Electric power engineering construction management method and system based on digital twinning

Abstract

The invention provides an electric power engineering construction management method and system based on digital twinning, and relates to the technical field of construction management.The method comprises the steps that when an electric power engineering is transferred to a new scene, reusability scores of all rules in an inherent construction management rule base in the new scene are quantitatively evaluated; removing the rules of which the reusability scores are lower than a preset threshold value, and determining a management rule missing domain in the new scene based on the function distribution of the remaining rules; for the management rule missing domain, generating a supplementary management rule adaptive to the new scene, and updating the inherent construction management rule base; and on the basis of the updated inherent construction management rule base, performing construction management on the new scene through a digital twin model. The method solves the problems that a fixed rule base is poor in adaptability during scene conversion and low in efficiency depending on manual adjustment, improves the real-time decision-making capability and scene adaptation effectiveness of the digital twinborn model in dynamic electric power engineering construction management, and remarkably improves the electric power work construction management effect.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management, and in particular to a power engineering construction management method and system based on digital twins. Background Art

[0002] Due to the vast geographical reach, complex and changing environments, and the periodic transitions in tasks associated with power projects, construction scenarios frequently shift. Currently, digital twin technology has been widely adopted in power project construction management practices. Its core relies on a pre-defined, fixed, and inherent construction management rule base. This rule base contains a large number of management rules covering safety, quality, schedule, resource allocation, and other dimensions, driving the digital twin model to manage the multi-dimensional construction process.

[0003] However, this management model, based on a fixed rule base, has significant limitations when adapting to changing scenarios. Whenever a power project transitions to a new, specific scenario with different environmental characteristics or construction requirements, some pre-defined rules in the rule base often fail to directly adapt to the actual needs of the new scenario. These inappropriate rules may stem from factors such as differences in geological conditions, climate characteristics, equipment limitations, and changes in safety risks.

[0004] To address this problem, existing methods lack an effective mechanism for evaluating rule adaptability. Construction managers rely solely on manual experience, reviewing the rule base one by one to identify which rules are invalid or inapplicable in new scenarios and, based on this, determine which new management rules need to be added. This process is not only tedious and time-consuming, but also highly dependent on individual experience, subjectivity, inefficiency, and the tendency to miss risk points. This manually-led rule adaptation and addition process lags significantly behind the actual needs of construction transitions, significantly restricting the timeliness of construction management and decision-making efficiency, and hindering the full potential of digital twin models to rapidly respond to new scenarios.

[0005] Therefore, there is an urgent need for a method that can automatically and intelligently evaluate the applicability of rules in new scenarios and dynamically update the rule base accordingly, so as to solve the pain points of poor adaptability of fixed rule bases during scenario conversion and low efficiency of manual adjustment, improve the real-time decision-making ability and scenario adaptation effectiveness of digital twin models in dynamic power engineering construction management, and improve the construction management effect of power work. Summary of the Invention

[0006] One of the purposes of the present invention is to provide a power engineering construction management method based on digital twins to solve the problems in the background technology.

[0007] An embodiment of the present invention provides a digital twin-based power engineering construction management method, comprising: When a power project is transferred to a new scenario, the reusability score of each rule in the inherent construction management rule base is quantitatively evaluated in the new scenario; Eliminate rules whose reusability scores are lower than a preset first threshold, and determine the missing domains of management rules in the new scenario based on the functional distribution of the remaining rules; For areas where management rules are missing, generate supplementary management rules that adapt to new scenarios and update the existing construction management rule library; Based on the updated inherent construction management rule base, construction management is implemented for new scenarios through the digital twin model.

[0008] Optionally, the quantitative evaluation of the reusability score of each rule in the inherent construction management rule base in a new scenario includes: Real-time perception of dynamic feature sets of new scenarios through digital twin models; For each rule in the inherent construction management rule base, the first similarity between the dynamic feature set and the adaptation scene feature set of the rule, as well as the second similarity between the dynamic feature set and the historical transition effective scene feature set of the rule are calculated, and the weighted calculation result of the first similarity and the second similarity is used as the reusability score of the rule.

