A heat pump station scheduling method, device and electronic equipment for a long pipeline network

Abstract

The present application relates to the technical field of long-distance pipe network, and discloses a heat pump station scheduling method and device for long-distance pipe network and electronic equipment, the method comprising: based on the water pump similarity between the heat pump stations of the long-distance pipe network, determining the priority scheduling pump station and the pending scheduling pump station; in response to the current scheduling instruction, based on the historical deviation of the priority scheduling pump station, determining whether the pending scheduling pump station needs to participate in scheduling; if so, determining the scheduling classification of the pending scheduling pump station; based on the scheduling classification of the priority scheduling pump station and the pending scheduling pump station, determining the scheduling scheme of the current scheduling instruction and scheduling; updating the scheduling classification of the pending scheduling pump station. The present application provides operation opportunities for different types of water pumps through type similarity driven differentiated scheduling to accumulate fault feature data, thereby effectively improving the recognition reliability of the fault diagnosis model for each type of water pump, and realizing the coordination and unity of safe and stable operation of the heating system and continuous improvement of fault diagnosis capability.

Description

Technical Field

[0001] This invention relates to the field of long-distance pipeline technology, specifically to a method, apparatus, and electronic equipment for scheduling thermal pumping stations in long-distance pipelines. Background Technology

[0002] During operation, long-distance heating pipelines require the coordinated scheduling of multiple heat pump stations along the route to achieve long-distance heat transmission and on-demand distribution. As the core power equipment of the pipeline network, the operation and sequence of each heat pump station directly determine the output capacity and response speed of the heating system. Therefore, achieving rational scheduling of heat pump stations is crucial to ensuring heating quality and safe system operation.

[0003] In existing technologies, a scheduling method based on heat load prediction is usually adopted, that is, the required heat supply flow is predicted according to parameters such as outdoor temperature and historical heat load data, and then the pump stations and combinations to be put into operation are determined according to preset scheduling rules.

[0004] However, this scheduling method only considers flow rate or temperature matching as a single objective when formulating strategies. Under this objective, heating pump stations that meet heating demand are always prioritized, leading to some heating pump stations being idle for extended periods. These stations cannot accumulate effective operational data, which is the foundation for fault diagnosis models to identify faults. Consequently, the fault diagnosis model has high reliability in identifying pump stations that operate frequently and have abundant data, but its reliability is significantly insufficient for identifying pump stations that have been idle for a long time and have sparse data. Once such data-sparse pump stations fail, the model struggles to accurately identify them in the early stages, leading to unplanned shutdowns or heating interruptions, seriously threatening the safety and stability of the heating system. Summary of the Invention

[0005] This invention provides a method, apparatus, and electronic equipment for scheduling thermal pumping stations in long-distance pipeline networks, in order to solve one of the technical problems existing in the prior art.

[0006] In a first aspect, the present invention provides a method for scheduling thermal pumping stations in long-distance pipeline networks, the method comprising: Based on the similarity of water pumps among thermal pumping stations in long-distance pipelines, priority scheduling pumping stations and undetermined scheduling pumping stations are identified. In response to the current dispatching instruction, based on the historical deviation of the priority dispatching pump stations, it is determined whether the pending dispatching pump stations need to participate in the dispatching; When a pending scheduling pump station needs to participate in scheduling, the scheduling category of the pending scheduling pump station is determined. The scheduling category is used to indicate the scheduling priority of the pending scheduling pump station. Based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations, the scheduling scheme for the current scheduling instruction is determined and the scheduling is carried out. Update the scheduling classification of pump stations with pending scheduling.

[0007] This invention identifies priority and pending-scheduling pump stations based on pump similarity among heating pump stations. On one hand, it prioritizes the accumulation of operational data for representative pump models within the system. On the other hand, by controlling the participation of pending-scheduling pump stations, it guides data-scarce models to participate in operation while ensuring heating supply. Based on this, the historical deviation data of priority pump stations determines whether pending-scheduling pump stations need to participate in scheduling. If they are required, they are categorized to clarify their priority in subsequent scheduling. Based on the scheduling categories and priority pump stations, a scheduling scheme is determined that both ensures current heating demand and accumulates fault characteristic data for scarce models. Finally, the scheduling categories are dynamically updated based on the scheduling situation, allowing the scheduling scheme to adaptively adjust to the actual state. Through model similarity-driven differentiated scheduling, different pump models are provided with operational opportunities to accumulate fault characteristic data, thereby effectively improving the reliability of the fault diagnosis model in identifying various pump models and achieving a coordinated unity between the safe and stable operation of the heating system and the continuous improvement of fault diagnosis capabilities.

[0008] In one optional implementation, based on the similarity of pumps among thermal pumping stations in the long-distance pipeline network, priority scheduling pumping stations and pending scheduling pumping stations are determined, including: For each thermal pumping station in the long-distance pipeline network, determine the same type of water pump between the thermal pumping station and each first pumping station, where the first pumping station is any other thermal pumping station besides the thermal pumping station. The proportion of the same model of water pumps between the thermal pump station and the first pump station in the total number of water pumps in the first pump station is calculated as the similarity coefficient between the thermal pump station and the first pump station. Calculate the average similarity coefficient between the thermal pumping station and all first pumping stations; Thermal pump stations with an average value greater than a preset similarity coefficient threshold are designated as priority scheduling pump stations, while other thermal pump stations are designated as pending scheduling pump stations.

[0009] This invention calculates a similarity coefficient based on the similarity of pump models among thermal pumping stations, thereby selecting priority scheduling pumping stations with representative model configurations. This continuously accumulates operational data on common models for fault diagnosis models. Simultaneously, it identifies undecided scheduling pumping stations, providing a foundation for subsequent differentiated scheduling based on model similarity.

[0010] In one optional implementation, based on the historical deviation data of the priority scheduling pump stations, it is determined whether the pending scheduling pump stations need to participate in the scheduling, including: For each historical date within a historical time period, retrieve the historical scheduling instructions for that date; The deviation is calculated based on the target heating flow rate in the historical dispatch instructions and the actual heating flow rate of the priority dispatch pump station under the historical dispatch instructions. When the deviation exceeds the preset deviation threshold, the historical scheduling instruction will be identified as the response deviation instruction. If all historical dates within the historical time period are response deviation instructions, it is determined that the pending scheduling pump station needs to participate in the scheduling. If any historical date within the historical time period is not a response deviation instruction, it is determined that the pending scheduling pump station does not need to participate in the scheduling.

