Operation and maintenance method of comprehensive energy equipment based on large model and related device

Abstract

The invention discloses an operation and maintenance method of integrated energy equipment based on a large model and a related device. The method comprises the following steps: firstly, determining a plurality of first to-do tasks of comprehensive energy equipment operation and maintenance work, and obtaining task scheduling parameters of each task, including task deadline, current time, predicted arrival time from a current position to a task destination calculated based on real-time road traffic conditions, and task emergency degree; and calculating the priority score of each task according to the task scheduling parameters by using a pre-trained priority scoring model. And then sorting the tasks according to the priority scores, and performing operation and maintenance planning based on a sorting result to formulate an operation and maintenance plan of a plurality of to-be-handled tasks, so as to perform operation and maintenance on a plurality of first to-be-handled tasks based on the operation and maintenance plan. The priority score is calculated by using data and a model, human intervention is eliminated, and fair distribution of tasks is ensured. The evaluation accuracy is improved by combining task scheduling and predicted arrival time, the road condition is reflected, delay is avoided, and the execution efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of integrated energy technology, and in particular to an operation and maintenance method and related devices for integrated energy equipment based on a large model. Background Art

[0002] An integrated energy system integrates multiple energy sources such as coal, oil, natural gas, electricity and thermal energy in a specific area through advanced physical information technology and innovative management models, aiming to achieve coordinated planning and optimized operation among heterogeneous energy subsystems. In an integrated energy system, the daily operation and maintenance work of energy service providers refers to various management and maintenance activities carried out to ensure the normal operation of energy facilities or equipment, such as equipment inspection, maintenance, inspection, fault handling, data monitoring, safety management and other tasks. Through daily maintenance and management of energy systems such as power supply, water supply and gas supply, it is possible to ensure the continuous and efficient operation of facilities, improve productivity and service quality, and reduce potential risks and costs.

[0003] At present, for the daily operation and maintenance work arrangements of energy service providers, relying mainly on experience-based human planning has some obvious disadvantages. First, this experience-based planning method is easily affected by subjective factors, such as personal preferences and emotions, resulting in uneven or unfair task distribution. In addition, planning based purely on experience is difficult to fully consider the priority and urgency of various tasks, which may cause important tasks to be ignored or improperly prioritized.

[0004] Secondly, the experience-based planning method lacks systematicity and scientificity, and cannot provide objective guidance and quantitative decision-making support. This planning method usually lacks effective data and analysis methods, making it difficult to evaluate and adjust the performance of task execution. The lack of a scientific task sorting and priority evaluation mechanism has resulted in irrational and inefficient task arrangements, affecting work efficiency and service quality.

[0005] In general, experience-based planning has many drawbacks in the daily operation and maintenance arrangements of energy service providers and cannot meet today's increasingly complex and diverse operation and maintenance needs. Summary of the invention

[0006] Based on the above problems, the present application provides an operation and maintenance method and related devices for integrated energy equipment based on a large model, which can improve the work efficiency and service level of task operation and maintenance planning.

[0007] The embodiments of the present application disclose the following technical solutions:

[0008] A large-scale model-based integrated energy equipment operation and maintenance method, the method comprising:

[0009] Determine multiple first to-do tasks of the integrated energy equipment operation and maintenance work, and obtain first task scheduling parameters of each first to-do task, wherein the first task scheduling parameters include task deadline, task current time, estimated arrival time from the current location to the task destination, and urgency of the first to-do task; the estimated arrival time is calculated based on real-time road traffic conditions;

[0010] For each of the first to-do tasks, a priority score of the first to-do task is calculated based on the first task scheduling parameters corresponding to the first to-do task using a pre-trained priority scoring model; the scoring label of the input data of the priority scoring model is calculated based on a large model;

[0011] Sorting the plurality of first to-do tasks based on the priority scores to obtain a task ranking;

[0012] Performing operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain operation and maintenance plans for the plurality of first to-be-done tasks;

[0013] The multiple first to-be-done tasks are operated and maintained based on the operation and maintenance plans of the multiple first to-be-done tasks.

[0014] In a possible implementation, performing operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain an operation and maintenance plan for the plurality of first to-be-done tasks includes:

[0015] Determine the start time of the operation and maintenance plan;

[0016] Setting the start time of the operation and maintenance plan to the planned start time of the first first to-be-done task in the task sequence;

[0017] In the operation and maintenance plan, the planned start time of the Nth first to-do task in the task sequence is set to the start time of the N-1th first to-do task in the task sequence plus the estimated completion time of the N-1th first to-do task, plus the inter-task movement time between the N-1th first to-do task and the Nth first to-do task; N is an integer greater than 1.

[0018] In a possible implementation, the method further includes:

[0019] Determine the completion time of the operation and maintenance plan;

[0020] If the planned start time of the Mth first to-do task in the task sorting has been set, but its planned start time is later than the completion time of the operation and maintenance plan, then the planned start time of the first to-do task and the planned start time of the subsequent to-do tasks of the first to-do task are both set to the completion time of the operation and maintenance plan; the subsequent to-do tasks include other to-do tasks that are arranged behind the first to-do task in the task sorting; M is an integer greater than 1.

