Intelligent power construction resource allocation method

Abstract

The invention discloses an intelligent power construction resource allocation method, and relates to the technical field of data processing, and the method comprises the steps: building a power construction related data storage library, and obtaining historical data in a power construction process according to the storage library; according to the method, through analysis of power construction project characteristics, research of historical data and definition of engineering requirements, multiple factors are integrated, a construction maintenance progress deviation threshold value is preset, an allowable deviation range between an actual construction maintenance progress and a twinborn prediction progress is measured, a resource reconfiguration process is triggered when the deviation exceeds the limit, and the twinborn prediction progress is reconfigured. Resource allocation can be dynamically adjusted according to actual conditions, the utilization rate of construction resources is effectively improved, a resource allocation execution and feedback mechanism is effectively improved, a resource allocation strategy is continuously adjusted, continuous optimization of resource allocation is achieved, the overall efficiency of power construction is improved, and sufficient sensitivity to construction progress deviation is guaranteed; therefore, reasonable configuration of construction resources and accurate control of the construction period are realized.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an intelligent power construction resource configuration method. Background Art

[0002] Power construction is a relatively broad field, covering construction, installation, maintenance and other operations related to multiple links such as power generation, transmission, transformation, distribution and power consumption. It includes the construction of large-scale substations, regular inspections of power facilities such as power plants and substations, urban power grid transformation and rural power grid upgrades, as well as the installation of high-voltage transmission lines. In power construction and maintenance work, especially in scenarios such as industrial parks with a certain scale and complex power system, reasonable resource allocation is crucial to ensuring a stable power supply, improving construction efficiency and controlling costs.

[0003] Traditional power construction resource allocation methods often rely on experience, lack accurate monitoring and real-time adjustments to the construction process, and rely on manual experience and static scheduling tables. They are unable to respond in real time to construction disturbances such as equipment failures and sudden weather changes. During the construction process, actual resource usage and equipment operating status information cannot be fed back in a timely manner, making it difficult for managers to detect potential problems in a timely manner. When deviations between actual and planned progress are discovered, there is a lack of dynamic response mechanisms, and resources cannot be adjusted in real time during construction. This seriously affects construction efficiency and resource utilization, increases construction costs, and fails to integrate construction progress and environmental data to generate dynamic decision-making basis. In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0004] The purpose of this invention is to define the construction and maintenance progress deviation threshold, and to achieve accurate prediction and real-time monitoring of the construction progress based on twin prediction technology, so as to timely discover the deviation between actual construction and prediction, and provide an accurate basis for resource reconfiguration.

[0005] To achieve the above-mentioned objectives, the present invention adopts the following technical solutions: a method for intelligent power construction resource allocation, comprising the following steps: establishing a data repository related to power construction, obtaining historical data of the power construction process from the repository, generating a data list of construction time and construction volume, and obtaining demand information of the power construction link based on the construction data list; Step 2: During resource allocation, real-time data from the power construction process is obtained. Based on a deep learning neural network, a construction prediction model for construction progress prediction is established. The real-time data is fed into the construction prediction model to output the model-predicted progress value. Based on the power construction demand and time requirements, a power construction maintenance progress deviation threshold is pre-set to generate the deviation range between the actual construction maintenance progress and the twin predicted progress during the power construction process. Step 3: Establish a power construction resource sharing platform through mobile terminals based on IoT monitoring devices to collect real-time construction and maintenance progress information, including completed workload, working hours, and personnel usage, and generate real-time construction and maintenance actual progress data; Step 4: Compare the real-time collected construction and maintenance progress data with the progress value predicted by the twin prediction model to generate a comparative analysis value. Based on the comparative analysis value, make resource allocation judgments and trigger the resource reconfiguration process. Based on the demand information of the power construction link, dynamically adjust resources and obtain dynamic adjustment information. Step 5: Obtain the dynamic control information and send it to the control platform to generate real-time allocation instructions, and send the dynamic control information to the resource management end for resource control execution.

[0006] Furthermore, the method further includes the following steps: in step 1, a data repository for power construction related data is established, the data repository stores and records data through a control module, and before data storage, the relevant data is cleaned and pre-processed on a unified data platform to ensure the accuracy and consistency of the data; Establish a classification of various resources required for power construction, including human, material, and financial resources, and establish detailed attribute characteristics for each type of resource.

