CN-122022349-A - Operation and maintenance task planning and scheduling method and system integrating weather window prediction

CN122022349ACN 122022349 ACN122022349 ACN 122022349ACN-122022349-A

Abstract

The invention discloses an operation and maintenance task planning and scheduling method and system integrating weather window prediction, and relates to the technical field of operation and maintenance task planning and scheduling. The method comprises the steps of obtaining an operation and maintenance task set to be scheduled and weather forecast data corresponding to each task, executing weather threshold values according to the operation and maintenance tasks and any time slice in a future forecast period, generating weather suitability scores for quantitatively representing the suitability of the tasks in the time slice, constructing a time-space operation and maintenance window matrix, storing the weather suitability scores of the operation and maintenance tasks in any time slice, solving the operation and maintenance task set by adopting a preset optimization algorithm based on the time-space operation and maintenance window matrix and comprehensively considering dependency constraints and resource constraints among the tasks to generate an optimal scheduling scheme. The invention converts the uncertain scheduling problem into the combined optimization problem in the deterministic feasible domain by constructing the quantized space-time operation and maintenance window matrix in advance.

Inventors

ZHANG HAIJUN
ZHANG GUOXIN
XUE HUI
ZHAO YAZHOU
QU YANFEI
ZHANG SIYUAN
WANG YE

Assignees

国华（河北）新能源有限公司

Dates

Publication Date: 20260512
Application Date: 20260204

Claims (10)

1. The operation and maintenance task planning and scheduling method integrating weather window prediction is characterized by comprising the following steps of: acquiring an operation and maintenance task set to be scheduled, wherein the operation and maintenance task set comprises a plurality of operation and maintenance tasks, and acquiring weather forecast data of the plurality of operation and maintenance tasks in a future prediction period; Aiming at any time slice in the operation and maintenance task and the future prediction period in the operation and maintenance task set, generating a weather suitability score based on weather forecast data corresponding to the operation and maintenance task and a preset task execution weather threshold of the operation and maintenance task, wherein the weather suitability score is used for quantitatively representing weather suitability of the operation and maintenance task executed in the time slice; Constructing a time-space operation and maintenance window matrix based on the weather suitability score of the operation and maintenance task at any time slice; Based on the space-time operation and maintenance window matrix, comprehensively considering task dependency constraints and resource constraints among operation and maintenance tasks in the operation and maintenance task set, and solving the operation and maintenance task set by adopting a preset optimization algorithm to generate an optimal scheduling scheme.
2. The method of claim 1, wherein the step of generating a weather suitability score comprises: And inputting a real-time weather forecast value corresponding to the operation and maintenance task and the task execution weather threshold value into a preset weather suitability score function, wherein the output value of the weather suitability score function is smoothly attenuated as the real-time weather forecast value approaches the task execution weather threshold value so as to generate the weather suitability score.
3. The method of claim 2, wherein the weather suitability score function is a normalized gaussian function, and the step of generating the weather suitability score is specifically: By the formula Calculating the weather suitability score; Wherein, the For the weather suitability score, v is the real-time weather forecast value, Meteorological thresholds are performed for the tasks.
4. The method of claim 1, further comprising, prior to said solving the set of operation and maintenance tasks using a preset optimization algorithm: determining a plurality of optimization target weight factors for characterizing task priority, time sensitivity and resource dependence based on an analytic hierarchy process; the step of solving the operation and maintenance task set by adopting a preset optimization algorithm comprises the following steps: And in the solving process of the optimization algorithm, evaluating the fitness of each candidate scheduling scheme based on the plurality of optimization target weight factors, the weather suitability score obtained from the space-time operation and maintenance window matrix, the meeting condition of task dependence constraint and the meeting condition of resource constraint.
5. The method of claim 4, wherein the predetermined optimization algorithm is a genetic algorithm, and the step of evaluating the fitness of each candidate scheduling scheme comprises: The fitness of the candidate scheduling scheme is calculated by a fitness function comprising a benefit term related to task priority and time sensitivity, and a penalty term related to violating task dependency constraints and resource constraints.
6. The method of claim 5, wherein the fitness function comprises: ; Wherein, the The adaptability of the candidate scheduling scheme S is achieved; A starting time slice of the task i; A static priority score for task i; for task i at start time slice Is a weather suitability score for (1); Weighting factors of task priority, time sensitivity and resource dependence respectively; counting the number of dependency violations; counting the number of resource conflict times; And Is a preset penalty factor.
7. The method according to claim 5 or 6, wherein the step of solving the set of operation and maintenance tasks using a preset optimization algorithm further comprises: when generating an initial population, adopting a topological sorting method based on a task dependency graph to generate an initial candidate scheduling scheme set meeting the task dependency constraint.
8. The method of claim 1, further comprising, after said constructing the time-space operation-dimension window matrix: Judging whether values of all elements in the time-space operation and maintenance window matrix are zero or not; if yes, generating and sending an emergency delay report, and terminating the scheduling flow.
9. An operation and maintenance task planning and scheduling system integrating weather window prediction is characterized by comprising the following steps: the multi-source data acquisition and preprocessing module is used for acquiring an operation and maintenance task set to be scheduled, wherein the operation and maintenance task set comprises a plurality of operation and maintenance tasks, and acquiring weather forecast data of the operation and maintenance tasks in a future prediction period; The time-space operation and maintenance window generation module is used for aiming at any time slice in the operation and maintenance task and the future prediction period, generating a weather suitability score based on the weather forecast data corresponding to the operation and maintenance task and a preset task execution weather threshold of the operation and maintenance task, and constructing a time-space operation and maintenance window matrix based on the weather suitability score of the operation and maintenance task in any time slice, wherein the weather suitability score is used for quantitatively representing the weather suitability of the operation and maintenance task executed in the time slice; And the strategy optimization engine module is used for solving the operation and maintenance task set by adopting a preset optimization algorithm based on the space-time operation and maintenance window matrix and comprehensively considering task dependency constraint and resource constraint among each operation and maintenance task in the operation and maintenance task set so as to generate an optimal scheduling scheme.
10. The system of claim 9, further comprising: The strategy scheduling configuration module is used for determining a plurality of optimization target weight factors for representing task priority, time sensitivity and resource dependence based on an analytic hierarchy process; the optimization engine module is specifically configured to evaluate, during a solution process of the optimization algorithm, fitness of each candidate scheduling scheme based on the plurality of optimization target weight factors, weather suitability scores obtained from the space-time operation and maintenance window matrix, satisfaction of task dependency constraints, and satisfaction of resource constraints.