[0011] This invention identifies whether there is a persistent lack of regulation capacity by obtaining the deviation between the actual heating flow and the target heating flow of the priority scheduling pump station in the historical scheduling. This allows for the determination of whether the pending scheduling pump station needs to participate in the scheduling, so that the pending scheduling pump station is only activated when the priority scheduling pump station is insufficient. At the same time, it provides the scheduling trigger conditions for the pending scheduling pump station, which helps to effectively alleviate the data sparsity problem caused by long-term idleness of some models while ensuring heating stability, thereby improving the identification reliability of the fault diagnosis model.

[0012] In one optional implementation, when a pending scheduling pump station needs to participate in scheduling, the scheduling classification of the pending scheduling pump station is determined, including: Determine whether the current scheduling instruction is within the validity period of the previous scheduling instruction; While the update period is in effect, the scheduling classification updated by the previous scheduling instruction is maintained. When the update validity period is not in effect, the scheduling classification of the undetermined scheduling pump station is determined based on the similarity between the undetermined scheduling pump station and the priority scheduling pump station.

[0013] This invention determines whether the current scheduling instruction is within the validity period of the previous scheduling instruction. Within this validity period, the existing scheduling classification is maintained, avoiding frequent policy changes and wasted computational resources caused by reclassifying the instruction for each scheduling instruction. Outside the validity period, the classification is redefined based on the model similarity between the pending scheduling pump stations and the priority scheduling pump stations, providing a basis for subsequent differentiated scheduling based on classification.

[0014] In one optional implementation, when the pump station is not within the update validity period, the scheduling classification of the unscheduled pump station is determined based on the similarity between the unscheduled pump station and the priority scheduling pump station, including: When not within the validity period of the update, for each pending scheduling pump station, determine the different types of water pumps between the pending scheduling pump station and the priority scheduling pump station, and determine the number of the same type of water pumps between the different types of water pumps of the pending scheduling pump station and the different types of water pumps of each second pump station. The second pump station is other pending scheduling pump stations besides the pending scheduling pump station. Calculate the percentage of different types of pumps in the undetermined pumping station among all the pumps in the undetermined pumping station; When the proportion of the number of stations exceeds the first preset threshold, the scheduling classification of the undetermined scheduling pump stations will be determined as the target scheduling pump stations. When the proportion of the number is less than the second preset threshold, the scheduling classification of the undetermined scheduling pump station is determined as a scheduling deviation pump station, and the first preset threshold is greater than the second preset threshold. When the number proportion is not less than the second preset threshold and not greater than the first preset threshold, and the number of all pumps of the same model corresponding to the undetermined scheduling pump station is greater than the preset number threshold, the scheduling category of the undetermined scheduling pump station is determined as the target scheduling pump station. When the proportion of the number of pumps is not less than the second preset threshold and not greater than the first preset threshold, and the number of any pumps of the same model corresponding to the undetermined scheduling pump station is not greater than the preset number threshold, the scheduling classification of the undetermined scheduling pump station is determined as a scheduling deviation pump station.

[0015] This invention calculates the proportion of different pump models between undetermined and priority scheduling pump stations and their distribution breadth among other undetermined scheduling pump stations. It identifies pump stations with scarce data as target scheduling pump stations to prioritize the accumulation of operational data, and identifies pump stations with sufficient data as scheduling deviation pump stations to avoid redundant scheduling. This provides more comprehensive operational data for the fault diagnosis model and improves its identification reliability.

[0016] In one optional implementation, based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations, a scheduling scheme for the current scheduling instruction is determined and scheduling is performed, including: Calculate the flow difference between the target heating flow rate of the current dispatch command and the actual heating flow rate of the priority dispatch pump station; When there is a target scheduling pump station and the actual heating flow of the target scheduling pump station meets the flow difference, the scheduling priority scheduling pump station and the target scheduling pump station are used as scheduling schemes and scheduling is carried out. When there is no target scheduling pump station or the actual heating flow of the target scheduling pump station does not meet the flow difference, the scheduling scheme is based on the pump station with the largest number of scheduling priority scheduling stations, the total number of scheduling of all heat pump stations is the smallest, and the actual heating flow of the heat pump stations participating in the scheduling meets the target heating flow of the current scheduling instruction.

[0017] This invention calculates the flow gap of priority scheduling pump stations and prioritizes the activation of target scheduling pump stations for scheduling, thus ensuring current heating demand while accumulating operational data for data-scarce pump stations. When target pump stations are unavailable, heating is met based on the principle of maximizing the deployment of priority pump stations and minimizing the overall number of pump stations, thereby achieving an effective balance between heating security, data accumulation, and operational economy.

[0018] In one alternative implementation, updating the scheduling classification of the undetermined pumping stations includes: When a pumping station with a scheduling deviation meets the preset update conditions, the scheduling classification of all pending scheduling pumping stations will be adjusted to the target scheduling pumping station within the update validity period.

[0019] This invention adjusts the scheduling classification of all pending scheduling pump stations to the target scheduling pump station within the update validity period when the scheduling deviation pump station meets the preset update conditions, enabling the scheduling to be adaptively adjusted and providing a guarantee for solving the data sparsity problem caused by long-term idleness of some models.

[0020] In an optional implementation, in response to the current scheduling instruction, after determining whether a pending scheduling pump station needs to participate in the scheduling based on the historical deviation of the priority scheduling pump station, the method further includes: When a pending scheduling pump station is not required to participate in scheduling, the scheduling priority is given to scheduling the pump station to complete the scheduling of the current scheduling instruction.

[0021] This invention maintains low energy consumption and low complexity in system operation by having only the priority scheduling pump station independently complete the current scheduling command when the pending scheduling pump station does not need to participate in the scheduling.

[0022] In a second aspect, the present invention provides a dispatching device for thermal pumping stations in long-distance pipeline networks, the device comprising: The first determining module is used to determine the priority scheduling pump station and the undetermined scheduling pump station based on the similarity of water pumps among thermal pump stations in the long-distance pipeline network. The judgment module is used to respond to the current scheduling instruction and, based on the historical deviation of the priority scheduling pump stations, determine whether the pending scheduling pump stations need to participate in the scheduling. The second determining module is used to determine the scheduling category of the undetermined scheduling pump station when the undetermined scheduling pump station needs to participate in the scheduling. The scheduling category is used to indicate the scheduling priority of the undetermined scheduling pump station. The first scheduling module is used to determine the scheduling scheme of the current scheduling instruction and perform scheduling based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations; The update module is used to update the scheduling classification of pump stations awaiting scheduling.

