A hydropower and electricity supply intelligent management method and system

Abstract

The present invention provides a method and system for intelligent management of hydropower and electric power supply, wherein the method includes: generating a digital model based on multimodal process information of hydropower and electric power supply; assisting an expert group in making decisions on optimization strategies for hydropower and electric power supply based on the digital model; and executing optimization strategies for hydropower and electric power supply. The method and system for intelligent management of hydropower and electric power supply of the present invention integrates various monitoring data of the hydropower and electric power supply process into a digital model, assists an expert group in making decisions on optimization strategies for hydropower and electric power supply based on the digital model, and finally executes the optimization strategies for hydropower and electric power supply, so that the expert group can fully grasp the real-time status of the power system during the optimization decision-making process, thereby improving the response speed and the accuracy of the decision. Secondly, the experts make optimization decisions with the assistance of the system, thereby improving the efficiency of optimization decisions.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of hydropower and electric power supply security, and in particular to an intelligent management method and system for hydropower and electric power supply security. Background Art

[0002] In the context of global energy transformation and sustainable development, the reliability and stability of power supply have become increasingly important. Hydropower power supply security involves comprehensive monitoring and management of the power system, and requires continuous optimization decisions to ensure that power supply can meet demand under various circumstances. However, the existing hydropower power supply security technology and management methods still have some shortcomings:

[0003] 1. Existing hydropower monitoring systems often use different technical platforms and standards, which makes it impossible to effectively integrate various types of data. This makes it difficult to fully grasp the real-time status of the hydropower system during the optimization decision-making process, affecting the response speed and decision-making accuracy.

[0004] 2. When experts make optimization decisions, they usually do it manually, lack intelligent auxiliary means, and the optimization decision-making efficiency is insufficient.

[0005] Therefore, a solution is urgently needed. Summary of the invention

[0006] One of the purposes of the present invention is to provide an intelligent management method for hydropower and electric power supply security, which integrates various monitoring data of the hydropower and electric power supply security process into a digital model, and based on the digital model, assists the expert group in deciding on the hydropower and electric power supply security optimization strategy, and finally implements the hydropower and electric power supply security optimization strategy, so that the expert group can fully grasp the real-time status of the power system during the optimization decision-making process, thereby improving the response speed and decision-making accuracy. Secondly, experts make optimization decisions with the assistance of the system, which improves the optimization decision-making efficiency.

[0007] An embodiment of the present invention provides a method for intelligent management of hydropower supply security, including:

[0008] Generate digital models based on multimodal process information for ensuring hydropower and electricity supply;

[0009] Based on the digital model, assist the expert group in making decisions on the optimization strategy for hydropower supply;

[0010] Implement optimization strategies for ensuring the supply of hydropower and electricity.

[0011] Optionally, the generating of a digital model based on multimodal process information for ensuring the supply of hydropower and electricity includes:

[0012] Generate evolution rules based on multimodal process information;

[0013] Based on the evolution rules, the initial model is evolved and configured to obtain a digital model;

[0014] The step of generating evolution rules based on multimodal process information includes:

[0015] Based on the generation time of each of the multiple process items in the multimodal process information, each process item is divided into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold;

[0016] Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain the qualitative label of each process item set;

[0017] Based on the calibration knowledge graph, each qualitative label is calibrated to obtain the calibration order of each qualitative label;

[0018] Generate evolution rules:

[0019] Based on the process demonstration template, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high.

[0020] When at least one qualitatively labeled process item set under the same i-th order is requested for demonstration:

[0021] If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order;

[0022] If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order;

[0023] If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order;

[0024] Among them, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

[0025] Optionally, the digital model-based, expert group-assisted decision-making on hydropower and electricity supply optimization strategy includes:

[0026] When the expert group holds an online meeting in the online meeting room, the digital model is pushed into the online meeting room;

[0027] Determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval;

[0028] Based on the standard decision logic library and meeting objectives, determine the standard decision logic;

[0029] Determine the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval;

[0030] When the real-time decision progress matches the first sub-logic in the standard decision logic, determining whether there is other second sub-logic after the first sub-logic in the standard decision logic;

[0031] When it is determined that the condition is yes, a logic sequence that meets the logic sequence condition is determined from the second sub-logic;

[0032] Generate expert conditions based on condition generation templates and logical sequences;

[0033] Based on the expert conditions, target experts are determined according to the personnel portraits of each expert in the expert group;