Description

Operation and maintenance task planning and scheduling method and system integrating weather window prediction Technical Field The invention relates to the technical field of operation and maintenance task planning and scheduling, in particular to an operation and maintenance task planning and scheduling method and system integrating weather window prediction. Background In operation and maintenance management in the fields of wind power, power grid, large ports and the like, task planning and scheduling are a core and complex decision-making work. The scheduling system needs to reasonably distribute a large number of operation and maintenance tasks to a future time window on the premise of meeting the constraint of logical dependency relationship and resource uniqueness among the tasks. However, most of these field operations and maintenance tasks are performed outdoors, and their executability is severely dependent on real-time weather conditions such as wind speed, rainfall, temperature, etc. In the scheduling method in the prior art, when dynamic weather information is processed, fundamental contradiction between decision and information separation exists generally. The scheduling engine, when performing optimization iterations, needs to repeatedly query the external meteorological system for its feasibility at a specified point in time for each task in each candidate. This mode results in significant computational overhead and time delay, making large-scale, global, refined optimization impractical. Meanwhile, the conventional method can only obtain yes/no binary judgment, and potential risks of executing tasks under critical meteorological conditions cannot be quantified, so that the generated scheduling scheme lacks robustness. Therefore, how to efficiently fuse dynamic weather information and static scheduling constraint to realize rapid and robust global optimization is a technical problem to be solved in the field. Disclosure of Invention The invention aims to provide an operation and maintenance task planning scheduling method and system integrating weather window prediction, which are used for solving the technical problems of low calculation efficiency and risk quantification missing caused by decision and information separation in the prior art. The invention provides an operation and maintenance task planning scheduling method integrating weather window prediction, which comprises the steps of obtaining an operation and maintenance task set to be scheduled, wherein the operation and maintenance task set comprises a plurality of operation and maintenance tasks, obtaining weather forecast data of the operation and maintenance tasks in a future prediction period, solving the operation and maintenance task set by adopting a preset optimization algorithm according to any time slice of the operation and maintenance tasks in the operation and maintenance task set and any time slice in the future prediction period, and generating a weather suitability score based on the weather forecast data corresponding to the operation and maintenance tasks and a task execution weather threshold of the preset operation and maintenance tasks, wherein the weather suitability score is used for quantifying weather suitability of the operation and maintenance tasks executed in the time slice, constructing a time-space operation and maintenance window matrix based on the weather suitability score of the operation and maintenance tasks in the any time slice, and comprehensively considering task dependency constraint and resource constraint among the operation and maintenance tasks in the operation and maintenance task set, so as to generate an optimal scheduling scheme. Optionally, the step of generating the weather suitability score comprises the step of inputting a real-time weather forecast value corresponding to the operation and maintenance task and the task execution weather threshold value into a preset weather suitability score function, wherein the output value of the weather suitability score function is smoothly attenuated as the real-time weather forecast value approaches the task execution weather threshold value so as to generate the weather suitability score. Optionally, the weather suitability score function is a normalized Gaussian function, and the step of generating the weather suitability score is specifically performed by the formulaCalculating the weather suitability score, wherein,For the weather suitability score, v is the real-time weather forecast value,Meteorological thresholds are performed for the tasks. Optionally, before the operation and maintenance task set is solved by adopting a preset optimization algorithm, the method further comprises the step of determining a plurality of optimization target weight factors used for representing task priority, time sensitivity and resource dependence on the basis of an analytic hierarchy process, wherein the step of solving the operation and maintena