[0009] Optionally, determining the management rule missing domain in the new scenario based on the functional distribution of the remaining rules includes: Based on the dynamic feature set, the new scenario is matched with the corresponding preset management requirement function distribution; Perform a difference analysis between the functional distribution of the remaining rules and the functional distribution of management requirements corresponding to the new scenario to identify functional coverage gaps and use them as missing domains for management rules.

[0010] Optionally, generating supplementary management rules adapted to new scenarios for the management rule-missing domain includes: Based on the dynamic feature set, multiple preset candidate management rules are matched to the new scenario; For each candidate management rule, the adaptability of the candidate management rule in the new scenario is simulated and verified through the digital twin model. When the first verification result meets the preset indicator threshold, the candidate management rule is used as a supplementary management rule.

[0011] Optionally, implementing construction management for the new scenario through the digital twin model based on the updated inherent construction management rule base includes: Integrate the updated inherent construction management rule base to generate an executable construction management engine; The construction management module is deployed in the logical decision-making layer of the digital twin model, and construction management instructions are output to the physical layer equipment in real time.

[0012] Optionally, after implementing construction management for the new scenario through the digital twin model based on the updated inherent construction management rule base, the method further includes: When implementing the current rules in the updated inherent construction management rule base in a new scenario, if the construction party in the new scenario refuses to execute the management instructions corresponding to the current rules, obtain the construction party's management objection; quantitatively evaluate the adoptability score of the management objection in the new scenario; When the adoptability score is higher than the preset second threshold, the target rules are optimized based on management objections, and construction management is re-implemented for the new scenario based on the optimized target rules; Otherwise, the digital twin model can be used to assist the construction party in accepting the current rules to eliminate management objections.

[0013] Optionally, the quantitative evaluation of the adoptability score of the management objection in the new scenario includes: simulating and verifying the adoption effect of the management objection in the new scenario waiting for the implementation of the current rules through a digital twin model, and taking the weighted calculation result of the second verification result under different preset scoring indicators as the adoptability score.

[0014] Optionally, the optimizing the target rule based on the management objection includes: The target rules are optimized based on the preset rule optimization template corresponding to the management objection and the target rules.

[0015] Optionally, the digital twin model is used to assist the construction party in accepting the current rules to eliminate management objections, including: Based on management objections, identify multiple cognitive barriers that affect the construction party's acceptance of the current rules and their respective first-level impact levels; For each cognitive obstacle, match the preset information display rules and obstacle elimination efficiency value corresponding to the cognitive obstacle; the obstacle elimination efficiency value refers to the quantitative indicator of the ability of the digital twin model to successfully eliminate the cognitive obstacle when displaying the corresponding information to the construction party according to the information display rules; With the goal of being closest to the planned conditions, the execution order of the information display rules corresponding to each cognitive impairment is optimized; Based on the execution order, the digital twin model is controlled to sequentially execute the information display rules corresponding to each cognitive obstacle to the construction party; The planning conditions include: The first balance indicator and the second balance indicator of each information display rule during execution meet the preset balance requirements; among them, for each information display rule, the obstacle elimination efficiency value of the information display rule is used as the first balance indicator; when the digital twin model executes the information display rule, the probability of inducing new cognitive impairment by interacting with other information display rules executed in the sequence before and after it, the second impact degree of the new cognitive impairment, and the weighted calculation result of the first impact degree of the cognitive impairment corresponding to the information display rule are used as the second balance indicator.

[0016] An embodiment of the present invention provides a digital twin-based power engineering construction management system, comprising: A quantitative evaluation module is used to quantitatively evaluate the reusability of each rule in the inherent construction management rule base in a new scenario when the power project is transferred to a new scenario; A missing domain determination module is used to eliminate rules whose reusability scores are lower than a preset first threshold, and determine the missing domain of management rules in the new scenario based on the functional distribution of the remaining rules; The rule generation module is used to generate supplementary management rules that adapt to new scenarios for areas where management rules are missing, and to update the existing construction management rule library; The construction management module is used to implement construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base.