[0034] Providing focus reminders to target experts, and accordingly constraining the target experts’ use of digital models based on the use of constraint templates;

[0035] Receive input from the expert group on strategies to optimize the supply of hydropower and electricity;

[0036] The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the threshold value of the cumulative trigger value corresponding to the historical speeches of the experts that is greater than or equal to the sum of the trigger values;

[0037] The start time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the end time is the time when the decision on the optimization strategy for ensuring the supply of hydropower and electricity is completed;

[0038] Wherein, the logical sequence conditions include:

[0039] The sum of the importance of each second sub-logic in the logic sequence falls within a threshold range of the sum of importance;

[0040] The logic type of the first and second sub-logic in the logic sequence matches the standard logic type.

[0041] Optionally, after executing the hydropower and electricity supply optimization strategy, the method further includes:

[0042] Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results;

[0043] The evaluation results will be pushed to the expert group.

[0044] Optionally, after pushing the evaluation results to the expert group, the process further includes:

[0045] When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

[0046] An embodiment of the present invention provides a hydropower and electric power supply intelligent management system, comprising:

[0047] A generation module for generating a digital model based on multimodal process information for ensuring the supply of hydropower and electricity;

[0048] Auxiliary module, used to assist the expert group in making decisions on optimization strategies for hydropower supply based on digital models;

[0049] The first execution module is used to execute the optimization strategy for ensuring the supply of hydropower and electricity.

[0050] Optionally, the generation module generates a digital model based on multimodal process information for ensuring the supply of hydropower and electricity, including:

[0051] Generate evolution rules based on multimodal process information;

[0052] Based on the evolution rules, the initial model is evolved and configured to obtain a digital model;

[0053] The step of generating evolution rules based on multimodal process information includes:

[0054] Based on the generation time of each of the multiple process items in the multimodal process information, each process item is divided into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold;

[0055] Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain the qualitative label of each process item set;

[0056] Based on the calibration knowledge graph, each qualitative label is calibrated to obtain the calibration order of each qualitative label;

[0057] Generate evolution rules:

[0058] Based on the process demonstration template, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high.

[0059] When at least one qualitatively labeled process item set under the same i-th order is requested for demonstration:

[0060] If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order;

[0061] If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order;

[0062] If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order;

[0063] Among them, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

[0064] Optionally, the auxiliary module assists the expert group in making decisions on the optimization strategy for ensuring the supply of hydropower and electricity based on the digital model, including:

[0065] When the expert group holds an online meeting in the online meeting room, the digital model is pushed into the online meeting room;

[0066] Determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval;

[0067] Based on the standard decision logic library and meeting objectives, determine the standard decision logic;

[0068] Determine the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval;

[0069] When the real-time decision progress matches the first sub-logic in the standard decision logic, determining whether there is other second sub-logic after the first sub-logic in the standard decision logic;

[0070] When it is determined that the condition is yes, a logic sequence that meets the logic sequence condition is determined from the second sub-logic;

[0071] Generate expert conditions based on condition generation templates and logical sequences;

[0072] Based on the expert conditions, target experts are determined according to the personnel portraits of each expert in the expert group;

[0073] Providing focus reminders to target experts, and accordingly constraining the target experts’ use of digital models based on the use of constraint templates;

[0074] Receive input from the expert group on strategies to optimize the supply of hydropower and electricity;

[0075] The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the threshold value of the cumulative trigger value corresponding to the historical speeches of the experts that is greater than or equal to the sum of the trigger values;

[0076] The start time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the end time is the time when the decision on the optimization strategy for ensuring the supply of hydropower and electricity is completed;

[0077] Wherein, the logical sequence conditions include:

[0078] The sum of the importance of each second sub-logic in the logic sequence falls within a threshold range of the sum of importance;

[0079] The logic type of the first and second sub-logic in the logic sequence matches the standard logic type.

[0080] Optionally, after the first execution module executes the hydropower and electricity supply optimization strategy, it also includes:

[0081] Evaluation module for:

[0082] Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results;

[0083] The evaluation results will be pushed to the expert group.

[0084] Optionally, after the evaluation module pushes the evaluation result to the expert group, the following steps are further included:

[0085] The second execution module is used for:

[0086] When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

[0087] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or 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.

[0088] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] 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:

[0090] Figure 1 A schematic diagram of a method for intelligent management of hydropower supply security in an embodiment of the present invention;

[0091] Figure 2 It is a schematic diagram of an intelligent management system for ensuring the supply of hydropower and electric power in an embodiment of the present invention. DETAILED DESCRIPTION

[0092] The preferred embodiments of the present invention are described below in conjunction with 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.