[0007] Furthermore, the demand information for power construction is obtained, including the following: S100. Obtain historical data from the repository regarding power construction, recording basic information about each power construction project, including the planned start and end times of the construction project; construction progress: recording actual construction progress, including actual start and end times, and completed workload; and recording information about equipment used during construction, including construction personnel information. S101. Group historical data by construction task, and calculate the cumulative construction volume and construction time of each task to obtain a construction data list, and sort them by construction start time; S102. Analyze and sort the data list, mark the demand information of each construction task link, including but not limited to specific requirements in terms of manpower, material resources, equipment, and technology, and obtain the demand information of the power construction link.

[0008] Furthermore, a construction prediction model for construction progress prediction is established. The specific steps are as follows: S200, obtaining the demand information of the power construction link, using the number of construction workers, completed construction volume, total construction volume, expected construction time, and actual construction time data as the sample data set of the construction prediction model, checking the data for missing values, outliers, and duplicate data, identifying, correcting, deleting, and standardizing the data to have a similar scale; S201: The number of construction workers, the amount of construction completed, and the expected construction time are used as inputs of the construction prediction model. The output data is analyzed by the processing layer, and the actual predicted construction time is used as output. S202, the specific process of data analysis is as follows: N is assumed to represent the number of construction workers, C represents the amount of construction completed, Represents the expected construction time, represents the actual predicted construction time, , Where, and is the set adjustment coefficient, is the actual number of construction workers, The total project volume.

[0009] Furthermore, the power construction and maintenance progress deviation threshold is pre-set, specifically including the following: S300, obtaining demand information for power construction links, selecting some similar power construction project demand information for analyzing the power construction maintenance progress; S301. Based on the demand information of some similar power construction projects, the time range and fluctuation of each power construction project are counted, and the average value and standard deviation statistics are calculated to obtain the construction progress time of each power construction project. The deviation value is generated by performing comparative analysis based on the predicted construction time. S301. Obtain the deviation value of each power construction project, sort them according to the length of time, obtain the time deviation range, and set the initial threshold within this range: Preset is the actual completion time of task I, is the planned completion time of task I, is the deviation value of the I-th task, I={1,2,3,…,N}; , The thresholds are: The maximum value of MAX, The minimum value of MIN, get the threshold .

[0010] Furthermore, the resource reconfiguration process is triggered. The specific operations are as follows: S300: When the deviation between the predicted construction time and the actual scheduled construction time exceeds a set threshold, the resource reconfiguration process is triggered, and the required resource types, quantities, and deployment plans are recalculated based on the deviation and the current resource status; S300, when the deviation threshold is greater than y+x, human resources are dynamically adjusted in real time; when the deviation threshold is greater than 2y, human resources and equipment resources are increased and regulated; S300. When the actual progress is less than the biased threshold, the input of some resources will be appropriately reduced. During the resource reallocation process, the execution of resource allocation and changes in construction progress will be monitored in real time. During the resource allocation process, the identified needs will be summarized and prioritized according to the degree of impact on construction progress, quality and cost.

[0011] Furthermore, the establishment of a power construction resource sharing platform specifically includes the following: Establish a real-time communication and collaboration platform between construction team members, between different construction links, and with external partners to share construction information in real time; Based on the geographic information system, a visual collaborative map is constructed to mark the personnel distribution, equipment location, and material storage point information of each construction site in real time. People from all parties can obtain detailed resource information and construction progress by clicking on the marks on the map.

[0012] Furthermore, step five also includes sending the generated resource allocation decision to the corresponding execution module, establishing a feedback mechanism, obtaining feedback information during the resource allocation execution process in real time, setting clear monitoring points and feedback channels in each execution link, and obtaining feedback information during the resource allocation execution in real time, so as to ensure that the feedback information is in place on time, the allocation is smooth, and there are no abnormal conditions. When an abnormal condition occurs, an early warning reminder signal is generated for real-time dynamic viewing.

