater than the preset interval distance.

[0057] It can be understood that when the power-off influence coefficient is greater than the preset influence coefficient threshold, it is determined that the distribution data does not meet the requirements.

[0058] Specifically, when the distribution data does not meet the requirements, directly transfer to step S3 to determine the scheduling plan.

[0059] Optionally, determining that the distribution data meets the requirements specifically includes:

[0060] S11: Based on the distribution data of the power-off pumping stations in the long-distance pipeline network, determine the number of the power-off pumping stations. Based on the distribution intervals between different power-off pumping stations, determine the distribution data and interval distances of the non-power-off pumping stations between different adjacent power-off pumping stations, determine the abnormal influence pumping stations among the power-off pumping stations, and according to the average values of the proportion of the number of power-off pumping stations and the proportion of the number of abnormal influence pumping stations in the long-distance pipeline network, determine the power-off influence coefficient of the long-distance pipeline network;

[0061] It should be noted that the power outage impact coefficient of the long-distance pipeline network reflects the number of power outage pump stations among the end pump stations in the long-distance pipeline network and the degree of aggregation of their distribution. For a long-distance pipeline network with a large number of end pump stations and a high degree of aggregation in the distribution, and a relatively large number of abnormal impact pump stations, even if the power outage duration of different power outage pump stations may be short, the impact on the entire long-distance pipeline network is relatively large. Therefore, based on this, it can be directly determined that the distribution data does not meet the requirements.

[0062] When the distribution data does not meet the requirements, it directly proceeds to step S3 to generate the scheduling plan for other pump stations, thereby improving the efficiency of generating the scheduling plan for pump stations.

[0063] S12: Determine the power outage abnormal impact coefficient of different power outage pump stations based on the interval distance between different power outage pump stations and adjacent power outage pump stations, and the distribution positions of non-power outage pump stations between the power outage pump stations and the adjacent power outage pump stations.

[0064] Schematically, when the interval distance between a power outage pump station and an adjacent power outage pump station is short and the number of non-power outage pump stations within the interval distance between the power outage pump station and the adjacent power outage pump station is small, it indicates that the distribution of power outage pump stations is concentrated. Therefore, for power outage pump stations with concentrated distribution, their impact on the entire long-distance pipeline network is higher.

[0065] Schematically, for the power outage abnormal impact coefficient, based on the interval distance between different power outage pump stations and adjacent power outage pump stations, and the distribution positions of non-power outage pump stations between the power outage pump stations and the adjacent power outage pump stations, mathematical models such as the analytic hierarchy process can be used to determine the power outage abnormal impact coefficient.

[0066] S13: Based on the power outage abnormal impact coefficient of different power outage pump stations, and in combination with the power outage impact coefficient of the long-distance pipeline network, determine the comprehensive abnormal impact coefficient of the long-distance pipeline network, and use the comprehensive abnormal impact coefficient to determine whether the distribution data meets the requirements.

[0067] Optionally, when the comprehensive abnormal impact coefficient is greater than the preset abnormal impact coefficient threshold, it is determined that the distribution data does not meet the requirements.

[0068] Schematically, the comprehensive abnormal impact coefficient of the long-distance pipeline network is determined based on the sum of the power outage abnormal impact coefficients of different power outage pump stations and the power outage impact coefficient of the long-distance pipeline network, or a mathematical model based on the analytic hierarchy process can be constructed according to the power outage abnormal impact coefficients of different power outage pump stations and the power outage impact coefficient of the long-distance pipeline network for determination.

[0069] Optionally, the following content is included in the above step S11:

[0070] S111: Based on the distribution data of the power-off pump stations in the long-distance pipeline network, determine the number of the power-off pump stations. When either the number of the power-off pump stations or the proportion of the number of the power-off pump stations in the long-distance pipeline network does not meet the requirements, it is determined that the distribution data does not meet the requirements. When both the number of the power-off pump stations and the proportion of the number of the power-off pump stations in the long-distance pipeline network meet the requirements, proceed to step S112;

[0071] Illustratively, when either the number of the power-off pump stations or the proportion of the number of the power-off pump stations in the long-distance pipeline network does not meet the requirements, it is determined that the number of the power-off pump stations in the heat supply pipeline network is relatively large. For a long-distance pipeline network with a relatively large number of power-off pump stations, it can be directly determined that its distribution data does not meet the requirements.