[0093] The embodiment of the present invention provides a method for intelligent management of hydropower supply security. Figure 1 As shown, including:

[0094] S1. Generate a digital model based on multimodal process information for ensuring the supply of hydropower and electricity;

[0095] S2. Assist the expert group to make decisions on the optimization strategy for hydropower supply based on the digital model;

[0096] S3. Implement optimization strategies for ensuring the supply of hydropower and electricity.

[0097] The working principle and beneficial effects of the above technical solution are:

[0098] The multimodal process information includes at least: various monitoring data of the hydropower and electricity supply process, such as load data, equipment status, meteorological conditions, market demand, etc.; the digital model can visualize the multimodal process information; there are multiple experts in the expert group, who are responsible for making optimal decisions on the hydropower and electricity supply; based on the digital model, the expert group is assisted in deciding on the hydropower and electricity supply optimization strategy, and finally the hydropower and electricity supply optimization strategy is implemented.

[0099] This application integrates various monitoring data of the hydropower and electricity supply guarantee process into a digital model. Based on the digital model, it assists the expert group in deciding on the hydropower and electricity supply guarantee optimization strategy, and finally implements the hydropower and electricity supply guarantee optimization strategy, so that the expert group can fully grasp the real-time status of the power system during the optimization decision-making process, thereby improving the response speed and decision-making accuracy. Secondly, experts make optimization decisions with the assistance of the system, which improves the efficiency of optimization decision-making.

[0100] In one embodiment, the generating of the digital model based on the multimodal process information of ensuring the supply of hydropower and electricity includes:

[0101] S11, generating evolution rules based on multimodal process information;

[0102] In step S11, the evolution rule is a rule for the system to execute to evolve the initial model;

[0103] S12, based on the evolution rules, evolving the initial model to obtain a digital model;

[0104] In step S12, the initial model is a blank digital model that can display information. Under the constraints of the evolution rules, after the initial model is evolved and configured, it will continue to display corresponding information in sequence according to the evolution rules; the initial model after the evolution and configuration is used as the digital model;

[0105] Wherein, the S11, generating evolution rules based on multimodal process information, includes:

[0106] S111, based on the generation time of each of the multiple process items in the multimodal process information, dividing each process item into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold;

[0107] In step S111, the multimodal process information includes multiple process items, and the process item is a monitoring data, which has a generation time, that is, the time recorded when the data is generated; based on the generation time, each process item is divided into multiple process item sets; the threshold of the time difference can be 200 seconds; when it is ensured that the generation time difference between two process items in the same process item set is less than or equal to the threshold of the time difference, the process items in the same process item set can be generated continuously within a certain period of time, that is, the process items in the same process item set represent a short-term process stage;

[0108] S112. Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain a qualitative label of each process item set;

[0109] In step S112, there is qualitative knowledge corresponding to different process item sets in the qualitative knowledge graph, and the qualitative knowledge indicates how to characterize the process item set, and the qualitative label represents the qualitative result of the process item set; for example: if each process item in the process item set is that the increased electricity demand is for public facilities, the increased electricity demand is for public institutions, and the public facilities and public institutions are located in the same jurisdiction, then the corresponding qualitative knowledge is to characterize the process item set as geographically associated electricity demand, and the obtained qualitative label is the content label of the geographically associated electricity demand; for another example: if each process item in the process item set is that the supply guarantee failure situation is an abnormal power outage of the security system, and the supply guarantee failure situation is an abnormal power outage of a local data center, then the corresponding qualitative knowledge is to characterize the process item set as a supply guarantee failure situation, and the obtained qualitative label is the content label of the supply guarantee failure situation;

[0110] S113, based on the calibration knowledge graph, calibrate each qualitative label to obtain the calibration order of each qualitative label;

[0111] In step S113, the calibration knowledge graph contains calibration knowledge corresponding to different qualitative labels. The calibration knowledge indicates how to determine the calibration order of the qualitative labels. The calibration order is the order in which the process items in the process item set with qualitative labels need to be displayed to the experts in the expert group in order to assist the experts in making efficient optimization decisions. For example, each qualitative label is a content label of geographically associated electricity demand and a content label of a supply guarantee failure situation. The corresponding calibration knowledge is to calibrate the content label of the supply guarantee failure situation to a low order and the content label of the geographically associated electricity demand to a high order (the experts need to deal with the supply guarantee failure situation first and solve it in time, and then pay attention to the geographically associated electricity demand). The introduction of the qualitative knowledge graph and the calibration knowledge graph realizes rapid qualitative processing and calibration processing of the process item set, improves the work efficiency of the system, and indirectly improves the accuracy of the generation of evolution rules.