[0021] In a possible implementation, the training process of the pre-trained priority scoring model includes:

[0022] Determine a plurality of second to-do tasks with scoring labels in the historical operation and maintenance work of the integrated energy equipment, and define a loss function; the scoring label is used to indicate the priority score of the second to-do task;

[0023] Obtaining the second task scheduling parameters of each second to-do task; the second task scheduling parameters include the time window of the second to-do task, the distance between the current location and the location of the second to-do task, and the urgency of the second to-do task; the time window of the second to-do task is the time difference between the time required to complete the second to-do task and the current time;

[0024] Inputting the second task scheduling parameters of the plurality of second to-do tasks and the plurality of second to-do tasks with scoring labels into a ranking learning model, and performing model training to obtain a primary scoring model;

[0025] The loss function is used to iteratively adjust the parameters of the primary scoring model to obtain the priority scoring model.

[0026] In a possible implementation, the method further includes:

[0027] If it is identified that one of the second to-do tasks is marked with an execution priority flag, determining the number of the execution priority flags;

[0028] Setting an increased score for the second to-do task based on the number of execution priority execution identifiers;

[0029] The scoring label of the second to-do task is adjusted based on the increased scoring.

[0030] In a possible implementation, the scoring label of the second to-do task is calculated by a large model;

[0031] Wherein, the large model is:

[0032]

[0033] Where S is the priority score, W t is the remaining time weight coefficient, T is the time window of the to-do task, a is the time change index, W d is the distance weight coefficient, D is the distance between the current location and the location of the to-do task, b is the distance change index, and W e is the urgency weight coefficient, E is the urgency of the task to be done, and c is the urgency change index; W t +W d +W e =1.

[0034] An operation and maintenance device for integrated energy equipment based on a large model, the device comprising:

[0035] A first task determination unit, used to determine a plurality of first to-do tasks for operation and maintenance of integrated energy equipment;

[0036] A first acquisition unit is used to acquire first task scheduling parameters of each first to-do task, wherein the first task scheduling parameters include task deadline, task current time, estimated arrival time from current location to task destination, and urgency of the first to-do task; the estimated arrival time is calculated based on real-time road traffic conditions;

[0037] a scoring calculation unit, configured to calculate, for each of the first to-do tasks, a priority score of the first to-do task based on the first task scheduling parameters corresponding to the first to-do task using a pre-trained priority scoring model; the scoring label of the input data of the priority scoring model is calculated based on a large model;

[0038] A task sorting unit, configured to sort the plurality of first to-do tasks based on the priority scores to obtain a task sorting;

[0039] An operation and maintenance planning unit, configured to perform operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting, and obtain operation and maintenance plans for the plurality of first to-be-done tasks;

[0040] An operation and maintenance unit is used to operate and maintain the multiple first to-be-done tasks based on the operation and maintenance plans of the multiple first to-be-done tasks.

[0041] In a possible implementation, the operation and maintenance planning unit specifically includes:

[0042] A start time determination unit, used to determine the start time of the operation and maintenance plan;

[0043] A first time setting unit, used to set the start time of the operation and maintenance plan to the planned start time of the first first to-be-done task in the task sequence;

[0044] The second time unit is used to set the planned start time of the Nth first to-do task in the task sequence in the operation and maintenance plan to the start time of the N-1th first to-do task in the task sequence plus the estimated completion time of the N-1th first to-do task, plus the inter-task movement time between the N-1th first to-do task and the Nth first to-do task; N is an integer greater than 1.

[0045] A large-model-based integrated energy equipment operation and maintenance method device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the large-model-based integrated energy equipment operation and maintenance method as described above is implemented.

[0046] A computer-readable storage medium stores instructions, which, when executed on a terminal device, enable the terminal device to execute the operation and maintenance method of integrated energy equipment based on a large model as described above.

[0047] Compared with the prior art, this application has the following beneficial effects:

[0048] The present application provides an operation and maintenance method of integrated energy equipment based on a large model and a related device. Specifically, when executing the operation and maintenance method of integrated energy equipment based on a large model provided in the embodiment of the present application, first, multiple first to-do tasks of the operation and maintenance work of the integrated energy equipment are determined, and the first task scheduling parameters of each first to-do task are obtained, which include the task deadline, the current time of the task, the estimated arrival time from the current location to the task destination, and the urgency of the first to-do task. Among them, the estimated arrival time is calculated based on the real-time road traffic conditions, which can accurately reflect the actual execution difficulty of each task. Next, for each first to-do task, the priority score is calculated according to the corresponding first task scheduling parameters using a pre-trained priority scoring model. This process makes the priority scoring more scientific and reasonable by comprehensively considering the task deadline, the current time and the road congestion. Subsequently, multiple first to-do tasks are sorted based on the calculated priority scores to form a task sorting list. This ensures that more urgent or important tasks are processed first. Then, the operation and maintenance planning of multiple first to-do tasks is carried out according to the task sorting results to formulate an efficient operation and maintenance plan. This can not only improve the efficiency of task execution, but also effectively avoid task delays caused by traffic jams or other factors. Finally, multiple first to-do tasks are operated and maintained based on the operation and maintenance plans of multiple first to-do tasks. This application calculates priority scores based on data and models, avoids the influence of human bias and emotions, and ensures that task allocation is more fair and reasonable. At the same time, through the comprehensive consideration of the first task scheduling parameters (such as deadline, current time, estimated arrival time, and urgency of to-do tasks), the task priority evaluation is ensured to be more comprehensive and accurate. In addition, by obtaining the estimated arrival time from the current location to the task destination in the first task scheduling parameters, the road congestion is reflected. This helps to consider traffic conditions in the operation and maintenance planning process, avoid delays in operation and maintenance plans due to congestion, and improve task execution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0050] Figure 1 A method flow chart of an operation and maintenance method of a comprehensive energy device based on a large model provided in an embodiment of the present application;