[0072] Illustratively, whether the number of the power-off pump stations and the proportion of the number of the power-off pump stations in the long-distance pipeline network meet the requirements can be determined by using a fixed threshold. When it is greater than the fixed threshold, it is determined that the distribution data does not meet the requirements.

[0073] S112: Based on the distribution intervals between different power-off pump stations, determine the distribution data and the interval distances of the non-power-off pump stations between different adjacent power-off pump stations, and determine the abnormal influence pump stations among the power-off pump stations. When either the number of the abnormal influence pump stations in the long-distance pipeline network or the proportion of the number of the abnormal influence pump stations in the long-distance pipeline network does not meet the requirements, it is determined that the distribution data does not meet the requirements. When both the number of the abnormal influence pump stations in the long-distance pipeline network and the proportion of the number of the abnormal influence pump stations in the long-distance pipeline network meet the requirements, proceed to step S113;

[0074] Optionally, when either the number of the abnormal influence pump stations or the proportion of the number of the abnormal influence pump stations in the long-distance pipeline network does not meet the requirements, it is determined that the number of the abnormal influence pump stations with a greater degree of abnormality in the heat supply pipeline network is relatively large. For a long-distance pipeline network with a relatively large number of abnormal influence pump stations, it can be directly determined that its distribution data does not meet the requirements.

[0075] Illustratively, whether the number of the abnormal influence pump stations and the proportion of the number of the power-off pump stations in the long-distance pipeline network meet the requirements can be determined by using a fixed threshold. When it is greater than the fixed threshold, it is determined that the distribution data does not meet the requirements.

[0076] S113: According to the average values of the proportion of the number of the power-off pump stations and the proportion of the number of the abnormal influence pump stations in the long-distance pipeline network, determine the power-off influence coefficient of the long-distance pipeline network. When the power-off abnormality coefficient does not meet the requirements, it is determined that the distribution data does not meet the requirements. When the endpoint abnormality coefficient meets the requirements, proceed to step S12.

[0077] Optionally, the above step S12 includes the following content:

[0078] S121: Determine the power-off abnormal influence coefficients of different power-off pump stations based on the interval distances between different power-off pump stations and adjacent power-off pump stations, as well as the distribution positions of the non-power-off pump stations between the power-off pump stations and the adjacent power-off pump stations. When the power-off abnormal influence coefficients of different power-off pump stations all meet the requirements, it is determined that the distribution data meets the requirements. When there is a power-off pump station with a power-off abnormal influence coefficient that does not meet the requirements, go to step S122;

[0079] It should be noted that when the power-off abnormal influence coefficients all meet the requirements, it is determined that the influence degrees of the power-off pump stations on the long-distance pipeline network all meet the requirements. Therefore, on this basis, when the power-off abnormal coefficient requirements have been determined in the above steps, that is, when the number of power-off pump stations meets the requirements, it can be directly determined that the influence degree on the long-distance pipeline network is low, and thus it can be directly determined that the distribution data meets the requirements.

[0080] Specifically, whether the power-off abnormal influence coefficient of the power-off pump station meets the requirements can be determined by setting a fixed threshold.

[0081] S122: Obtain the number of power-off pump stations with power-off abnormal influence coefficients that do not meet the requirements. When the number of power-off pump stations with power-off abnormal influence coefficients that do not meet the requirements is greater than the preset number of power-off pump stations, it is determined that the distribution data does not meet the requirements. When the number of power-off pump stations with power-off abnormal influence coefficients that do not meet the requirements is not greater than the preset number of power-off pump stations, go to step S13.

[0082] Furthermore, the matching situation between the power-off pump station and different types of power-off reasons is determined according to the matching quantity of the alarm signals between the power-off pump station and different types of power-off reasons.