[0023] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the above-described method for scheduling thermal pumping stations in long-distance pipeline networks, or any of its corresponding embodiments.

[0024] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for scheduling thermal pumping stations for long-distance pipeline networks as described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0025] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a thermal pumping station scheduling method for long-distance pipeline networks according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a thermal pumping station dispatching device for long-distance pipeline networks according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0029] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0030] According to an embodiment of the present invention, a method for scheduling thermal pumping stations in long-distance pipeline networks is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This embodiment provides a method for scheduling thermal pumping stations in long-distance pipeline networks. Figure 1 This is a flowchart of a thermal pumping station scheduling method for long-distance pipeline networks according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Based on the similarity of water pumps among the thermal pumping stations in the long-distance pipeline network, determine the priority scheduling pumping stations and the pending scheduling pumping stations.

[0032] Specifically, long-distance pipelines have multiple thermal pumping stations along their routes, each consisting of multiple pumps used to power the delivery of the heating medium. The pump models used in different thermal pumping stations may vary, and when different models experience the same type of fault, their fault characteristic signals often differ significantly. Traditional methods ignore these differences, scheduling only based on flow rate or temperature matching as a single objective. This leads to sparse data for some models due to a lack of long-term operational opportunities, resulting in insufficient reliability of fault diagnosis models in identifying them.

[0033] To this end, embodiments of the present invention analyze the similarity of pump models among various thermal pumping stations, identify priority scheduling pumping stations as the main adjustment targets from all thermal pumping stations, and regard the remaining thermal pumping stations as pending scheduling pumping stations. This allows for the priority scheduling of representative pumping stations, on the one hand prioritizing the accumulation of operational data of representative models in the system, and on the other hand, by controlling the participation mode of pending scheduling pumping stations, it is possible to guide models with scarce data to participate in operation while ensuring heating supply. This promotes the balanced accumulation of operational data of different pump models, thereby improving the reliability of the fault diagnosis model in identifying each pump model.

[0034] Step S102: In response to the current scheduling instruction, based on the historical deviation of the priority scheduling pump stations, determine whether the pending scheduling pump stations need to participate in the scheduling.

[0035] Specifically, upon receiving the current dispatch instruction, the priority dispatch pump station, as the primary dispatch target, responds first. Based on its deviation in the historical dispatch process, it is determined whether the pending dispatch pump station needs to participate in this dispatch. In this way, while ensuring heating demand, the model with scarce data is guided to participate in operation, avoiding the inadequacy of the fault diagnosis model's identification due to long-term idleness.

[0036] Step S103: When a pending scheduling pump station needs to participate in scheduling, determine the scheduling category of the pending scheduling pump station. The scheduling category is used to indicate the scheduling priority of the pending scheduling pump station.

[0037] Specifically, if pending scheduling pump stations are required to assist in scheduling, each pending scheduling pump station needs to be classified to clarify its priority in subsequent scheduling. This will enable subsequent scheduling to take into account both the current scheduling's heating needs and the data accumulation needs of each type of water pump, thereby providing support for improving the identification reliability of the fault diagnosis model.

[0038] Step S104: Based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations, determine the scheduling scheme of the current scheduling instruction and carry out the scheduling.

[0039] Specifically, based on the scheduling classification of the undetermined pump stations and in conjunction with the priority scheduling pump stations, the scheduling scheme for the current scheduling instruction is determined, and scarce models are guided to participate in the scheduling in a targeted manner. This enables the rational scheduling of various types of water pumps while meeting the heating demand of the current scheduling instruction, ensuring heating stability and accumulating diverse operational data for the fault diagnosis model.

[0040] Step S105: Update the scheduling classification of the undetermined pump stations.

[0041] Specifically, after completing the current dispatching instruction, the dispatching classification of the pending dispatching pump stations is updated to ensure that there are sufficient regulation resources under different operating conditions, thereby ensuring that the fault diagnosis model can continuously obtain the operating data of various pumps, and at the same time ensuring the long-term stable operation of the heating system.

[0042] This invention identifies priority and pending-scheduling pump stations based on pump similarity among heating pump stations. On one hand, it prioritizes the accumulation of operational data for representative pump models within the system. On the other hand, by controlling the participation of pending-scheduling pump stations, it guides data-scarce models to participate in operation while ensuring heating supply. Based on this, the historical deviation data of priority pump stations determines whether pending-scheduling pump stations need to participate in scheduling. If they are required, they are categorized to clarify their priority in subsequent scheduling. Based on the scheduling categories and priority pump stations, a scheduling scheme is determined that both ensures current heating demand and accumulates fault characteristic data for scarce models. Finally, the scheduling categories are dynamically updated based on the scheduling situation, allowing the scheduling scheme to adaptively adjust to the actual state. Through model similarity-driven differentiated scheduling, different pump models are provided with operational opportunities to accumulate fault characteristic data, thereby effectively improving the reliability of the fault diagnosis model in identifying various pump models and achieving a coordinated unity between the safe and stable operation of the heating system and the continuous improvement of fault diagnosis capabilities.

[0043] This embodiment provides a method for scheduling thermal pumping stations in long-distance pipeline networks, which specifically includes the following steps: Step S201: Based on the similarity of water pumps among the thermal pumping stations in the long-distance pipeline network, determine the priority scheduling pumping stations and the undetermined scheduling pumping stations.

[0044] Specifically, step S201 includes: Step S2011: For each thermal pumping station in the long-distance pipeline network, determine the same type of water pump between the thermal pumping station and each first pumping station, where the first pumping station is any other thermal pumping station besides the thermal pumping station.

[0045] Specifically, for each thermal pumping station in the long-distance pipeline network, all other thermal pumping stations are designated as first pumping stations, and the pumps of the same model between each thermal pumping station and each first pumping station are determined sequentially. For example, if the pump model of thermal pumping station i is [A,B,C,D], and the pump model of first pumping station j is [A,B,D,E], then the pumps of the same model between thermal pumping station i and first pumping station j are [A,B,D].

[0046] Step S2012: Calculate the proportion of the same model of water pumps between the thermal pump station and the first pump station in the total number of water pumps in the first pump station, and use it as the similarity coefficient between the thermal pump station and the first pump station.