[0013] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This intelligent power construction resource allocation method, based on the analysis of the characteristics of power construction projects, the study of historical data and the clarification of engineering requirements, comprehensively considers multiple factors, pre-sets the construction and maintenance progress deviation threshold, measures the allowable deviation range between the actual construction and maintenance progress and the twin predicted progress, and triggers the resource reconfiguration process when the deviation exceeds the limit. It can dynamically adjust resource allocation according to actual conditions, effectively improve the utilization rate of construction resources, resource allocation execution and feedback mechanism, continuously adjust resource allocation strategy, realize continuous optimization of resource allocation, improve the overall efficiency of power construction, ensure sufficient sensitivity to construction progress deviation, thereby achieving reasonable allocation of construction resources and precise control of construction period. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Shown is a schematic diagram of the overall external structure of the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] Example 1:

[0017] like Figure 1 As shown, a method for configuring intelligent power construction resources includes the following steps: Step 1: Establish a data repository related to power construction, obtain historical data on the power construction process from the repository, generate a list of construction time and construction volume data, and obtain demand information for the power construction process based on the construction data list; Step 2: During resource allocation, real-time data from the power construction process is obtained. Based on a deep learning neural network, a construction prediction model for construction progress prediction is established. The real-time data is fed into the construction prediction model to output the model-predicted progress value. Based on the power construction demand and time requirements, a power construction maintenance progress deviation threshold is pre-set to generate the deviation range between the actual construction maintenance progress and the twin predicted progress during the power construction process. Step 3: Establish a power construction resource sharing platform through mobile terminals based on IoT monitoring devices to collect real-time construction and maintenance progress information, including completed workload, working hours, and personnel usage, and generate real-time construction and maintenance actual progress data; Step 4: Compare the real-time collected construction and maintenance progress data with the progress value predicted by the twin prediction model to generate a comparative analysis value. Based on the comparative analysis value, make resource allocation judgments and trigger the resource reconfiguration process. Based on the demand information of the power construction link, dynamically adjust resources and obtain dynamic adjustment information. Step 5: Obtain the dynamic control information and send it to the control platform to generate real-time allocation instructions, and send the dynamic control information to the resource management end for resource control execution.

[0018] The following steps are also included: in step 1, a data repository for power construction related data is established, the repository stores records through a control module, and before data storage, the relevant data is cleaned and pre-processed on a unified data platform to ensure the accuracy and consistency of the data; Establish a classification of various resources required for power construction, including human, material, and financial resources, and establish detailed attribute characteristics for each type of resource.

[0019] By using IoT devices and sensor technology, data such as construction progress, resource usage, and environmental parameters can be collected in real time at the construction site. By installing sensors on construction equipment, the equipment's operating status and working hours can be obtained in real time.

[0020] The demand information for power construction is as follows: S100. Obtain historical data from the repository regarding power construction, recording basic information about each power construction project, including the planned start and end times of the construction project; construction progress: recording actual construction progress, including actual start and end times, and completed workload; and recording information about equipment used during construction, including construction personnel information. S101. Group historical data by construction task, and calculate the cumulative construction volume and construction time of each task to obtain a construction data list, and sort them by construction start time; S102. Analyze and sort the data list, mark the demand information of each construction task link, including but not limited to specific requirements in terms of manpower, material resources, equipment, and technology, and obtain the demand information of the power construction link.

[0021] The construction prediction model for construction progress prediction is established. The specific steps are as follows: S200, obtaining the demand information of the power construction link, using the number of construction workers, completed construction volume, total construction volume, expected construction time, and actual construction time data as the sample data set of the construction prediction model, checking the data for missing values, outliers, and duplicate data, identifying, correcting, deleting, and standardizing the data to have a similar scale; S201: The number of construction workers, the amount of construction completed, and the expected construction time are used as inputs of the construction prediction model. The output data is analyzed by the processing layer, and the actual predicted construction time is used as output. S202, the specific process of data analysis is as follows: N is assumed to represent the number of construction workers, C represents the amount of construction completed, Represents the expected construction time, represents the actual predicted construction time, , Where, and is the set adjustment coefficient, is the actual number of construction workers, The total project volume.

[0022] Pre-set power construction and maintenance progress deviation thresholds, including the following: S300, obtaining demand information for power construction links, selecting some similar power construction project demand information for analyzing the power construction maintenance progress; S301. Based on the demand information of some similar power construction projects, the time range and fluctuation of each power construction project are counted, and the average value and standard deviation statistics are calculated to obtain the construction progress time of each power construction project. The deviation value is generated by performing comparative analysis based on the predicted construction time. S301. Obtain the deviation value of each power construction project, sort them according to the length of time, obtain the time deviation range, and set the initial threshold within this range: Preset is the actual completion time of task I, is the planned completion time of task I, is the deviation value of the I-th task, I={1,2,3,…,N}; , The thresholds are: The maximum value of MAX, The minimum value of MIN, get the threshold .