[0083] It should be noted that as Figure 3 shown, determining that the power-off duration of the power-off pump station does not meet the requirements specifically includes:

[0084] Based on the analysis result of the power-off alarm signal of the power-off pump station, determine the proportion of the matching quantity of the alarm signal of the power-off pump station and the matching alarm signals of different types of power-off reasons, and use the proportion of the matching quantity to determine the matching weight coefficient of different types of power-off reasons;

[0085] According to the power-off processing duration of different types of power-off reasons and the matching weight coefficient of different types of power-off reasons, determine the power-off prediction duration of the power-off pump station;

[0086] Based on the power-off prediction durations of different power-off pump stations, determine whether the power-off duration of the power-off pump station meets the requirements.

[0087] Further, when the number of power-off pump stations with a power-off prediction duration greater than the preset power-off prediction market threshold or the number of power-off pump stations with a power-off prediction duration within the preset power-off prediction duration interval does not meet the requirements, it is determined that the power-off duration of the power-off pump stations does not meet the requirements.

[0088] Specifically, when the power-off duration of the power-off pump stations meets the requirements, there is no need to perform scheduling processing on other pump stations except for the power-off pump stations.

[0089] Optionally, determining that the power-off duration of the power-off pump stations does not meet the requirements specifically includes:

[0090] S21: Based on the analysis result of the power-off alarm signal of the power-off pump station, determine the proportion of the matching quantity of the alarm signal of the power-off pump station and the matching alarm signals of different types of power-off reasons, and use the proportion of the matching quantity to determine the matching weight coefficient for different types of power-off reasons. The power-off pump stations with the maximum value of the matching weight coefficients for different types being less than the preset matching coefficient threshold are regarded as pump stations with unknown reasons.

[0091] S22: Use the power-off processing duration of different types of power-off reasons to determine the power-off reasons with a power-off processing duration greater than the preset processing duration, and regard them as the screened power-off reasons. The power-off pump stations with the matching weight coefficient for the screened power-off reasons greater than the preset matching coefficient threshold are regarded as the screened matching pump stations.

[0092] S23: Determine the power-off prediction duration of the power-off pump stations according to the power-off processing duration of different types of power-off reasons and the matching weight coefficient for different types of power-off reasons. Based on the power-off prediction durations of different power-off pump stations, determine whether the power-off duration of the power-off pump stations meets the requirements.

[0093] Optionally, before entering step S22, the following content is further included:

[0094] Judge that when the number of pump stations with unknown reasons does not meet the requirements, it is determined that the power-off duration of the power-off pump stations does not meet the requirements. When the number of pump stations with unknown reasons meets the requirements, then transfer to step S22.

[0095] It should be noted that when the number of pump stations with unknown reasons is large, it means that the number of pump stations for which the power-off duration cannot be accurately determined is large at this time. Since the power-off duration of the power-off pump stations cannot be accurately judged, it can be directly determined at this time that the power-off duration of the power-off pump stations does not meet the requirements.

[0096] In addition, it should be noted that judging whether the number of pump stations with unknown reasons meets the requirements is determined by means of a fixed threshold in this application.

[0097] Optionally, the above step S22 includes the following:

[0098] S221: Determine the power outage causes with power outage processing durations greater than the preset processing duration using the power outage processing durations of different types of power outage causes, and use them as the screened power outage causes. When the sum of the matching weight coefficients of different power outage pump stations and the screened power outage causes is greater than the preset weight coefficient threshold, it is determined that the power outage duration of the power outage pump station does not meet the requirements. When the sum of the matching weight coefficients of different power outage pump stations and the screened power outage causes is not greater than the preset weight coefficient threshold, proceed to step S222;

[0099] Specifically, for the power outage causes with processing durations greater than the preset processing duration, when the matching degree between the power outage pump station and it is high, that is, when the sum of the matching weight coefficients is greater than the preset weight coefficient threshold, it indicates that the power outage processing duration of the power outage pump stations in the long-distance pipeline network is very long at this time. Therefore, it can be directly determined that the power outage duration is difficult to meet the requirements.

[0100] By using the evaluation of the matching weight coefficients of the screened power outage causes, the possibility of the screened power outage causes occurring in the power outage pump station can be realized conveniently and quickly, and then the processing efficiency of whether the power outage duration meets the requirements can be improved.