[0017] The present invention has achieved the following beneficial effects: When the power project is transferred to a new scenario, the present invention first quantitatively evaluates the reusability of each rule in the inherent construction management rule base in the new scenario, and eliminates the rules with scores below the threshold; then determines the missing domain of management rules for the new scenario based on the functional distribution of the remaining rules; then generates supplementary management rules adapted to the missing domain to update the rule base; finally, based on the updated rule base, implements the construction management of the new scenario through the digital twin model. This achieves the ability to automatically and intelligently evaluate the applicability of rules in new scenarios, and dynamically updates the rule base accordingly, solving the pain points of the fixed rule base's poor adaptability during scenario conversion and the low efficiency of manual adjustment, improving the real-time decision-making ability and scenario adaptation effectiveness of the digital twin model in dynamic power project construction management, and significantly improving the effectiveness of power construction management.

[0018] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0019] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a flow chart of a method for power engineering construction management based on digital twins in an embodiment of the present invention; Figure 2 This is another flow chart of a method for managing electric power engineering construction based on digital twins in an embodiment of the present invention; Figure 3 This is a workflow diagram of a power engineering construction management system based on digital twins in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0022] Example 1: like Figure 1 As shown, an embodiment of the present invention provides a power engineering construction management method based on digital twins, including: S1. When a power project is transferred to a new scenario, the reusability score of each rule in the existing construction management rule base is quantitatively evaluated in the new scenario. The reusability score is a score that evaluates the reusability of the rule in the new scenario, which represents the degree of reusability of the rule in the new scenario. S1 includes: S11. Real-time perception of the dynamic feature set of the new scene through the digital twin model. A sensor network deployed in the new scene collects physical entity information in real time (supporting manual input), and a digital twin model of the new scene is created based on this information. The dynamic feature set should include at least: environmental characteristics (temperature and humidity, wind speed, geological conditions, spatial topology, etc.), construction requirements (safety standards, process specifications, progress milestones, etc.), and on-site equipment conditions (construction machinery model, positioning terminal type, monitoring equipment distribution, etc.).

[0023] S12. For each rule in the inherent construction management rule base, calculate the first similarity between the dynamic feature set and the adaptation scene feature set of the rule, as well as the second similarity between the dynamic feature set and the historical transition effective scene feature set of the rule, and use the weighted calculation result of the first similarity and the second similarity as the reusability score of the rule. Collect the construction scenes that the rule has been adapted to in history in advance, analyze the environmental characteristics, construction requirements, and on-site equipment conditions of the construction scenes, and construct the adaptation scene feature set. Similarly, collect the construction scenes that have taken effect after the transition of the rule in history in advance, analyze the environmental characteristics and other features of the scenes, and construct the historical transition effective scene feature set. When calculating the first similarity and the second similarity, the cosine similarity calculation method can be used. The higher the first similarity or the second similarity, the higher the degree of reusability of the rule in the construction scene. Therefore, the two are positively correlated with the reusability score. Pre-set the weights of the first and second similarities as needed. For example, if you want the system to place more weight on the first similarity when evaluating the reusability of rules in new scenarios, then set the weight of the first similarity higher than the second similarity. Based on the set weights, perform a weighted calculation on the first and second similarities to obtain a reusability score. The weighted calculation formula is: ,in, Score reusability, is the first similarity, is the weight corresponding to the first similarity, is the second similarity, is the weight corresponding to the second similarity.

[0024] S2. Eliminate rules whose reusability scores fall below a preset first threshold and, based on the functional distribution of the remaining rules, determine the missing domains of management rules for the new scenario. The first threshold is pre-set as needed. For example, if the system is expected to increase the stringency of rule elimination, the first threshold can be set higher. Functional distribution refers to the management functions of the remaining rules after the relevant rules in the existing construction management rule base have been eliminated. Missing domains of management rules refer to management functional requirements in the new scenario that are not covered by this functional distribution.

[0025] S3. For areas where management rules are missing, generate supplementary management rules that adapt to new scenarios and update the inherent construction management rule library.

[0026] S4: Implement construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base. S4 includes: S41. Integrate the updated inherent construction management rule base to generate an executable construction management engine.

[0027] S42. Deploy the construction management module in the logical decision layer of the digital twin model to output construction management instructions to the physical layer devices in real time. The logical decision layer of the digital twin model is used to manage and interact with the new scene. It can output construction management instructions to the physical layer devices within the new scene, thereby performing construction management for the new scene.