[0047] Specifically, the similarity coefficient between the two heating pump stations is calculated by dividing the number of pumps of the same model between the heating pump station and the first pump station by the total number of pumps in the first pump station. This ratio measures the degree of similarity between the two heating pump stations in terms of pump models. For example, if the number of pumps of the same model between heating pump station i and the first pump station j is [A,B,D], and the number of pumps of the same model in the first pump station j is [A,B,D,E], then the similarity coefficient between heating pump station i and the first pump station j is 3 / 4 = 0.75.

[0048] Step S2013: Calculate the average similarity coefficient between the thermal pumping station and all first pumping stations.

[0049] Specifically, the similarity coefficient between the heat pump station and each first pump station can be calculated through the above steps. The average value of these similarity coefficients is calculated to measure the overall similarity level between the heat pump station and all other heat pump stations in the long-distance pipeline network. The higher the value, the more representative the pump model composition of the heat pump station is in the pipeline network.

[0050] Step S2014: Heat pump stations with an average value greater than the preset similarity coefficient threshold are identified as priority scheduling pump stations, and other heat pump stations other than priority scheduling pump stations are identified as pending scheduling pump stations.

[0051] Specifically, thermal pump stations with an average value greater than a preset similarity coefficient threshold (e.g., 0.3) are designated as priority scheduling pump stations and will serve as the primary adjustment targets for subsequent scheduling. There can be one or more of these priority scheduling pump stations. The remaining thermal pump stations are designated as pending scheduling pump stations. Priority scheduling pump stations are highly representative of the pipeline network due to their pump model composition. Using them as the main force in daily scheduling allows for the priority accumulation of operational data for representative models in the system. Furthermore, designating pending scheduling pump stations provides a basis for subsequent differentiated scheduling based on model similarity.

[0052] Step S202: In response to the current scheduling instruction, based on the historical deviation of the priority scheduling pump stations, determine whether the pending scheduling pump stations need to participate in the scheduling.

[0053] Specifically, step S202 includes: Step S2021: For each historical date within the historical time period, obtain the historical scheduling instructions for that historical date.

[0054] Specifically, a historical time period is set, and within this time period, each day corresponds to a historical scheduling instruction. The historical scheduling instructions for each day are obtained one by one.

[0055] Step S2022: Calculate the deviation based on the target heating flow rate in the historical dispatch instructions and the actual heating flow rate of the priority dispatch pump station under the historical dispatch instructions.

[0056] Specifically, each dispatch instruction includes the target heating flow required for dispatch. For each historical dispatch instruction, since there may be multiple priority dispatch pump stations, it is necessary to calculate the sum of the actual heating flows of all priority dispatch pump stations under the historical dispatch instruction. The absolute value of the difference between the target heating flow in the historical dispatch instruction and the sum of the values ​​of the priority dispatch pump stations is calculated. Then, the ratio of this absolute value of the difference to the target heating flow in the historical dispatch instruction is calculated as the deviation. This deviation quantifies the degree of deviation between the actual output of the priority dispatch pump stations and the dispatch demand in historical dispatch; a larger value indicates a more severe deviation between the actual heating capacity of the priority dispatch pump stations and the dispatch demand.

[0057] Step S2023: When the deviation is greater than the preset deviation threshold, the historical scheduling instruction is determined as the response deviation instruction.

[0058] Specifically, if the deviation is greater than a preset deviation threshold (e.g., 0.5), the historical dispatch instruction is determined as a response deviation instruction, indicating that there is an unacceptable deviation between the actual output heating flow of the priority dispatch pump station under the historical dispatch instruction and the dispatch demand.

[0059] Step S2024: When all historical dates within the historical time period are response deviation instructions, it is determined that the pending scheduling pump station needs to participate in the scheduling.

[0060] Specifically, if all historical dispatch instructions for each day within a historical time period are marked as response deviation instructions, it indicates that the priority dispatch pump station failed to meet the heating flow demand in all historical dispatches within that time period. Therefore, it is determined that the priority dispatch pump station's adjustment capacity is insufficient when operating alone, and a pending dispatch pump station needs to be introduced for joint dispatch to compensate for the heating flow gap of the priority dispatch pump station and ensure the stable operation of the heating system. Simultaneously, from the perspective of flow matching, this allows other pump stations to gain operating opportunities, thereby alleviating the data sparsity problem caused by long-term inactivity, accumulating operational data for this type of scarce pump station for the fault diagnosis model, and improving the model's reliability in identifying it.

[0061] Step S2025: If any historical date within the historical time period is not a response deviation instruction, it is determined that the pending scheduling pump station does not need to participate in the scheduling.

[0062] Specifically, if any historical dispatch instruction on any day within the historical time period is not marked as a response deviation instruction, it means that the priority dispatch pump station can at least meet the heating demand for some days within that historical time period. Therefore, it is determined that the priority dispatch pump station still has a certain adjustment margin, and it is not necessary to introduce the pending dispatch pump station to participate in the joint dispatch for the time being. The subsequent dispatch can be completed by the priority dispatch pump station alone.

[0063] Step S203: When the pending scheduling pump station does not need to participate in the scheduling, the scheduling priority scheduling pump station completes the scheduling of the current scheduling instruction.

[0064] Specifically, when the judgment result of step S202 is that there is no need to introduce the pending scheduling pump station to participate in this scheduling, only the priority scheduling pump station is scheduled to respond to the current scheduling command and complete the output task of the heating flow. This can maintain the low energy consumption and low complexity of the system operation while meeting the current heating demand.

[0065] Step S204: When a pending scheduling pump station needs to participate in scheduling, determine the scheduling category of the pending scheduling pump station. The scheduling category is used to indicate the scheduling priority of the pending scheduling pump station.

[0066] Specifically, step S204 includes: Step S2041: Determine whether the current scheduling instruction is within the update validity period of the previous scheduling instruction.

[0067] Specifically, when a pending scheduling pump station needs to participate in scheduling, the system determines whether to update the scheduling classification. After each scheduling operation, the system updates the scheduling classification based on the classification of pending scheduling pump stations in this scheduling operation and sets an update validity period for the updated scheduling classification, such as 2 days. When a new scheduling instruction arrives, the system first checks whether the current time is within the update validity period set by the previous scheduling instruction to determine whether the scheduling classification needs to be redefined.

[0068] Step S2042: While the update validity period is in effect, maintain the scheduling classification updated by the previous scheduling instruction.