[0101] S222: Use the power outage pump stations with matching weight coefficients greater than the preset matching coefficient threshold for the screened power outage causes as the screened matching pump stations. When the number of the screened matching pump stations does not meet the requirements, it is determined that the power outage duration of the power outage pump station does not meet the requirements. When the number of the screened power outage pump stations meets the requirements, proceed to step S223;

[0102] It should be noted that when the power outage pump stations with matching weight coefficients greater than the preset matching coefficient threshold for the screened power outage causes, that is, the number of the screened matching pump stations is large, the number of pump stations with power outage durations greater than the preset processing duration is large. Therefore, it can be directly determined that the power outage duration of the power outage pump station does not meet the requirements.

[0103] Specifically, the judgment of whether the number of the screened matching pump stations meets the requirements can be realized by means of a fixed number threshold of the screened matching pump stations.

[0104] S223: Determine the screened matching weight coefficients based on the matching weight coefficients of different screened power outage pump stations and the screened power outage causes. When the screened matching weight coefficients do not meet the requirements, it is determined that the power outage duration of the power outage pump station does not meet the requirements. When the screened matching weight coefficients meet the requirements, proceed to step S23.

[0105] Optionally, the screening matching weight coefficient is determined by constructing a mathematical model of the analytic hierarchy process according to the matching weight coefficients of different screening power-off pump stations and the screening power-off reasons, or it can be determined by the expert scoring method, or by the maximum value of the matching weight coefficient of the screening power-off pump station and the screening power-off reason.

[0106] Specifically, when the screening matching weight coefficient is greater than a fixed threshold, it indicates that the power-off processing duration at this time is very long and difficult to meet the requirements.

[0107] Furthermore, the power-off reasons include pump station equipment failures, external power distribution equipment failures, and abnormal tripping.

[0108] It should be noted that the pressure wave data and water hammer data of the long-distance pipeline network are determined according to the simulation results of the hydraulic simulation model of the long-distance pipeline network.

[0109] Specifically, as Figure 4 shown, the method for determining the screening scheduling plan in the adjustment plan is as follows:

[0110] Based on the pressure wave data and water hammer data of the long-distance pipeline network in the adjustment process of the adjustment plan, determine the positions where the pressure wave data and water hammer data of the long-distance pipeline network do not meet the requirements, and use them as the operation abnormal positions;

[0111] According to the distribution data of the operation abnormal positions, determine the operation abnormal positions whose interval distance from adjacent operation abnormal positions is less than the preset interval distance, and use them as the aggregation abnormal positions;

[0112] Based on the quantity proportion of the aggregation abnormal positions in the operation abnormal positions and the quantity of the operation abnormal positions, determine the pipeline network influence coefficient of the adjustment plan, and use the pipeline network influence coefficient to determine whether the adjustment plan is a screening scheduling plan.

[0113] Furthermore, the method for determining the pipeline network influence coefficient of the adjustment plan is as follows:

[0114] Based on the quantity of the operation abnormal positions in the long-distance pipeline network, determine the preset influence coefficient of the long-distance pipeline network under the quantity of the operation abnormal positions;

[0115] Based on the sum of the quantity proportion of the aggregation abnormal positions in the operation abnormal positions and the weight of the preset influence coefficient, determine the pipeline network influence coefficient of the adjustment plan.

[0116] It can be understood that the value range of the pipeline network influence coefficient is between 0 and 1. When the pipeline network influence coefficient is less than the preset influence coefficient threshold, it is determined that the adjustment plan is a screening scheduling plan.

[0117] It should be noted that the method for determining the scheduling processing scheme in the screening scheduling scheme is as follows:

[0118] Based on the matching situation between the heating data and the heating demand of the screening scheduling scheme, determine the deviation amount between the heat supply amount and the heating demand amount of the screening scheduling scheme, and use the ratio of the deviation amount to the heating demand amount to determine the heating matching deviation coefficient of the screening scheduling scheme;

[0119] According to the adjustment data of different scheduling objectives, determine the adjustment amount of different scheduling objectives, and use the ratio of the adjustment amount of different adjustment objectives to the basic operation data of the adjustment objective to determine the adjustment amplitude coefficient of different adjustment objectives;

[0120] Based on the interval distances between different adjustment objectives and the power-off pumping stations, determine the adjacent adjustment objectives in the adjustment objectives. Through the average value of the heating matching deviation coefficient of the screening scheduling scheme, the adjustment amplitude coefficients of different adjustment objectives, and the adjustment amplitude coefficients of the adjacent adjustment objectives, determine the adaptation deviation coefficient of the screening scheduling scheme, and use the adaptation deviation coefficient to determine the scheduling processing scheme in the screening scheduling scheme.