[0028] When a power project is transferred to a new scenario, the embodiment of the present invention first quantitatively evaluates the reusability of each rule in the inherent construction management rule base in the new scenario, and eliminates rules with scores below a threshold; then, based on the functional distribution of the remaining rules, determines the missing domain of management rules for the new scenario; then generates supplementary management rules adapted to the missing domain to update the rule base; and finally, based on the updated rule base, implements construction management of the new scenario through a digital twin model. This enables automated and intelligent evaluation of the applicability of rules in new scenarios, and dynamically updates the rule base accordingly, resolving pain points such as poor adaptability of fixed rule bases during scenario conversion and low efficiency due to reliance on manual adjustments. It enhances the real-time decision-making capability and scenario adaptation effectiveness of digital twin models in dynamic power project construction management, significantly improving the effectiveness of power construction management.

[0029] The adaptation scene feature set and the historical transition effective scene feature set are introduced, and the similarity between the two is comprehensively quantitatively evaluated using the dynamic feature set of the new scene to improve the accuracy of the quantitative evaluation of the reusability score and its accuracy in rule screening.

[0030] Example 2: On the basis of Example 1, in this embodiment of the present invention, S2 includes: S21. Based on the dynamic feature set, the new scenario is matched with a preset management requirement function distribution. Preliminary analysis is performed on all construction management function requirements required for each construction scenario with different dynamic feature sets to form a matching management requirement function distribution, which can also be set as needed.

[0031] S22. Perform a differential analysis on the functional distribution of the remaining rules and the functional distribution of the management requirements corresponding to the new scenario to identify functional coverage gaps, which are then used as missing domains for management rules. Performing a differential analysis on the functional distribution of the remaining rules and the functional distribution of the management requirements corresponding to the new scenario will reveal the management functional requirements in the new scenario that are not covered by the functional distribution, i.e., functional coverage gaps, which are used as missing domains for management rules.

[0032] The embodiments of the present invention greatly improve the accuracy, comprehensiveness and efficiency of determining the management rule missing domain.

[0033] Example 3: On the basis of Example 1, in this embodiment of the present invention, S3 includes: S31. Based on the dynamic feature set, the new scene is matched with a plurality of preset candidate management rules. The construction scenes with different dynamic feature sets are pre-analyzed for their respective applicable multiple construction management rules to form a plurality of matching candidate management rules, which can also be set as needed.

[0034] S32. For each candidate management rule, simulate and verify its adaptability in the new scenario using the digital twin model. When the first verification result meets a preset indicator threshold, the candidate management rule is adopted as a supplementary management rule. The indicator threshold can be set in advance as needed. For example, if the system is expected to strictly control adaptability verification, the indicator threshold can be set higher. Using the sandbox principle, simulate and verify the adaptability of the candidate management rule in the new scenario in the digital twin model to obtain a first verification result. For example, a sandbox environment for the new scenario is constructed in the digital twin model, and the candidate management rule is loaded for virtual simulation. Verification results for various verification indicators, such as security, efficiency, and stability, are output. (The analysis method for the results of different verification indicators can be pre-set as needed. For example, for the security verification indicator, the full score is set to 10 points. For each security risk encountered during the virtual simulation, 1 point is deducted. After the virtual simulation, the deduction result is used as the security verification indicator result.) When the first verification result meets the preset indicator threshold, it indicates that the corresponding candidate management rule can be implemented in the new scenario as a supplementary management rule.

[0035] The embodiments of the present invention significantly improve the effectiveness of generating supplementary management rules and enhance the applicability of the system.

[0036] Example 4: Power engineering construction is constrained by factors such as high environmental complexity, highly variable working conditions, and the objective limitations of construction personnel experience. When a digital twin system, based on an established construction management rule base, outputs management instructions for a new scenario, a key pain point arises: on-site construction personnel may object to the system instructions and refuse to execute them. Such objections often stem from the unique characteristics of the new scenario (such as unforeseen risks), forcing management personnel to intervene and determine the legitimacy of the objection.