[0051] Figure 2 A method flow chart of a method for training a priority scoring model provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of the structure of an operation and maintenance device for integrated energy equipment based on a large model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] To facilitate understanding of the technical solutions provided by the embodiments of the present application, the background technology involved in the embodiments of the present application will be described below.

[0054] As described above, the daily operation and maintenance work of energy service providers is aimed at ensuring the normal operation of energy facilities, including various management and maintenance activities. However, at present, this field mainly relies on experience-based human planning, which leads to unfair task allocation, inability to fully consider task priorities and urgency, lack of scientificity and objectivity, and limits the improvement of work efficiency and service quality.

[0055] In order to solve this problem, an operation and maintenance method and related devices of integrated energy equipment based on a large model are provided in the embodiment of the present application. First, multiple first to-do tasks in the operation and maintenance work of the integrated energy equipment are determined, and the first task scheduling parameters of each task are obtained, including the deadline of the task, the current time, the estimated arrival time from the current location to the task destination, and the urgency of the first to-do task. The estimated arrival time here is calculated based on the real-time road traffic conditions. Then, for each first to-do task, the corresponding priority score is calculated according to the first task scheduling parameters using the pre-trained priority scoring model. Then, according to these priority scores, multiple first to-do tasks are sorted to obtain the sorting order of the tasks. Finally, operation and maintenance planning is carried out based on the sorting order of the tasks, and operation and maintenance plans for multiple first to-do tasks are formulated to operate and maintain multiple first to-do tasks according to the plan. The present application uses data and models to calculate priority scores, eliminates the influence of human bias and emotions, and ensures that task allocation is more fair and reasonable. At the same time, by comprehensively considering the first task scheduling parameters (such as deadline, current time, estimated arrival time, and urgency of to-do tasks), it is ensured that the task priority evaluation is more comprehensive and accurate. In addition, taking into account road congestion, obtaining the estimated arrival time will help to consider traffic conditions in operation and maintenance planning, avoid schedule delays, and improve execution efficiency.

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] See also Figure 1, which is a method flow chart of an operation and maintenance method of a comprehensive energy device based on a large model provided in an embodiment of the present application, such as Figure 1 As shown, the operation and maintenance method of the integrated energy equipment based on the large model may include steps S101-S105:

[0058] S101: Determine a plurality of first to-be-done tasks of the integrated energy equipment operation and maintenance work, and obtain a first task scheduling parameter of each first to-be-done task.

[0059] When planning the operation and maintenance of tasks, it is first necessary to determine all pending tasks (i.e., multiple first pending tasks) to be planned in the operation and maintenance of integrated energy equipment, that is, it is necessary to identify and list the tasks that need to be processed in the current time period. These tasks may come from different sources, such as work arrangements, project progress, customer needs, etc. Once these tasks are determined, it is necessary to further obtain the specific information of each task, i.e., the first task scheduling parameters.

[0060] The first task scheduling parameters include but are not limited to three main parts: task deadline, estimated arrival time from the current location to the task destination, and the urgency of the first to-do task. The task deadline refers to the deadline by which the task must be completed, which helps ensure that the task is completed on time. The current time of the task refers to the current point in time, which is very important for evaluating whether the remaining time is sufficient to complete the task. The estimated arrival time from the current location to the task destination refers to the estimated time from the current location to the task execution location. This distance is calculated based on real-time road traffic conditions, so that it can more accurately reflect the actual time required. The urgency of the first to-do task refers to how urgent or important the task ranked first in the to-do list is.

[0061] For example, suppose there are three pending tasks: daily boiler inspection (Task A), water quality testing (Task B), and weekly pump inspection (Task C). It is necessary to obtain the deadline and current time of each task, and also calculate the estimated arrival time from the current location to each task destination. This estimated arrival time is obtained through real-time traffic data, which can reflect the road congestion and ensure that the task execution time estimation is more accurate.

[0062] In this way, not only can the specific requirements of the task be determined, but the priority and execution time of each task can also be evaluated more accurately, thus providing a solid foundation for subsequent task priority scoring and operation and maintenance planning.