[0121] Furthermore, the adjustment scheme is the screening scheduling scheme with the smallest adaptation deviation coefficient.

[0122] Specifically, the adjacent adjustment objective is an adjustment objective whose interval distance from the nearest power-off pumping station is within a preset distance range.

[0123] Embodiment 2

[0124] On the other hand, an embodiment of the present application provides a computer system on which a computer program is stored. When the computer program is executed on the computer, the computer is made to execute the above-mentioned multi-station collaborative scheduling method for abnormal power-off of pumping stations in a long-distance pipeline network.

[0125] Embodiment 3

[0126] On the other hand, an embodiment of the present application provides a computer program product. The computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above-mentioned multi-station collaborative scheduling method for abnormal power-off of pumping stations in a long-distance pipeline network.

[0127] In the embodiments of the present invention, the term "a plurality of" refers to two or more, unless otherwise clearly defined. Terms such as "installation", "connection", "fixation", etc. should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific situations.

[0128] In the description of the embodiments of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "upper" and "lower" is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the embodiments of the present invention.

[0129] In the description of this specification, the description of terms such as "one embodiment" and "one preferred embodiment" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0130] The above are only the preferred embodiments of the embodiments of the present invention and are not used to limit the embodiments of the present invention. For those skilled in the art, the embodiments of the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the embodiments of the present invention shall be included within the protection scope of the embodiments of the present invention.

Claims

1. A multi-station collaborative scheduling method for abnormal power outage of pumping stations in long-distance pipeline networks, characterized in that, Specifically, it includes: Identifying and processing the power-off pump stations based on the analysis results of the power supply data of the pump stations in the long-distance pipeline network, performing flexible power-off processing on the power-off pump stations, obtaining the distribution data of the power-off pump stations in the long-distance pipeline network, and when the distribution data meets the requirements, proceeding to the next step; Determining the matching situation between different power-off pump stations and different types of power-off reasons based on the analysis results of the power-off alarm signals of different power-off pump stations, and combining the power-off processing duration of different power-off reasons. When the power-off duration of the power-off pump stations does not meet the requirements, proceeding to the next step; Regarding the other pump stations except the power-off pump stations as the adjustment targets, generating multiple groups of adjustment schemes with the adjustment range of the water pumps in different adjustment targets as the constraint conditions, and determining the screening and dispatching schemes in the adjustment schemes based on the pressure wave data and water hammer data of the long-distance pipeline network during the adjustment process; Based on the matching situation between the heating data of the screening and dispatching schemes and the heating demand, and combining the adjustment data of different adjustment targets and the interval distance from the power-off pump stations, determining the dispatching processing schemes in the screening and dispatching schemes; Judging that the distribution data meets the requirements specifically includes: Determining the number of the power-off pump stations based on the distribution data of the power-off pump stations in the long-distance pipeline network; Based on the distribution intervals between different power-off pump stations, determining the distribution data and interval distances of the non-power-off pump stations between different adjacent power-off pump stations, and determining the abnormal influence pump stations among the power-off pump stations; Determining the power-off influence coefficient of the long-distance pipeline network according to the average values of the proportion of the number of power-off pump stations and the proportion of the number of abnormal influence pump stations in the long-distance pipeline network, and using the power-off influence coefficient to determine whether the distribution data meets the requirements; Determining that the power-off duration of the power-off pump stations does not meet the requirements specifically includes: Based on the analysis results of the power-off alarm signals of the power-off pump stations, determining the proportion of the matching number of the alarm signals of the power-off pump stations and the matching alarm signals of different types of power-off reasons, and using the proportion of the matching number to determine the matching weight coefficient for different types of power-off reasons; Determining the predicted power-off duration of the power-off pump stations according to the power-off processing duration of different types of power-off reasons and the matching weight coefficient for different types of power-off reasons; Based on the predicted power-off duration of different power-off pump stations, determining whether the power-off duration of the power-off pump stations meets the requirements.