[0037] This manual arbitration process requires complex procedures such as objection review, rule applicability reassessment, and decision-making. As a result, the construction progress is stalled while waiting for the ruling results. A large amount of time that should be used for construction is consumed by objection handling. The closed-loop decision-making ability of the digital twin model is artificially interrupted, reducing the level of intelligent construction management.

[0038] For this reason, based on Example 1, Figure 2 As shown, based on Example 1, in this embodiment of the present invention, after the step S4 of implementing construction management for the new scenario through the digital twin model based on the updated inherent construction management rule base, the method further includes: S5. When the current rules in the updated inherent construction management rule base are applied to the new scenario, if the construction party in the new scenario refuses to execute the management instructions corresponding to the current rules, obtain the construction party's management objection. The management objection refers to the construction party's opinion on the construction management, etc.

[0039] S6: Quantitatively assess the admissibility of management objections in new scenarios. S6 includes: S61. Use the digital twin model to simulate and verify the adoption effect of the management objection in a new scenario awaiting implementation of the current rule. The weighted calculation result of the second verification result under different preset scoring indicators is used as the adoptability score. Similarly, the sandbox principle can be used to simulate and verify the adoption effect of the management objection in a new scenario awaiting implementation of the current rule in the digital twin model to obtain a second verification result. For example, a sandbox environment is constructed in the digital twin model for the new scenario awaiting implementation of the current rule, and the adoption of the management objection is loaded for virtual simulation. The results of scoring indicators such as safety deviation, construction delay rate, and cost overrun risk value are output. (The analysis method for the results of different scoring indicators can be pre-set as needed. For example, for the construction delay rate indicator, the actual completion time of the construction process is recorded in the virtual simulation, and the estimated completion time of directly implementing the current rule is obtained. If the actual completion time is longer than the estimated completion time, the difference between the actual completion time and the estimated completion time is calculated as the ratio of the difference between the actual completion time and the estimated completion time.) Based on the pre-set weights of the different scoring indicators, the corresponding scores are weighted and calculated to obtain the adoptability score. The weighted calculation formula is: ,in, Score the acceptability. For the The weight of the scoring indicators, The second verification result is Ratings under each rating indicator: is the total number of scoring indicators. Scores for different indicators can be numerically constrained as needed, for example, all expressed as percentages, all constrained to be between 0 and 1, etc.

[0040] S7. When the adoptability score is higher than the preset second threshold, the target rule is optimized based on the management objection, and construction management is re-implemented for the new scenario based on the optimized target rule. The second threshold is set in advance as needed. For example, if the system is expected to adopt management objections with a higher degree of rigor, a higher second threshold is set. When the adoptability score is higher than the second threshold, it means that the management objection can be adopted, and the target rule is optimized based on it, and then re-implemented in real time after optimization. Then S7 includes: S71. Optimize the target rules based on the preset rule optimization template corresponding to the management objections and the target rules. Collect a large number of management objections and construction management rules in advance, pair the management objections and construction management rules in pairs, and obtain multiple pairing groups. For each pairing group, experts analyze how to optimize the construction management rules when facing the management objections and construction management rules in the pairing group, form an optimization strategy, and based on the optimization strategy, make a rule optimization template corresponding to the management objections and construction management rules in the pairing group. Therefore, when optimizing the target rules, directly determine the corresponding preset rule optimization template, and perform corresponding optimization processing against the template. The forms of optimization include at least: adding new rules, eliminating rules, etc. For example: if the management objection points out that there are unforeseen risks in the new scenario, then during optimization, the rules for monitoring the risks will be added to the target rules.

[0041] S8. Otherwise, the digital twin model is used to assist the construction party in accepting the current rules to eliminate management objections. S8 includes: S81. Based on management objections, determine the multiple cognitive barriers that affect the construction party's acceptance of the current rules and their respective first impact levels. Cognitive barriers refer to the psychological resistance formed by the construction party due to factors such as deviations in rule understanding, misplaced risk perception, or limited experience and cognition, which causes the construction party to refuse to execute management instructions and directly hinders its acceptance of the current rules. For example: the current rules are set for a potential risk in a new scenario, and the construction party does not understand the severity of the potential risk, which forms a cognitive barrier. A degree table containing the first impact levels of different cognitive barriers is set in advance according to the impact levels of different cognitive barriers. When determining the first impact level, the table is directly queried to obtain it.