[0069] Specifically, if the time corresponding to the current scheduling instruction is within the update validity period set by the previous scheduling instruction, there is no need to redetermine the scheduling classification. The scheduling classification updated by the previous scheduling instruction can be maintained directly, reducing unnecessary duplicate calculations and providing continuous and stable operating opportunities for each type of water pump. This effectively ensures that the fault diagnosis model continuously accumulates complete operating data on each type of water pump, which helps to improve its reliability in identifying scarce models.

[0070] Step S2043: When the update validity period is not in effect, determine the scheduling classification of the unscheduled pump station based on the similarity between the unscheduled pump station and the priority scheduling pump station.

[0071] In some optional implementations, step S2043 above includes: Step a1: When not within the update validity period, for each pending scheduling pump station, determine the different types of water pumps between the pending scheduling pump station and the priority scheduling pump station, and determine the number of the same type of water pumps between the different types of water pumps of the pending scheduling pump station and the different types of water pumps of each second pump station. The second pump station is other pending scheduling pump stations besides the pending scheduling pump station.

[0072] Specifically, if the time corresponding to the current dispatch instruction is not within the update validity period set by the previous dispatch instruction, the dispatch classification of the pending dispatch pump station is determined through steps a1-a6. First, since there may be multiple priority dispatch pump stations, the union of the pump models of all priority dispatch pump stations is determined. Using the pump models of the pending dispatch pump station as the benchmark, pump models that do not appear in the union are selected as different pump models. Other pending dispatch pump stations are designated as second pump stations. The different pump models of the pending dispatch pump station are compared with the different pump models of each second pump station, and the number of pumps of the same model between the two is counted.

[0073] For example, if the union of pump models of the priority scheduling pump station is [A,C,D,F], the pump models of the undetermined scheduling pump station j are [A,B,D,E,J], and the pump models of the undetermined scheduling pump station z are [B,C,D,E], then the different pump models between the priority scheduling pump station and the undetermined scheduling pump station j are [B,E,J], and the different pump models between the priority scheduling pump station and the undetermined scheduling pump station z are [B,E]. When determining the scheduling category of the undetermined scheduling pump station j, the undetermined scheduling pump station z is the second pump station, and the number of pumps of the same model between the different pump models of the two pump stations is [B,E], which is 2.

[0074] Step a2: Calculate the percentage of different types of pumps in the undetermined pumping station among all the pumps in the undetermined pumping station.

[0075] Specifically, the ratio of the number of different pump models between the pending scheduling pump station and the priority scheduling pump station to the total number of pumps in the pending scheduling pump station is used as the quantity proportion. This ratio measures the degree of difference between the pending scheduling pump station and the priority scheduling pump station in terms of pump model composition. The larger the value, the greater the difference and the more significant the data scarcity. For example, if the union of pump models of the priority scheduling pump station is [A,C,D,F], and the pump models of the pending scheduling pump station j are [A,B,D,E,J], and the different pump models between the priority scheduling pump station and the pending scheduling pump station j are [B,E,J], then the quantity proportion = 3 / 5 = 0.6.

[0076] Step a3: When the proportion of the number of stations exceeds the first preset threshold, the scheduling category of the undetermined scheduling pump station is determined as the target scheduling pump station.

[0077] Specifically, when the proportion of such pumps exceeds a first preset threshold (e.g., 0.8), it indicates that the vast majority of pump models in the pending scheduling pump station are not found in the priority scheduling pump stations, and there are significant differences in equipment composition between the two. The operational data of this pending scheduling pump station is highly scarce and valuable for the fault diagnosis model. Therefore, the scheduling classification of this pending scheduling pump station is determined as the target scheduling pump station, making it a priority auxiliary station in subsequent scheduling. This allows for the accumulation of operational data for this scarce model while ensuring heating demand, thereby improving the reliability of the fault diagnosis model in identifying its fault characteristics.

[0078] Step a4: When the proportion of the number of stations is less than the second preset threshold, the scheduling classification of the undetermined scheduling pump stations is determined as scheduling deviation pump stations, and the first preset threshold is greater than the second preset threshold.

[0079] Specifically, when the proportion of pumps in the pending scheduling pump station is less than the second preset threshold (e.g., 0.3), it indicates that the vast majority of pump models in the pending scheduling pump station have already appeared in the priority scheduling pump station, and the two are highly similar in equipment composition. The operating data of the pending scheduling pump station is already sufficient for the fault diagnosis model. Therefore, the scheduling classification of the pending scheduling pump station is determined as a scheduling deviation pump station, so that it is avoided from being called in regular scheduling as much as possible.

[0080] Step a5: When the number proportion is not less than the second preset threshold and not greater than the first preset threshold, and the number of all pumps of the same model corresponding to the pending scheduling pump station is greater than the preset number threshold, the scheduling classification of the pending scheduling pump station is determined as the target scheduling pump station.

[0081] Specifically, if the number of pumps in the pending scheduling station is not less than the second preset threshold and not greater than the first preset threshold, it indicates that the degree of difference between the pending scheduling pump station and the priority scheduling pump station is at a moderate level, and its data value cannot be directly determined based solely on the number percentage. Furthermore, if the number of pumps of the same model between the pending scheduling pump station and all second-level pump stations is greater than a preset number threshold (e.g., 2), it indicates that the different models of the pending scheduling pump station are widely present in the long-distance pipeline network and have high representativeness. Its operational data can provide a reference for multiple pump stations and has high collection value. Therefore, the scheduling classification of the pending scheduling pump station is determined as the target scheduling pump station, allowing it to obtain operational opportunities in subsequent scheduling to accumulate effective fault characteristic data, thereby improving the identification reliability of the fault diagnosis model.

[0082] Step a6: When the number proportion is not less than the second preset threshold and not greater than the first preset threshold, and the number of any pump of the same model corresponding to the pending scheduling pump station is not greater than the preset number threshold, the scheduling classification of the pending scheduling pump station is determined as a scheduling deviation pump station.

[0083] Specifically, when the proportion of pumps in a pumping station is between the second and first preset thresholds, and the number of pumps of the same model between the station to be scheduled and any second pumping station is not greater than a preset threshold, it indicates that at least one pump of a different model is rarely distributed in the long-distance pipeline network and is not representative. Its operational data is difficult to generalize to multiple pumping stations, resulting in limited data accumulation coverage. Therefore, the scheduling classification of this station to be scheduled is determined as a scheduling deviation station, minimizing its use in regular scheduling. Operational opportunities are prioritized for pumping stations with a wider distribution of different models in the system, stronger representativeness, and higher data collection value, thereby optimizing the overall data accumulation efficiency of each pump model.