[0063] In a possible implementation, the degree of urgency can be described by urgent (e.g., emergency repair tasks), important (e.g., defect elimination tasks, maintenance tasks), and general (e.g., safety training tasks, emergency drill tasks). Urgent: The task needs to be processed immediately, and delay may lead to serious consequences. Important: The task needs to be processed in a shorter period of time, but can be placed after tasks with higher urgency. General: The task can be processed after other more urgent tasks. The score corresponding to urgent is 0 points, the score corresponding to important is 2 points, and the score corresponding to general is 3 points.

[0064] S102: For each of the first to-do tasks, a priority score of the first to-do task is calculated using a pre-trained priority scoring model based on the first task scheduling parameters corresponding to the first to-do task.

[0065] For each first-to-do task identified, its corresponding first-task scheduling parameters are input into a pre-trained priority scoring model for calculation to determine the priority score of the task. Through this process, the importance, urgency or other key factors of the task are measured using the pre-set model and the first-task scheduling parameters, thereby assigning a relative weight or priority to each task. This method aims to automatically determine the priority order of each task in the overall task list based on specific attributes of the task, such as deadlines, transportation distances, etc., thereby helping to optimize workflow and resource allocation. Among them, the scoring labels of the input data of the priority scoring model are calculated based on the large model.

[0066] See also Figure 2 , Figure 2 A method flow chart of a training method for a priority scoring model provided in an embodiment of the present application can be implemented through steps A1-A4:

[0067] A1: Identify multiple second-to-do tasks with scoring labels in the historical operation and maintenance work of integrated energy equipment, and define the loss function.

[0068] First, multiple second-to-do tasks with scoring labels in the historical operation and maintenance of integrated energy equipment are identified, and the loss function is defined. These second-to-do tasks are indicated by scoring labels to indicate their priority scores. The scoring labels are used to mark the importance level of each task, enabling the model to learn and identify which tasks need to be prioritized.

[0069] In one possible implementation, RankNet can be defined as the loss function. RankNet is an algorithm for learning to rank that aims to solve the ranking problem. It is based on a neural network and learns how to effectively rank items by comparing the relative order relationship between input data pairs. The main goal of RankNet is to maximize the ranking relevance index to achieve more accurate and reliable ranking results. The algorithm is widely used in fields such as information retrieval, recommendation systems, and advertising ranking. It can help the model rank items according to user needs or search query results, improving user experience and system efficiency.

[0070] In a possible implementation, the scoring label of the second to-do task is calculated by a large model.

[0071] Wherein, the large model is:

[0072]

[0073] Where S is the priority score, W t is the remaining time weight coefficient, T is the time window of the to-do task, a is the time change index, W d is the distance weight coefficient, D is the distance between the current location and the location of the to-do task, b is the distance change index, and W e is the urgency weight coefficient, E is the urgency of the task to be done, and c is the urgency change index; W t +W d +W e =1.

[0074] By adjusting W t , W d , W e The value of W determines the weights of the three factors T, D and E in the ranking to meet some basic ranking principles. t =0.3,W d =0.2,W e =0.5, the basic sorting principle that can be met at this time is "giving priority to completing urgent tasks, ensuring that tasks are not overdue and saving travel time as much as possible."

[0075] The values ​​of a, b, and c determine the rate of change of the priority score S with T, D, and E, respectively. For example, when a=0.5, after T is greater than 7 hours, the priority score S no longer changes significantly with the increase of the remaining time T.

[0076] In a possible implementation, the method further includes:

[0077] If a second to-do task is identified as being marked with an execution priority flag, the number of execution priority flags of the second to-do task is determined, and an increase score is set for the second to-do task based on the number of execution priority flags. The score tag of the second to-do task is then adjusted based on the increase score.

[0078] For example, assuming that a second to-do task is marked with 3 execution priority execution identifiers, then the second to-do task is set to increase the score to 3*0.01=0.03. Assuming that the score label of the second to-do task is 3, the score label obtained after adjusting the score label of the second to-do task based on the increased score is 3.03.

[0079] A2: Obtain the second task scheduling parameters of each second to-be-done task.

[0080] Next, the second task scheduling parameters of each second to-be-done task are obtained. These parameters include but are not limited to the following:

[0081] Time window: The time difference between the previously recorded time required to complete the second to-do task and the current time. The time window can reflect the urgency of the task and help evaluate how long it takes to complete the task.

[0082] The distance between the current location and the location of the second to-do task: the actual distance from the current location to the task destination previously recorded. This distance is calculated based on real-time road traffic conditions and can accurately reflect the traffic conditions and the actual time required.

[0083] Second, the urgency of the tasks to be done: The urgency of a task is usually determined by its importance and deadline. Quantifying the urgency can help better prioritize tasks.

[0084] A3: Input the second task scheduling parameters of the plurality of second to-do tasks and the plurality of second to-do tasks with scoring labels into a ranking learning model, and perform model training to obtain a primary scoring model.