[0042] S82. For each cognitive barrier, match the preset information display rule corresponding to the cognitive barrier and its barrier elimination effectiveness value; wherein the barrier elimination effectiveness value is a quantitative indicator of the ability of the digital twin model to successfully eliminate the cognitive barrier when the corresponding information is displayed to the construction party according to the information display rule. Methods for eliminating different cognitive barriers to a certain extent through information display using the digital twin model are analyzed in advance. For example, if the cognitive barrier is that the construction party does not understand a potential risk in a new scenario, the digital twin model can be used to display the location, type, and possible construction accidents of the potential risk to the construction party. The workflow for monitoring the potential risk based on the current rules can also be displayed. Based on this method, information display rules corresponding to different cognitive barriers are set, and a rule table containing the information display rules corresponding to different cognitive barriers is further set. Based on the degree to which the corresponding cognitive barriers are eliminated by this method, an effectiveness value table containing the barrier elimination effectiveness values corresponding to the different information display rules is set. When matching the information display rules and their barrier elimination effectiveness values, the information display rule is determined by querying the rule table for the cognitive barrier, and the barrier elimination effectiveness value is determined by querying the effectiveness value table for the determined information display rule. The obstacle removal efficiency value can be numerically constrained as needed, for example: expressed in the form of a percentage, and the constraint size is between 0 and 1.

[0043] S83. With the goal of being closest to the planned conditions, optimize the execution order of the information display rules corresponding to each cognitive impairment.

[0044] S84. Based on the execution order, control the digital twin model to sequentially execute the information display rules corresponding to each cognitive barrier to the construction party. The planning conditions include: the first balance index and the second balance index of each information display rule meet the preset balance requirements during execution; wherein, for each information display rule, the barrier elimination efficiency value of the information display rule is used as the first balance index; and the weighted calculation result of the probability of inducing a new cognitive barrier when the digital twin model executes the information display rule and interacts with other information display rules executed before and after it, the second impact of the new cognitive barrier, and the first impact of the cognitive barrier corresponding to the information display rule is used as the second balance index. Experimental analysis is conducted in advance to determine if the interaction of multiple different information display rules, when executed consecutively by the digital twin model, can induce new cognitive barriers to the construction party. For example, two rules, one for safety alert management and one for progress reminder management, may cause confusion among the construction party regarding the priority of safety and efficiency, thus forming a new cognitive barrier. Based on this, an obstacle table is established containing the new cognitive barriers corresponding to different information display rules. Next, experts analyze the probability of inducing new cognitive barriers in this situation and establish a probability table containing the corresponding probabilities of different new cognitive barriers. When determining the probability of new cognitive disorders caused by the interaction of different information display rules, the probability table and the probability table are queried in sequence to obtain the result. When determining the second degree of influence, the above degree table is queried to obtain the result. The range of the order of precedence and follow-up can be set in advance as needed. For example, the more deeply the system is expected to consider the factor of the interaction of information display rules executed continuously within a certain period of time to induce new cognitive disorders, the larger the range of the order of precedence and follow-up will be set, such as setting it to the order range of the other information display rules executed before and the other information display rules executed after. Based on the pre-set weights, the probability of inducing new cognitive disorders, the second degree of influence of new cognitive disorders, and the first degree of influence of the information display rule corresponding to the cognitive disorder are weightedly calculated to obtain the second balance index. The weighted calculation formula is: ,in, is the second balance indicator, Induced The probability of a new cognitive impairment is the weight corresponding to the probability of occurrence, To induce the The second level of impact of a new cognitive impairment, is the weight corresponding to the second degree of influence, is the total number of new cognitive impairments induced, is the first level of impact, is the weight corresponding to the first degree of influence. The probability of occurrence, the first degree of influence, and the second degree of influence can be numerically constrained as needed, for example: they are all expressed in the form of percentages, and the sizes are all constrained between 0 and 1. The first balance index and the second balance index are set in this way, so that the first balance index represents the comprehensive positive effect level when the information display rule is executed, and the second balance index represents the comprehensive negative effect level when the information display rule is executed. The balance requirement is set in advance as needed. For example: if the system is expected to improve the comprehensive positive effect level of each execution of the information display rule as much as possible, the balance requirement is set to a preset value where the difference between the first balance index and the second balance index is larger.