2. The multi-station collaborative scheduling method for abnormal power outage of pumping stations in long-distance pipeline networks according to claim 1, characterized in that The power-off pump stations are pump stations where the voltage drop depth of the power supply data does not meet the requirements or there is a power outage in the power supply data.

3. The multi-station collaborative scheduling method for abnormal power outage of pump stations in long-distance pipeline networks according to claim 1, characterized in that, Performing flexible power-off processing on the power-off pump stations specifically includes: Based on the PCS and energy storage systems, stabilizing the power supply voltage and current of the water pumps in the power-off pump stations, and performing a downward adjustment process on the power supply voltage and current at a preset downward rate until the power-off is successful.

4. The multi-station collaborative scheduling method for abnormal power outage of pumping stations in long-distance pipeline networks according to claim 3, wherein The abnormal influence pump stations are power-off pump stations where there are no non-power-off pump stations between adjacent power-off pump stations and the interval distance between adjacent power-off pump stations is greater than the preset interval distance.

5. The multi-station collaborative scheduling method for abnormal power outage of pump stations in long-distance pipeline networks according to claim 1, wherein, Judging that the distribution data meets the requirements specifically includes: Based on the distribution data of the power-off pump stations in the long-distance pipeline network, determine the number of the power-off pump stations, determine the distribution data and the interval distance of the non-power-off pump stations between different adjacent power-off pump stations according to the distribution interval between different power-off pump stations, determine the abnormal influence pump stations among the power-off pump stations, and determine the power-off influence coefficient of the long-distance pipeline network according to the average values of the proportion of the number of power-off pump stations and the proportion of the number of abnormal influence pump stations in the long-distance pipeline network; Determine the power-off abnormal influence coefficients of different power-off pump stations according to the interval distances between different power-off pump stations and adjacent power-off pump stations and the distribution positions of the non-power-off pump stations between the power-off pump stations and the adjacent power-off pump stations; Based on the power-off abnormal influence coefficients of different power-off pump stations, and in combination with the power-off influence coefficient of the long-distance pipeline network, determine the comprehensive abnormal influence coefficient of the long-distance pipeline network, and use the comprehensive abnormal influence coefficient to determine whether the distribution data meets the requirements.

6. The multi-station collaborative scheduling method for abnormal power outage of pump stations in long-distance pipeline networks according to claim 1, characterized in that When there is a power-off pump station with a power-off prediction duration greater than the preset power-off prediction duration threshold or the number of power-off pump stations with a power-off prediction duration within the preset power-off prediction duration interval does not meet the requirements, it is determined that the power-off duration of the power-off pump stations does not meet the requirements.

7. The multi-station collaborative scheduling method for abnormal power outage of pumping stations in long-distance pipeline networks according to claim 1, characterized in that, The method for determining the scheduling processing plan in the screening scheduling plan is as follows: Based on the matching situation between the heating data and the heating demand of the screening scheduling plan, determine the deviation amount between the heating supply amount and the heating demand amount of the screening scheduling plan, and use the ratio of the deviation amount to the heating demand amount to determine the heating matching deviation coefficient of the screening scheduling plan; According to the adjustment data of different scheduling targets, determine the adjustment amounts of different scheduling targets, and use the ratio of the adjustment amounts of different adjustment targets to the basic operation data of the adjustment targets to determine the adjustment amplitude coefficients of different adjustment targets; Based on the interval distances between different adjustment targets and the power-off pump stations, determine the adjacent adjustment targets among the adjustment targets. Through the average value of the heating matching deviation coefficient of the screening scheduling plan, the average values of the adjustment amplitude coefficients of different adjustment targets, and the average value of the adjustment amplitude coefficients of the adjacent adjustment targets, determine the adaptation deviation coefficient of the screening scheduling plan, and use the adaptation deviation coefficient to determine the scheduling processing plan in the screening scheduling plan.

8. A computer system having a computer program stored thereon, characterized in that when the computer program is executed in a computer, Let a computer execute a multi-station collaborative scheduling method for abnormal power-off of pump stations in a long-distance pipeline network according to any one of claims 1-7.

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