[0085] The task scheduling parameters of the plurality of second to-do tasks and the second to-do tasks with the scoring labels are input into the sorting learning model for training, thereby obtaining a primary scoring model. The sorting learning model generates a preliminary priority scoring model by learning the relationship between the task scheduling parameters and the scoring labels.

[0086] A4: Iteratively adjust the parameters of the primary scoring model using the loss function to obtain the priority scoring model.

[0087] The defined loss function is used to iteratively adjust the parameters of the primary scoring model, and finally the optimized priority scoring model is obtained. The loss function is used to evaluate the error between the priority score output by the model and the actual scoring label. The model parameters are adjusted by minimizing the loss function to make the model's prediction results more accurate.

[0088] S103: Sort the plurality of first to-do tasks based on the priority scores to obtain a task ranking.

[0089] Sorting multiple first-to-do tasks based on priority scores means arranging the items in the task list according to the calculated relative importance of each task, placing the first-to-do task with the highest score at the first place in the task ranking, placing the first-to-do task with the second highest score at the second place in the task ranking, and so on. The ranking of other first-to-do tasks is similar.

[0090] This process is designed to determine the order of priority between tasks so that they can be handled most efficiently. By comparing and ranking the priority scores of each task, you can ensure that work is arranged in order of highest importance or most urgent deadlines. This method of prioritization helps improve work efficiency and ensure that critical tasks are handled in a timely manner, thereby optimizing time management and resource allocation.

[0091] S104: Performing operation and maintenance planning for the plurality of first to-be-done tasks based on the task sorting to obtain operation and maintenance plans for the plurality of first to-be-done tasks.

[0092] Operational planning for multiple first-to-do tasks based on task sequencing means developing a detailed work schedule or plan based on the determined task sequence and priority. This process includes scheduling the start time, end time, and possible overlap time of each task, and taking into account the relevance and dependencies between tasks. Through operational planning, the team can effectively allocate time and resources, ensure that important tasks receive full attention, and avoid time conflicts and delays.

[0093] In a possible implementation, step S104 performs operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain an operation and maintenance plan for the plurality of first to-be-done tasks, which specifically includes the following steps:

[0094] (1) Determine the start time of the operation and maintenance plan: First, you need to determine the start time of the entire operation and maintenance plan. This start time is the time point when the entire plan begins to be executed.

[0095] (2) Set the planned start time of the first task: Set the start time of the operation and maintenance plan to the planned start time of the first task in the task sequence. This means that the entire operation and maintenance plan starts from this time point, and the first task also starts to be executed from this time point.

[0096] (3) Calculate the planned start time of the subsequent task: For the Nth first to-do task in the task sequence (N>1), its planned start time is determined by the following three factors:

[0097] The start time of the N-1th first to-do task.

[0098] The estimated completion time of the N-1th first-to-do task.

[0099] The inter-task movement time between the N-1th first to-do task and the Nth first to-do task.

[0100] The specific logic is as follows:

[0101] The start time of the Nth task = the start time of the N-1th task + the estimated completion time of the N-1th task + the inter-task movement time between the N-1th task and the Nth task.

[0102] In this way, it can be ensured that the planned start time of each task is accurately calculated based on the completion time of the previous task and the necessary movement time, making the entire operation and maintenance plan more reasonable and feasible.

[0103] For example, suppose there is a task sorting list, where the first task is scheduled to start at 9:00 am, the estimated completion time is 1 hour, and the task moving time is 10 minutes. Then the second task will be scheduled to start at 10:10 am (9:00 + 1 hour + 10 minutes). This calculation method can ensure that the time schedule between tasks is seamless and improve overall work efficiency.

[0104] This method of formulating operation and maintenance plans can ensure that the time arrangement between tasks is reasonable, taking into account both the completion time of the task itself and the movement time between tasks, thereby ensuring the efficient execution of the entire operation and maintenance plan.

[0105] In a possible implementation, the method further includes:

[0106] (1) Determine the completion time of the operation and maintenance plan: First, you need to determine the completion time of the entire operation and maintenance plan. This completion time is the time point when the entire plan ends.

[0107] (2) Check the planned start time in the task sequence: For each first to-do task in the task sequence, determine whether its planned start time has been set. Specifically, if the planned start time of the Mth first to-do task in the task sequence has been set, but its planned start time is later than the completion time of the operation and maintenance plan, special processing is required.

[0108] (3) Adjust the planned start time: If the planned start time of the Mth task is later than the completion time of the operation and maintenance plan (i.e., the original planned start time of the task is beyond the effective range of the entire operation and maintenance plan), the planned start time of the task is adjusted to the completion time of the operation and maintenance plan. This means that the task cannot actually be started within the plan.

[0109] (4) Adjust the planned start time of subsequent tasks: Furthermore, the planned start time of all other pending tasks (i.e., subsequent pending tasks) that are scheduled after the Mth task also needs to be adjusted to the completion time of the operation and maintenance plan. The purpose of this is to ensure that all tasks that cannot be completed within the effective time of the operation and maintenance plan are marked as timed out and are no longer scheduled for execution.