[0045] In this embodiment of the present invention, when a construction party in a new scenario refuses to execute the management instructions corresponding to the current rules, the system obtains management objections and quantitatively evaluates their adoptability scores. If the score exceeds a preset threshold, the management objection is adopted to optimize the target rules and re-implement construction management based on the optimized rules. Otherwise, the digital twin model outputs auxiliary strategies to the construction party to resolve the management objection. This process does not require management personnel to intervene in arbitration, and the system can independently achieve rapid response, significantly shortening the objection handling time, minimizing construction downtime, and avoiding interruptions in the digital twin decision-making closed loop, thereby improving the intelligent level of power project construction management.

[0046] A preset rule optimization template corresponding to management objections and target rules is introduced. The target rules are optimized using this template, which improves the accuracy and efficiency of target rule optimization.

[0047] When using a digital twin model to assist construction parties in accepting current rules and resolving management objections, the system precisely analyzes multiple cognitive barriers to acceptance and their respective first-order impacts. It then matches the most appropriate information display rule and its barrier-removal effectiveness value for each barrier. The barrier-removal effectiveness value is used as the first balance indicator, while the second balance indicator is a weighted calculation of the probability of new cognitive barriers induced by the interaction between the digital twin model's execution of an information display rule and other information display rules executed in its preceding and following sequence, the second-order impact of the new cognitive barrier, and the first-order impact of the information display rule corresponding to the cognitive barrier. During execution sequence planning, the system optimizes the execution sequence by ensuring that both the first and second balance indicators of each information display rule meet the preset balance requirements. This improves the comprehensiveness, accuracy, and efficiency of execution sequence planning, significantly enhancing the effectiveness of assisting construction parties in accepting the current rules and resolving management objections when the digital twin model sequentially executes each information display rule according to the planned execution sequence. This further shortens objection handling time and reduces construction downtime.

[0048] In addition, it is particularly important to note that considering the interaction of different information display rules to induce new cognitive obstacles greatly improves the effectiveness of the system in providing assistance when the construction party encounters multiple cognitive obstacles, improves the applicability of the system in this special scenario, and further improves the level of intelligence in power engineering construction management.

[0049] Example 5: like Figure 3 As shown, an embodiment of the present invention provides a power engineering construction management system based on digital twins, including: A quantitative evaluation module is used to quantitatively evaluate the reusability of each rule in the inherent construction management rule base in a new scenario when the power project is transferred to a new scenario; A missing domain determination module is used to eliminate rules whose reusability scores are lower than a preset first threshold, and determine the missing domain of management rules in the new scenario based on the functional distribution of the remaining rules; The rule generation module is used to generate supplementary management rules that adapt to new scenarios for areas where management rules are missing, and to update the existing construction management rule library; The construction management module is used to implement construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base.

[0050] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A power engineering construction management method based on digital twins, characterized in that: include: When a power project is transferred to a new scenario, the reusability score of each rule in the inherent construction management rule base is quantitatively evaluated in the new scenario; Eliminate rules whose reusability scores are lower than a preset first threshold, and determine the missing domains of management rules in the new scenario based on the functional distribution of the remaining rules; For areas where management rules are missing, generate supplementary management rules that adapt to new scenarios and update the existing construction management rule library; Based on the updated inherent construction management rule base, construction management is implemented for new scenarios through the digital twin model.

2. The power engineering construction management method based on digital twins according to claim 1 is characterized in that: The quantitative evaluation of the reusability of each rule in the inherent construction management rule base in a new scenario includes: Real-time perception of dynamic feature sets of new scenarios through digital twin models; For each rule in the inherent construction management rule base, the first similarity between the dynamic feature set and the adaptation scene feature set of the rule, as well as the second similarity between the dynamic feature set and the historical transition effective scene feature set of the rule are calculated, and the weighted calculation result of the first similarity and the second similarity is used as the reusability score of the rule.