[0023] And trigger the resource reconfiguration process, the specific operations are as follows: S300: When the deviation between the predicted construction time and the actual scheduled construction time exceeds a set threshold, the resource reconfiguration process is triggered, and the required resource types, quantities, and deployment plans are recalculated based on the deviation and the current resource status; S300, when the deviation threshold is greater than y+x, human resources are dynamically adjusted in real time; when the deviation threshold is greater than 2y, human resources and equipment resources are increased and regulated; S300: When the actual progress is less than the bias threshold, appropriately reduce the input of some resources. During the resource reallocation process, monitor the execution of resource allocation and changes in construction progress in real time. During the resource allocation process, summarize the identified requirements and prioritize them based on their impact on construction progress, quality, and cost. When the deviation exceeds the limit, the resource reconfiguration process is triggered, which can dynamically adjust resource allocation according to actual conditions and effectively improve the utilization rate of construction resources.

[0024] The establishment of a power construction resource sharing platform specifically includes the following: Establish a real-time communication and collaboration platform between construction team members, between different construction links, and with external partners to share construction information in real time; Based on the geographic information system, a visual collaborative map is constructed to mark the personnel distribution, equipment location, and material storage point information of each construction site in real time. Personnel from all parties can obtain detailed resource information and construction progress by clicking on the markers on the map; Improve communication efficiency during the construction process, reduce resource waste and construction delays caused by poor information flow, and optimize the overall construction process.

[0025] Step five also includes sending the generated resource allocation decision to the corresponding execution module, establishing a feedback mechanism, obtaining real-time feedback information during the resource allocation execution process, setting clear monitoring points and feedback channels in each execution link, and obtaining real-time feedback information during the resource allocation execution, so as to ensure that the feedback information is in place on time, the allocation is smooth, and there are no abnormal conditions. When an abnormal situation occurs, an early warning reminder signal is generated for real-time dynamic viewing.

[0026] This intelligent power construction resource allocation method, through the analysis of the characteristics of power construction projects, the study of historical data and the clarification of engineering requirements, comprehensively considers multiple factors, pre-sets the construction and maintenance progress deviation threshold, measures the allowable deviation range between the actual construction and maintenance progress and the twin predicted progress, and triggers the resource reconfiguration process when the deviation exceeds the limit. It can dynamically adjust resource allocation according to actual conditions, effectively improve the utilization rate of construction resources, resource allocation execution and feedback mechanism, continuously adjust resource allocation strategy, realize continuous optimization of resource allocation, improve the overall efficiency of power construction, ensure sufficient sensitivity to construction progress deviation, thereby achieving reasonable allocation of construction resources and precise control of construction period.

[0027] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0028] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by those skilled in the art according to actual conditions. In the two embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interface, and the indirect coupling or communication connection of devices or modules may be electrical, mechanical or other forms. The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for allocating resources for intelligent power construction, characterized in that: The following steps are involved: Step 1: Establish a data repository related to power construction, obtain historical data on the power construction process from the repository, generate a list of construction time and construction volume data, and obtain demand information for the power construction process based on the construction data list; Step 2: During resource allocation, real-time data from the power construction process is obtained. Based on a deep learning neural network, a construction prediction model for construction progress prediction is established. The real-time data is fed into the construction prediction model to output the model-predicted progress value. Based on the power construction demand and time requirements, a power construction maintenance progress deviation threshold is pre-set to generate the deviation range between the actual construction maintenance progress and the twin predicted progress during the power construction process. Step 3: Establish a power construction resource sharing platform through mobile terminals based on IoT monitoring devices to collect real-time construction and maintenance progress information, including completed workload, working hours, and personnel usage, and generate real-time construction and maintenance actual progress data; Step 4: Compare the real-time collected construction and maintenance progress data with the progress value predicted by the twin prediction model to generate a comparative analysis value. Based on the comparative analysis value, make resource allocation judgments and trigger the resource reconfiguration process. Based on the demand information of the power construction link, dynamically adjust resources and obtain dynamic adjustment information. Step 5: Obtain the dynamic control information and send it to the control platform to generate real-time allocation instructions, and send the dynamic control information to the resource management end for resource control execution.

2. The intelligent power construction resource configuration method according to claim 1, characterized in that: The following steps are also included: in step 1, a data repository for power construction related data is established, the repository stores records through a control module, and before data storage, the relevant data is cleaned and pre-processed on a unified data platform to ensure the accuracy and consistency of the data; Establish a classification of various resources required for power construction, including human, material, and financial resources, and establish detailed attribute characteristics for each type of resource.