[0110] In this way, it can be ensured that the operation and maintenance plan is always executed within the scheduled time frame, and tasks that cannot be started or completed on time can be properly handled. This not only helps to optimize resource utilization, but also improves the efficiency and predictability of overall work.

[0111] For example, suppose the completion time of an operation and maintenance plan is 5:00 p.m., and the planned start time of the fourth task in the task sequence is calculated as 5:10 p.m. According to the above rules, the planned start time of this task and all subsequent tasks will be adjusted to 5:00 p.m., indicating that they cannot be started within the scheduled time.

[0112] This mechanism can effectively avoid planning conflicts and ensure that the planning time of all tasks is within a reasonable range, making the operation and maintenance plan more feasible and efficient.

[0113] S105: Performing operation and maintenance on the plurality of first to-be-done tasks based on the operation and maintenance plans of the plurality of first to-be-done tasks.

[0114] Operating and maintaining multiple first-to-do tasks based on their operation and maintenance plans means actually operating and managing these tasks according to the operation and maintenance plans developed for each first-to-do task. This step involves executing pre-planned maintenance and monitoring measures to ensure that the equipment, system or process operates normally according to the established plan, and taking corresponding maintenance, repair or optimization measures when necessary.

[0115] By using the task scheduling parameters such as the predicted arrival time, task deadline, current time and urgency, combined with the priority score and task sorting results, the priority order and operation and maintenance plan of each task are determined. Therefore, "operating and maintaining the multiple first to-do tasks based on the operation and maintenance plans of the multiple first to-do tasks" emphasizes the implementation of the operation and maintenance plans planned in the early stage, and the orderly operation and maintenance operations of these tasks according to the preset order and priority.

[0116] Based on the contents of S101-S105, it is known that after determining multiple first to-do tasks of the operation and maintenance of integrated energy equipment, it is crucial to obtain the first task scheduling parameters of each task. These parameters include the task deadline, the current time of the task, the estimated arrival time from the current location to the task destination, and the urgency of the to-do task, and the estimated arrival time is calculated based on the real-time road traffic conditions. Then, for each first to-do task, the priority score is calculated using a pre-trained priority scoring model. By combining these scores with the scheduling parameters of each task, all first to-do tasks can be sorted to form a task sorting list. Finally, based on this sorting list, operation and maintenance planning can be carried out, and an operation and maintenance plan can be formulated to operate and maintain multiple first to-do tasks to ensure that these first to-do tasks are completed efficiently. This application avoids the influence of human bias and emotions by calculating the priority score based on data and models, ensuring that the task allocation is more fair and reasonable. At the same time, the first task scheduling parameters (such as deadline, current time, estimated arrival time, and urgency of to-do tasks) are comprehensively considered to make the task priority evaluation more comprehensive and accurate. In addition, by obtaining the estimated arrival time from the current location to the mission destination, the road congestion situation can be reflected, so that the traffic conditions can be fully considered in the operation and maintenance planning process, avoiding delays in operation and maintenance plans due to road congestion, and further improving the efficiency of task execution.

[0117] See also Figure 3 , Figure 3 A schematic diagram of the structure of an operation and maintenance device for integrated energy equipment based on a large model provided in an embodiment of the present application. Figure 3 As shown, the operation and maintenance device of the comprehensive energy equipment based on the large model includes:

[0118] A first task determination unit 301 is used to determine a plurality of first pending tasks for operation and maintenance of integrated energy equipment;

[0119] The first acquisition unit 302 is used to acquire the first task scheduling parameters of each first to-do task, wherein the first task scheduling parameters include the task deadline, the task current time, the estimated arrival time from the current location to the task destination, and the urgency of the first to-do task; the estimated arrival time is calculated based on the real-time road traffic conditions;

[0120] A scoring calculation unit 303 is used to calculate the priority score of each of the first to-do tasks based on the first task scheduling parameters corresponding to the first to-do tasks using a pre-trained priority scoring model; the scoring label of the input data of the priority scoring model is calculated based on the large model;

[0121] A task sorting unit 304 is used to sort the plurality of first to-do tasks based on the priority scores to obtain a task sorting;

[0122] An operation and maintenance planning unit 305 is used to perform operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain operation and maintenance plans for the plurality of first to-be-done tasks;

[0123] The operation and maintenance unit 306 is used to perform operation and maintenance on the multiple first to-be-done tasks based on the operation and maintenance plans of the multiple first to-be-done tasks.

[0124] In a possible implementation, the operation and maintenance planning unit 305 specifically includes:

[0125] A start time determination unit, used to determine the start time of the operation and maintenance plan;

[0126] A first time setting unit, used to set the start time of the operation and maintenance plan to the planned start time of the first first to-be-done task in the task sequence;

[0127] The second time unit is used to set the planned start time of the Nth first to-do task in the task sequence in the operation and maintenance plan to the start time of the N-1th first to-do task in the task sequence plus the estimated completion time of the N-1th first to-do task, plus the inter-task movement time between the N-1th first to-do task and the Nth first to-do task; N is an integer greater than 1.