[0084] Step S205: Based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations, determine the scheduling scheme of the current scheduling instruction and carry out the scheduling.

[0085] Specifically, step S205 includes: Step S2051: Calculate the flow difference between the target heating flow rate of the current dispatch instruction and the actual heating flow rate of the priority dispatch pump station.

[0086] Specifically, upon receiving the current dispatch instruction, the system obtains the target heating flow rate required to be achieved, and simultaneously obtains the sum of the actual heating flow rates of all priority dispatch pump stations. The difference between the two is calculated as the flow rate difference, which can quantify the heating capacity gap of priority dispatch pump stations under the current dispatch instruction. This serves as the basis for determining whether and how much auxiliary dispatch resources are needed to fill the gap.

[0087] Step S2052: When there is a target scheduling pump station and the actual heating flow of the target scheduling pump station meets the flow difference, the priority scheduling pump station and the target scheduling pump station are used as scheduling schemes and scheduling is carried out.

[0088] Specifically, after determining the flow difference, the system checks whether there are any pending scheduling pump stations already classified as target scheduling pump stations, and determines whether the actual heating flow of these pump stations, individually or in combination, can compensate for the flow difference. If a target scheduling pump station exists and has the ability to compensate for the flow difference, the priority scheduling pump station and the target scheduling pump station are both included in the current scheduling plan and executed according to the plan. This approach not only compensates for the heating flow gap when the priority scheduling pump station operates alone, ensuring that the heating demand of the current scheduling command is met, but also provides the target scheduling pump station with operating opportunities, allowing it to accumulate operating data under actual conditions. This alleviates the data sparsity problem caused by long-term idleness and improves the reliability of the fault diagnosis model in identifying this type of pump station.

[0089] Step S2053: When there is no target scheduling pump station or the actual heating flow of the target scheduling pump station does not meet the flow difference, the scheduling scheme is to select the pump station with the largest number of scheduling priority scheduling stations, the total number of scheduling of all heat pump stations with the smallest number of scheduling, and the actual heating flow of the heat pump stations participating in the scheduling meets the target heating flow of the current scheduling instruction, and then the scheduling is carried out.

[0090] Specifically, when there is no target dispatching pump station, or when the actual heating flow of a target dispatching pump station is insufficient to compensate for the flow difference of the priority dispatching pump station, the heating demand cannot be met by activating the priority dispatching pump station and the target dispatching pump station. In this case, the dispatching deviation pump station can be included in the dispatching candidate range, and the constraint target of the dispatching scheme is determined by the maximum number of priority dispatching pump stations, the minimum number of dispatching all heat pump stations, and the actual heating flow of the heat pump stations participating in the dispatching meeting the target heating flow of the current dispatching instruction. The final dispatching scheme is then determined and executed.

[0091] Step S206: Update the scheduling classification of the undetermined pump stations.

[0092] Specifically, step S206 includes: Step S2061: When the scheduling deviation pump station meets the preset update conditions, adjust the scheduling classification of all pending scheduling pump stations to the target scheduling pump station within the update validity period.

[0093] Specifically, the preset update conditions include the following four situations: (1) The proportion of all scheduled deviation pump stations in all thermal pump stations is greater than the first preset proportion threshold (e.g., 0.5); (2) The proportion calculated in (1) is less than the second preset proportion threshold (0.1) and there are a preset number of scheduled deviation pump stations that have not participated in scheduling within the most recent preset time period, indicating that although the number of scheduled deviation pump stations is small, there is a certain backlog, which needs to be dealt with in time to avoid data gaps caused by long-term idleness; (3) The average proportion of all scheduled deviation pump stations calculated in step a2 is greater than the first preset proportion threshold; (4) The number of rare model pump stations is greater than the preset pump station number threshold (e.g., 2). Rare model pump stations refer to scheduled deviation pump stations where at least one pump model has not appeared in all priority scheduling pump stations and all target scheduling pump stations, indicating that there are pump stations with extremely special equipment composition, and conventional scheduling strategies are difficult to effectively cover the operation needs of such pump stations.

[0094] The four scenarios are evaluated sequentially. When a pumping station with a scheduling deviation meets a certain condition, within the update validity period (e.g., the next two days), the scheduling classification of all pending scheduling pumping stations is adjusted to target scheduling pumping stations. This means all thermal pumping stations are included in the scheduling scope, achieving overall scheduling. Within the update validity period, if a new scheduling instruction is received, all thermal pumping stations participate in the scheduling as scheduling objects. After each scheduling, the system is re-evaluated to see if the preset update conditions are met, thus forming a dynamic closed loop for the scheduling strategy.

[0095] If none of the above conditions are met, the scheduling classification will not be updated. When a new scheduling instruction is received, the process will return to step S202 for execution.

[0096] This invention identifies priority and pending-scheduling pump stations based on pump similarity among heating pump stations. On one hand, it prioritizes the accumulation of operational data for representative pump models within the system. On the other hand, by controlling the participation of pending-scheduling pump stations, it guides data-scarce models to participate in operation while ensuring heating supply. Based on this, the historical deviation data of priority pump stations determines whether pending-scheduling pump stations need to participate in scheduling. If they are required, they are categorized to clarify their priority in subsequent scheduling. Based on the scheduling categories and priority pump stations, a scheduling scheme is determined that both ensures current heating demand and accumulates fault characteristic data for scarce models. Finally, the scheduling categories are dynamically updated based on the scheduling situation, allowing the scheduling scheme to adaptively adjust to the actual state. Through model similarity-driven differentiated scheduling, different pump models are provided with operational opportunities to accumulate fault characteristic data, thereby effectively improving the reliability of the fault diagnosis model in identifying various pump models and achieving a coordinated unity between the safe and stable operation of the heating system and the continuous improvement of fault diagnosis capabilities.

[0097] This embodiment also provides a dispatching device for thermal pumping stations in long-distance pipeline networks. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0098] This embodiment provides a dispatching device for thermal pumping stations in long-distance pipeline networks, such as... Figure 2 As shown, it includes: The first determining module 201 is used to determine the priority scheduling pump station and the undetermined scheduling pump station based on the similarity of water pumps between thermal pump stations in the long-distance pipeline network.

[0099] The judgment module 202 is used to respond to the current scheduling instruction and determine whether the pending scheduling pump station needs to participate in the scheduling based on the historical deviation of the priority scheduling pump station.

[0100] The second determining module 203 is used to determine the scheduling category of the undetermined scheduling pump station when the undetermined scheduling pump station needs to participate in the scheduling. The scheduling category is used to indicate the scheduling priority of the undetermined scheduling pump station.