3. The power engineering construction management method based on digital twins according to claim 2 is characterized in that: The function distribution based on the remaining rules determines the missing domain of management rules in the new scenario, including: Based on the dynamic feature set, the new scenario is matched with the corresponding preset management requirement function distribution; Perform a difference analysis between the functional distribution of the remaining rules and the functional distribution of management requirements corresponding to the new scenario to identify functional coverage gaps and use them as missing domains for management rules.

4. The power engineering construction management method based on digital twins according to claim 2, characterized in that: The generation of supplementary management rules adapted to new scenarios for the domains where management rules are missing includes: Based on the dynamic feature set, multiple preset candidate management rules are matched to the new scenario; For each candidate management rule, the adaptability of the candidate management rule in the new scenario is simulated and verified through the digital twin model. When the first verification result meets the preset indicator threshold, the candidate management rule is used as a supplementary management rule.

5. The power engineering construction management method based on digital twins according to claim 1, characterized in that: The implementation of construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base includes: Integrate the updated inherent construction management rule base to generate an executable construction management engine; The construction management module is deployed in the logical decision-making layer of the digital twin model, and construction management instructions are output to the physical layer equipment in real time.

6. The power engineering construction management method based on digital twins according to claim 1, characterized in that: After implementing construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base, the following also applies: When implementing the current rules in the updated inherent construction management rule base in a new scenario, if the construction party in the new scenario refuses to execute the management instructions corresponding to the current rules, obtain the construction party's management objection; quantitatively evaluate the adoptability score of the management objection in the new scenario; When the adoptability score is higher than the preset second threshold, the target rules are optimized based on management objections, and construction management is re-implemented for the new scenario based on the optimized target rules; Otherwise, the digital twin model can be used to assist the construction party in accepting the current rules to eliminate management objections.

7. The power engineering construction management method based on digital twins according to claim 1, characterized in that: The quantitative evaluation of the adoptability score of the management objection in the new scenario includes: simulating and verifying the adoption effect of the management objection in the new scenario waiting for the implementation of the current rules through the digital twin model, and taking the weighted calculation result of the score of the second verification result under different preset scoring indicators as the adoptability score.

8. The power engineering construction management method based on digital twins according to claim 6, characterized in that: The optimization of target rules based on management objections includes: The target rules are optimized based on the preset rule optimization template corresponding to the management objection and the target rules.

9. The power engineering construction management method based on digital twins according to claim 1, characterized in that: The digital twin model is used to assist construction parties in accepting current rules and eliminating management objections, including: Based on management objections, identify multiple cognitive barriers that affect the construction party's acceptance of the current rules and their respective first-level impact levels; For each cognitive obstacle, match the preset information display rules and obstacle elimination efficiency value corresponding to the cognitive obstacle; the obstacle elimination efficiency value refers to the quantitative indicator of the ability of the digital twin model to successfully eliminate the cognitive obstacle when displaying the corresponding information to the construction party according to the information display rules; With the goal of being closest to the planned conditions, the execution order of the information display rules corresponding to each cognitive impairment is optimized; Based on the execution order, the digital twin model is controlled to sequentially execute the information display rules corresponding to each cognitive obstacle to the construction party; The planning conditions include: The first balance indicator and the second balance indicator of each information display rule during execution meet the preset balance requirements; among them, for each information display rule, the obstacle elimination efficiency value of the information display rule is used as the first balance indicator; when the digital twin model executes the information display rule, the probability of inducing new cognitive impairment by interacting with other information display rules executed in the sequence before and after it, the second impact degree of the new cognitive impairment, and the weighted calculation result of the first impact degree of the cognitive impairment corresponding to the information display rule are used as the second balance indicator.

10. A power engineering construction management system based on digital twins, characterized in that: include: A quantitative evaluation module is used to quantitatively evaluate the reusability of each rule in the inherent construction management rule base in a new scenario when the power project is transferred to a new scenario; A missing domain determination module is used to eliminate rules whose reusability scores are lower than a preset first threshold, and determine the missing domain of management rules in the new scenario based on the functional distribution of the remaining rules; The rule generation module is used to generate supplementary management rules that adapt to new scenarios for areas where management rules are missing, and to update the existing construction management rule library; The construction management module is used to implement construction management for new scenarios through the digital twin model based on the updated inherent construction management rule base.

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