[0128] In a possible implementation manner, the device further includes:

[0129] A completion time determination unit, used to determine the completion time of the operation and maintenance plan;

[0130] A third time unit, if the planned start time of the Mth first to-do task in the task sorting has been set, but its planned start time is later than the completion time of the operation and maintenance plan, then it is used to set the planned start time of the first to-do task and the planned start time of the subsequent to-do tasks of the first to-do task to the completion time of the operation and maintenance plan; the subsequent to-do tasks include other to-do tasks that are arranged behind the first to-do task in the task sorting; M is an integer greater than 1.

[0131] In a possible implementation manner, the device further includes:

[0132] A second task determination unit is used to determine a plurality of second to-do tasks with scoring labels in the historical operation and maintenance work of the integrated energy equipment, and define a loss function; the scoring label is used to indicate the priority score of the second to-do task;

[0133] A second acquisition unit is used to acquire the second task scheduling parameters of each second to-do task; the second task scheduling parameters include the time window of the second to-do task, the distance between the current position and the position of the second to-do task, and the urgency of the second to-do task; the time window of the second to-do task is the time difference between the time required to complete the second to-do task and the current time;

[0134] A model training unit, used for inputting the second task scheduling parameters of the plurality of second to-do tasks and the plurality of second to-do tasks with scoring labels into a ranking learning model, and performing model training to obtain a primary scoring model;

[0135] A parameter adjustment unit is used to use the loss function to adjust the parameters of the primary scoring model to obtain the priority scoring model.

[0136] In a possible implementation manner, the device further includes:

[0137] a priority execution mark determination unit, configured to determine the number of the priority execution marks if it is identified that one of the second to-do tasks is marked with an execution priority execution mark;

[0138] an increase score setting unit, configured to set an increase score for the second to-do task based on the number of the execution priority execution identifiers;

[0139] A scoring label adjustment unit is used to adjust the scoring label of the second to-do task based on the increased score.

[0140] In a possible implementation, the scoring label of the second to-do task is calculated by a large model;

[0141] Wherein, the large model is:

[0142]

[0143] Where S is the priority score, W t is the remaining time weight coefficient, T is the time window of the to-do task, a is the time change index, W d is the distance weight coefficient, D is the distance between the current location and the location of the to-do task, b is the distance change index, and W e is the urgency weight coefficient, E is the urgency of the task to be done, and c is the urgency change index; W t +W d +W e =1.

[0144] In addition, an embodiment of the present application also provides an operation and maintenance method device for an integrated energy equipment based on a large model, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the operation and maintenance method for the integrated energy equipment based on a large model as described above is implemented.

[0145] In addition, an embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device executes the operation and maintenance method of the integrated energy equipment based on the large model as described above.

[0146] The embodiment of the present application provides an operation and maintenance device for integrated energy equipment based on a large model. First, a first task determination unit 301 is used to determine multiple first to-do tasks of the operation and maintenance work of the integrated energy equipment, and a first acquisition unit 302 is used to obtain the first task scheduling parameters of each first to-do task. The first task scheduling parameters include the task deadline, the current time of the task, the estimated arrival time from the current location to the task destination, and the urgency of the first to-do task. The score calculation unit 303 calculates the priority score of the first to-do task based on the first task scheduling parameters corresponding to the first to-do task using a pre-trained priority scoring model for each first to-do task. Then, the task sorting unit 304 is used to sort the multiple first to-do tasks based on the priority score to obtain the task sorting, so that the operation and maintenance planning unit 305 can perform operation and maintenance planning for the multiple first to-do tasks based on the task sorting, and obtain the operation and maintenance plans of the multiple first to-do tasks. Finally, the operation and maintenance unit 306 operates and maintains the multiple first to-do tasks based on the operation and maintenance plans of the multiple first to-do tasks. The present application uses data and models to calculate priority scores, thereby eliminating the influence of human bias and emotions and ensuring the fairness and rationality of task allocation. At the same time, the task priority is comprehensively and accurately evaluated by comprehensively considering the first task scheduling parameters (such as deadline, current time, estimated arrival time, and urgency of pending tasks). In addition, by obtaining the estimated arrival time from the current location to the destination in the first task scheduling parameters, the road congestion can be reflected, which helps to consider traffic conditions in operation and maintenance planning, avoid delays in operation and maintenance plans due to traffic congestion, and thus improve task execution efficiency.

[0147] The above is a detailed introduction to the operation and maintenance method and related devices of a comprehensive energy equipment based on a large model provided by the present application. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can refer to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

[0148] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0149] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. An operation and maintenance method for integrated energy equipment based on a large model, characterized in that: The method comprises: Determine multiple first to-do tasks of the integrated energy equipment operation and maintenance work, and obtain first task scheduling parameters of each first to-do task, wherein the first task scheduling parameters include task deadline, task current time, estimated arrival time from the current location to the task destination, and urgency of the first to-do task; the estimated arrival time is calculated based on real-time road traffic conditions; For each of the first to-do tasks, a priority score of the first to-do task is calculated based on the first task scheduling parameters corresponding to the first to-do task using a pre-trained priority scoring model; the scoring label of the input data of the priority scoring model is calculated based on a large model; Sorting the plurality of first to-do tasks based on the priority scores to obtain a task ranking; Performing operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain operation and maintenance plans for the plurality of first to-be-done tasks; The multiple first to-be-done tasks are operated and maintained based on the operation and maintenance plans of the multiple first to-be-done tasks.