[0101] The first scheduling module 204 is used to determine the scheduling scheme of the current scheduling instruction and perform scheduling based on the scheduling classification of priority scheduling pump stations and pending scheduling pump stations.

[0102] Update module 205 is used to update the scheduling classification of unscheduled pump stations.

[0103] In some alternative implementations, the first determining module 201 includes: The first determining unit is used to determine, for each thermal pumping station in the long-distance pipeline network, the same type of water pump between the thermal pumping station and each first pumping station, wherein the first pumping station is any other thermal pumping station besides the thermal pumping station.

[0104] The first calculation unit is used to calculate the proportion of the same type of water pumps between the thermal pump station and the first pump station in the total number of water pumps in the first pump station, which is used as the similarity coefficient between the thermal pump station and the first pump station.

[0105] The second calculation unit is used to calculate the average similarity coefficient between the heat pump station and all the first pump stations.

[0106] The second determining unit is used to determine the heat pump stations whose average value is greater than the preset similarity coefficient threshold as priority scheduling pump stations, and to designate other heat pump stations other than priority scheduling pump stations as pending scheduling pump stations.

[0107] In some optional implementations, the determination module 202 includes: The acquisition unit is used to acquire historical scheduling instructions for each historical date within a historical time period.

[0108] The third calculation unit is used to calculate the deviation based on the target heating flow rate in the historical dispatch instructions and the actual heating flow rate of the priority dispatch pump station under the historical dispatch instructions.

[0109] The third determining unit is used to determine the historical scheduling instruction as the response deviation instruction when the deviation is greater than the preset deviation threshold.

[0110] The fourth determining unit is used to determine which pending scheduling pump stations need to participate in scheduling when all historical dates within the historical time period are response deviation instructions.

[0111] The fifth determining unit is used to determine that, if any historical date within the historical time period is not a response deviation instruction, the pending scheduling pump station does not need to participate in the scheduling.

[0112] In some alternative implementations, the second determining module 203 includes: The judgment unit is used to determine whether the current scheduling instruction is within the update validity period of the previous scheduling instruction.

[0113] The maintenance unit is used to maintain the scheduling classification updated by the previous scheduling instruction when the update validity period is in effect.

[0114] The sixth determining unit is used to determine the scheduling classification of a pending scheduling pump station based on the similarity between the pending scheduling pump station and the priority scheduling pump station when it is not within the update validity period.

[0115] In some alternative implementations, the sixth determining unit includes: The first determining subunit is used, when not in the update validity period, for each pending scheduling pump station, to determine the different types of water pumps between the pending scheduling pump station and the priority scheduling pump station, and to determine the number of the same type of water pumps between the different types of water pumps of the pending scheduling pump station and the different types of water pumps of each second pump station, wherein the second pump station is other pending scheduling pump stations besides the pending scheduling pump station.

[0116] The calculation subunit is used to calculate the proportion of different types of water pumps in the undetermined scheduling pump station among all the water pumps in the undetermined scheduling pump station.

[0117] The second determining subunit is used to determine the scheduling classification of the undetermined scheduling pump station as the target scheduling pump station when the proportion of the number is greater than the first preset threshold.

[0118] The third determining subunit is used to determine the scheduling classification of the undetermined scheduling pump station as a scheduling deviation pump station when the proportion of the number is less than the second preset threshold, and the first preset threshold is greater than the second preset threshold.

[0119] The fourth determining subunit is used to determine the scheduling category of the undetermined scheduling pump station as the target scheduling pump station when the quantity ratio is not less than the second preset threshold and not greater than the first preset threshold, and the quantity of all the same type of water pumps corresponding to the undetermined scheduling pump station is greater than the preset quantity threshold.

[0120] The fifth determining subunit is used to determine the scheduling category of the undetermined scheduling pump station as a scheduling deviation pump station when the quantity ratio is not less than the second preset threshold and not greater than the first preset threshold, and the quantity of any pump of the same model corresponding to the undetermined scheduling pump station is not greater than the preset quantity threshold.

[0121] In some alternative implementations, the first scheduling module 204 includes: The fourth calculation unit is used to calculate the flow difference between the target heating flow rate of the current dispatch instruction and the actual heating flow rate of the priority dispatch pump station.

[0122] The first scheduling unit is used to schedule the priority scheduling pump station and the target scheduling pump station as scheduling schemes and to schedule them when there is a target scheduling pump station and the actual heating flow of the target scheduling pump station meets the flow difference.

[0123] The second scheduling unit is used to schedule pumps when there is no target scheduling pump station or the actual heating flow of the target scheduling pump station does not meet the flow difference. The scheduling scheme is based on the pump station with the largest number of scheduling priority scheduling stations, the total number of scheduling of all heat pump stations is the smallest, and the actual heating flow of the heat pump stations participating in the scheduling meets the target heating flow of the current scheduling instruction.

[0124] In some alternative implementations, the update module 205 includes: The update unit is used to adjust the scheduling classification of all pending scheduling pump stations to the target scheduling pump station within the update validity period when the scheduling deviation pump station meets the preset update conditions.

[0125] In some alternative implementations, after the determination module 202, the device further includes: The second scheduling module is used to prioritize scheduling pump stations to complete the current scheduling instruction when the pending scheduling pump stations do not need to participate in the scheduling.

[0126] The thermal pump station scheduling device for long-distance pipelines provided in this embodiment of the invention can execute the thermal pump station scheduling method for long-distance pipelines provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0127] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0128] The following is a detailed reference. Figure 3 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0129] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0130] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a memory 308, or installed from a ROM 302. When the computer program is executed by the processor 301, it performs the functions defined in the method for scheduling thermal pumping stations for long-distance pipeline networks according to embodiments of the present invention.

[0131] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0132] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the thermal pump station scheduling method for long-distance pipeline networks shown in the above embodiments is implemented.

[0133] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for scheduling thermal pumping stations in long-distance pipeline networks, characterized in that, The method includes: Based on the similarity of water pumps among thermal pumping stations in long-distance pipelines, priority scheduling pumping stations and undetermined scheduling pumping stations are identified. In response to the current scheduling instruction, based on the historical deviation of the priority scheduling pump station, it is determined whether the pending scheduling pump station needs to participate in the scheduling. When the pending scheduling pump station needs to participate in scheduling, the scheduling classification of the pending scheduling pump station is determined, and the scheduling classification is used to indicate the scheduling priority of the pending scheduling pump station; Based on the scheduling classification of the priority scheduling pump stations and the undetermined scheduling pump stations, the scheduling scheme of the current scheduling instruction is determined and the scheduling is carried out. Update the scheduling classification of the undetermined pumping stations.