3. The intelligent power construction resource configuration method according to claim 1, characterized in that: The demand information for power construction is as follows: S100. Obtain historical data from the repository regarding power construction, recording basic information about each power construction project, including the planned start and end times of the construction project; construction progress: recording actual construction progress, including actual start and end times, and completed workload; and recording information about equipment used during construction, including construction personnel information. S101. Group historical data by construction task, and calculate the cumulative construction volume and construction time of each task to obtain a construction data list, and sort them by construction start time; S102. Analyze and sort the data list, mark the demand information of each construction task link, including but not limited to specific requirements in terms of manpower, material resources, equipment, and technology, and obtain the demand information of the power construction link.

4. The intelligent power construction resource configuration method according to claim 1, characterized in that: The construction prediction model for construction progress prediction is established. The specific steps are as follows: S200, obtaining the demand information of the power construction link, using the number of construction workers, completed construction volume, total construction volume, expected construction time, and actual construction time data as the sample data set of the construction prediction model, checking the data for missing values, outliers, and duplicate data, identifying, correcting, deleting, and standardizing the data to have a similar scale; S201: The number of construction workers, the amount of construction completed, and the expected construction time are used as inputs of the construction prediction model. The output data is analyzed by the processing layer, and the actual predicted construction time is used as output. S202, the specific process of data analysis is as follows: N is assumed to represent the number of construction workers, C represents the amount of construction completed, Represents the expected construction time, represents the actual predicted construction time, ， Where, and is the set adjustment coefficient, is the actual number of construction workers, The total project volume.

5. The intelligent power construction resource configuration method according to claim 1, characterized in that: Pre-set power construction and maintenance progress deviation thresholds, including the following: S300, obtaining demand information for power construction links, selecting some similar power construction project demand information for analyzing the power construction maintenance progress; S301. Based on the demand information of some similar power construction projects, the time range and fluctuation of each power construction project are counted, and the average value and standard deviation statistics are calculated to obtain the construction progress time of each power construction project. The deviation value is generated by performing comparative analysis based on the predicted construction time. S301. Obtain the deviation value of each power construction project, sort them according to the length of time, obtain the time deviation range, and set the initial threshold within this range: Preset is the actual completion time of task I, is the planned completion time of task I, is the deviation value of the I-th task, I={1,2,3,…,N}; ， The thresholds are: The maximum value of MAX, The minimum value of MIN, get the threshold .

6. The intelligent power construction resource configuration method according to claim 1, characterized in that: And trigger the resource reconfiguration process, the specific operations are as follows: S300: When the deviation between the predicted construction time and the actual scheduled construction time exceeds a set threshold, the resource reconfiguration process is triggered, and the required resource types, quantities, and deployment plans are recalculated based on the deviation and the current resource status; S300, when the deviation threshold is greater than y+x, human resources are dynamically adjusted in real time; when the deviation threshold is greater than 2y, human resources and equipment resources are increased and regulated; S300. When the actual progress is less than the biased threshold, the input of some resources will be appropriately reduced. During the resource reallocation process, the execution of resource allocation and changes in construction progress will be monitored in real time. During the resource allocation process, the identified needs will be summarized and prioritized according to the degree of impact on construction progress, quality and cost.

7. The intelligent power construction resource configuration method according to claim 1, characterized in that: The establishment of a power construction resource sharing platform specifically includes the following: Establish a real-time communication and collaboration platform between construction team members, between different construction links, and with external partners to share construction information in real time; Based on the geographic information system, a visual collaborative map is constructed to mark the personnel distribution, equipment location, and material storage point information of each construction site in real time. People from all parties can obtain detailed resource information and construction progress by clicking on the marks on the map.

8. The intelligent power construction resource configuration method according to claim 1, characterized in that: Step five also includes sending the generated resource allocation decision to the corresponding execution module, establishing a feedback mechanism, obtaining real-time feedback information during the resource allocation execution process, setting clear monitoring points and feedback channels in each execution link, and obtaining real-time feedback information during the resource allocation execution, so as to ensure that the feedback information is in place on time, the allocation is smooth, and there are no abnormal conditions. When an abnormal situation occurs, an early warning reminder signal is generated for real-time dynamic viewing.

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