2. The method according to claim 1, characterized in that The performing operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting to obtain an operation and maintenance plan for the plurality of first to-be-done tasks includes: Determine the start time of the operation and maintenance plan; Setting the start time of the operation and maintenance plan to the planned start time of the first first to-be-done task in the task sequence; In the operation and maintenance plan, the planned start time of the Nth first to-do task in the task sequence is set to the start time of the N-1th first to-do task in the task sequence plus the estimated completion time of the N-1th first to-do task, plus the inter-task movement time between the N-1th first to-do task and the Nth first to-do task; N is an integer greater than 1.

3. The method according to claim 2, characterized in that The method further comprises: Determine the completion time of the operation and maintenance plan; If the planned start time of the Mth first to-do task in the task sorting has been set, but its planned start time is later than the completion time of the operation and maintenance plan, then the planned start time of the first to-do task and the planned start time of the subsequent to-do tasks of the first to-do task are both set to the completion time of the operation and maintenance plan; the subsequent to-do tasks include other to-do tasks that are arranged behind the first to-do task in the task sorting; M is an integer greater than 1.

4. The method according to claim 1, characterized in that: The training process of the pre-trained priority scoring model includes: Determine a plurality of second to-do tasks with scoring labels in the historical operation and maintenance work of the integrated energy equipment, and define a loss function; the scoring label is used to indicate the priority score of the second to-do task; Obtaining the second task scheduling parameters of each second to-do task; the second task scheduling parameters include the time window of the second to-do task, the distance between the current location and the location of the second to-do task, and the urgency of the second to-do task; the time window of the second to-do task is the time difference between the time required to complete the second to-do task and the current time; Inputting the second task scheduling parameters of the plurality of second to-do tasks and the plurality of second to-do tasks with scoring labels into a ranking learning model, and performing model training to obtain a primary scoring model; The loss function is used to iteratively adjust the parameters of the primary scoring model to obtain the priority scoring model.

5. The method according to claim 4, characterized in that The method further comprises: If it is identified that one of the second to-do tasks is marked with an execution priority flag, determining the number of the execution priority flags; Setting an increased score for the second to-do task based on the number of execution priority execution identifiers; The scoring label of the second to-do task is adjusted based on the increased scoring.

6. The method according to claim 4, characterized in that The score label of the second to-do task is calculated by the big model; Wherein, the large model is: Where S is the priority score, W t is the remaining time weight coefficient, T is the time window of the to-do task, a is the time change index, W d is the distance weight coefficient, D is the distance between the current location and the location of the to-do task, b is the distance change index, and W e is the urgency weight coefficient, E is the urgency of the task to be done, and c is the urgency change index; W t +W d +W e =1.

7. An operation and maintenance device for integrated energy equipment based on a large model, characterized in that: The device comprises: A first task determination unit, used to determine a plurality of first to-do tasks for operation and maintenance of integrated energy equipment; A first acquisition unit is used to acquire first task scheduling parameters of each first to-do task, wherein the first task scheduling parameters include task deadline, task current time, estimated arrival time from current location to task destination, and urgency of the first to-do task; the estimated arrival time is calculated based on real-time road traffic conditions; a scoring calculation unit, configured to calculate, for each of the first to-do tasks, a priority score of the first to-do task based on the first task scheduling parameters corresponding to the first to-do task using a pre-trained priority scoring model; the scoring label of the input data of the priority scoring model being calculated based on a large model; A task sorting unit, configured to sort the plurality of first to-do tasks based on the priority scores to obtain a task sorting; An operation and maintenance planning unit, configured to perform operation and maintenance planning on the plurality of first to-be-done tasks based on the task sorting, and obtain operation and maintenance plans for the plurality of first to-be-done tasks; An operation and maintenance unit is used to operate and maintain the multiple first to-be-done tasks based on the operation and maintenance plans of the multiple first to-be-done tasks.

8. The method according to claim 1, characterized in that The operation and maintenance planning unit specifically includes: A start time determination unit, used to determine the start time of the operation and maintenance plan; A first time setting unit, used to set the start time of the operation and maintenance plan to the planned start time of the first first to-be-done task in the task sequence; The second time unit is used to set the planned start time of the Nth first to-do task in the task sequence in the operation and maintenance plan to the start time of the N-1th first to-do task in the task sequence plus the estimated completion time of the N-1th first to-do task, plus the inter-task movement time between the N-1th first to-do task and the Nth first to-do task; N is an integer greater than 1.

9. A method and device for operation and maintenance of integrated energy equipment based on a large model, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the operation and maintenance method of the integrated energy equipment based on the large model as described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the operation and maintenance method of a comprehensive energy device based on a large model as described in any one of claims 1 to 6.

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