2. The method according to claim 1, characterized in that, Based on the similarity of water pumps among the thermal pumping stations in the long-distance pipeline network, the priority scheduling pumping stations and the pending scheduling pumping stations are determined, including: For each thermal pumping station in the long-distance pipeline network, determine the same type of water pump between the thermal pumping station and each first pumping station, where the first pumping station is any other thermal pumping station besides the thermal pumping station. The proportion of the same model of water pumps between the thermal pump station and the first pump station in the total number of water pumps in the first pump station is calculated as the similarity coefficient between the thermal pump station and the first pump station. Calculate the average of the similarity coefficients between the thermal pumping station and all the first pumping stations; Thermal pump stations with an average value greater than a preset similarity coefficient threshold are identified as priority scheduling pump stations, and other thermal pump stations besides the priority scheduling pump stations are identified as pending scheduling pump stations.

3. The method according to claim 1, characterized in that, The step of determining whether the pending pump station needs to participate in the scheduling based on the historical deviation data of the priority scheduling pump station includes: For each historical date within the historical time period, obtain the historical scheduling instructions for that historical date; The deviation is calculated based on the target heating flow rate in the historical dispatch instructions and the actual heating flow rate of the priority dispatch pump station under the historical dispatch instructions. When the deviation is greater than a preset deviation threshold, the historical scheduling instruction is determined as a response deviation instruction; If all historical dates within the historical time period are response deviation instructions, it is determined that the pending scheduling pump station needs to participate in the scheduling. If any historical date within the historical time period is not a response deviation instruction, it is determined that the pending scheduling pump station does not need to participate in the scheduling.

4. The method according to claim 1, characterized in that, When the undetermined scheduling pump station needs to participate in scheduling, determining the scheduling category of the undetermined scheduling pump station includes: Determine whether the current scheduling instruction is within the validity period of the previous scheduling instruction; While the update period is in effect, maintain the scheduling classification updated by the previous scheduling instruction. When the update validity period is not in effect, the scheduling classification of the undetermined scheduling pump station is determined based on the similarity between the undetermined scheduling pump station and the priority scheduling pump station.

5. The method according to claim 4, characterized in that, When the pumping station is not within the update validity period, the process of determining the scheduling classification of the unscheduled pumping station based on the similarity between the unscheduled pumping station and the priority scheduling pumping station includes: When not within the validity period of the update, for each pending scheduling pump station, the different types of water pumps between the pending scheduling pump station and the priority scheduling pump station are determined, and the number of the same type of water pumps between the different types of water pumps of the pending scheduling pump station and the different types of water pumps of each second pump station is determined, wherein the second pump station is other pending scheduling pump stations besides the pending scheduling pump station. Calculate the percentage of different types of water pumps in the undetermined pumping station among all the water pumps in the undetermined pumping station; When the proportion of the number of stations exceeds the first preset threshold, the scheduling classification of the undetermined scheduling pump stations is determined as the target scheduling pump stations. When the proportion of the number is less than the second preset threshold, the scheduling classification of the undetermined scheduling pump station is determined as a scheduling deviation pump station, and the first preset threshold is greater than the second preset threshold. When the number proportion is not less than the second preset threshold and not greater than the first preset threshold, and the number of all the same type of water pumps corresponding to the undetermined scheduling pump station is greater than the preset number threshold, the scheduling classification of the undetermined scheduling pump station is determined as the target scheduling pump station. When the proportion of the number of pumps is not less than the second preset threshold and not greater than the first preset threshold, and the number of any pumps of the same model corresponding to the undetermined scheduling pump station is not greater than the preset number threshold, the scheduling classification of the undetermined scheduling pump station is determined as a scheduling deviation pump station.

6. The method according to claim 5, characterized in that, The process of determining the scheduling scheme for the current scheduling instruction and performing scheduling based on the scheduling classification of the priority scheduling pump stations and the pending scheduling pump stations includes: Calculate the flow difference between the target heating flow rate of the current scheduling instruction and the actual heating flow rate of the priority scheduling pump station; When a target scheduling pump station exists and the actual heating flow of the target scheduling pump station meets the flow difference, the priority scheduling pump station and the target scheduling pump station will be scheduled as the scheduling scheme and the scheduling will be carried out. When there is no target scheduling pump station or the actual heating flow of the target scheduling pump station does not meet the flow difference, the scheduling scheme is based on the priority scheduling pump station with the largest number of scheduling, the total number of scheduling of all heat pump stations with the smallest number of scheduling, and the actual heating flow of the heat pump station participating in the scheduling meets the target heating flow of the current scheduling instruction.

7. The method according to claim 5, characterized in that, The updating of the scheduling classification of the undetermined pumping stations includes: When the scheduled deviation pump station meets the preset update conditions, the scheduling classification of all pending scheduling pump stations will be adjusted to the target scheduling pump station within the update validity period.

8. The method according to claim 1, characterized in that, In response to the current scheduling instruction, after determining whether the pending scheduling pump station needs to participate in the scheduling based on the historical deviation of the priority scheduling pump station, the method further includes: When the pending scheduling pump station does not need to participate in the scheduling, the priority scheduling pump station is scheduled to complete the scheduling of the current scheduling instruction.

9. A dispatching device for thermal pumping stations in long-distance pipeline networks, characterized in that, The device includes: The first determining module is used to determine the priority scheduling pump station and the undetermined scheduling pump station based on the similarity of water pumps among thermal pump stations in the long-distance pipeline network. The judgment module is used to respond to the current scheduling instruction and, based on the historical deviation of the priority scheduling pump station, determine whether the pending scheduling pump station needs to participate in the scheduling. The second determining module is used to determine the scheduling category of the undetermined scheduling pump station when the undetermined scheduling pump station needs to participate in the scheduling, and the scheduling category is used to represent the scheduling priority of the undetermined scheduling pump station. The first scheduling module is used to determine the scheduling scheme of the current scheduling instruction and perform scheduling based on the scheduling classification of the priority scheduling pump stations and the undetermined scheduling pump stations; The update module is used to update the scheduling classification of the undetermined scheduling pump stations.

10. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the thermal pumping station scheduling method for long-distance pipelines as described in any one of claims 1 to 8.

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