[0112] S114, generate evolution rules:

[0113] Rule 1: Based on the process demonstration template, demonstrate the process item sets of all qualitative labels under the same calibration order from low to high in sequence;

[0114] In rule 1, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high. For example, if there are 2 qualitative labels with calibration order 1 and 3 qualitative labels with calibration order 2, the process item sets of the qualitative labels with calibration order 1 are demonstrated first, and then the process item sets of the qualitative labels with calibration order 2 are demonstrated. The process demonstration template is a template for the system to demonstrate the process item set, which specifically includes: during the demonstration, the process items in the process item set are laid out according to the sub-template corresponding to the qualitative label of the process item set to which they belong, and a layout interface is generated. The initial model is configured to display the layout interface; the sub-template is, for example, each process item in the process item set is an abnormal power failure of the security system, and the supply failure is an abnormal power failure of the data center, then the sub-template is an interface template containing two equal-sized situation display boxes; when implementing rule one, the process item sets of all qualitative labels under the same calibration order can be demonstrated in order from low to high according to the calibration order, and the experts of the expert group can efficiently make optimization decisions on water and electricity supply according to the demonstration content, thereby improving the accuracy, suitability and rationality of digital model generation;

[0115] Rule 2: When at least one qualitatively labeled process item set under the same i-th order is requested for demonstration:

[0116] If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order;

[0117] If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order;

[0118] If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order;

[0119] Among them, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

[0120] In rule 2, the experts in the expert group can request to demonstrate at least one process item set of qualitative labels under the same i-th calibration order. When requesting, if i≤t1, it means that the content of the requested demonstration is in the front stage of preliminary demonstration to the experts in the expert group, and the experts in the expert group need to understand the whole situation of the front stage, then the process item sets of all qualitative labels under the same first i calibration order are demonstrated at the same time; if i≥t2, it means that the content of the requested demonstration is in the back stage of the final demonstration to the experts in the expert group, for example: the final actual decision-making stage, then the experts in the expert group need to understand the comprehensive situation of the back stage, then all process item sets under the same i-th calibration order and the same i+d-th order are demonstrated at the same time. The process item sets of each qualitative label; if t1<i<t2, it means that the content requested for demonstration is in the middle stage of demonstration to the experts in the expert group during the period, then the experts in the expert group need to understand the relevant content of other related calibration orders before and after, and then demonstrate the process item sets of all qualitative labels under the same ijth calibration order to i+jth calibration order at the same time; when implementing rule 2, experts can request demonstration independently, and the system adaptively determines reasonable demonstration content according to the demonstration stage, so that experts can efficiently make optimization decisions on hydropower supply according to the demonstration content, and further improve the accuracy, suitability and rationality of digital model generation; the first order threshold and the second order threshold are pre-set by technical personnel.

[0121] In one embodiment, the S2, based on the digital model, assisting the expert group in deciding on the optimization strategy for ensuring the supply of hydropower and electricity, includes:

[0122] S201. When the expert group holds an online meeting in the online conference room, the digital model is pushed into the online conference room;

[0123] In step S201, after the digital model is pushed into the online conference room, all experts in the expert group can view the digital model online;

[0124] S202, determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval;

[0125] In step S202, in the early stage of the online meeting, the experts in the expert group will discuss and determine the meeting objectives, which may be the direction, requirements and specific goals of optimizing the decision-making on the water, electricity and power supply; the first meeting record is the meeting speech generated by the experts in the first time interval; specifically, when determining based on the first meeting record, it can be implemented based on semantic analysis technology;

[0126] S203, based on the standard decision logic library and according to the meeting objectives, determine the standard decision logic;

[0127] In step S203, the pre-set standard decision logic library contains standard decision logic corresponding to different conference goals, and the standard decision logic is the logic for executing conference decisions that can achieve the conference goals;

[0128] S204, determining the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval;

[0129] In step S204, the second meeting record is the meeting speech generated by the expert personnel in the first time interval; in the middle and later stages of the online meeting, the expert group will continue to discuss and make decisions, so the real-time decision progress can be determined based on the second meeting record. The real-time decision progress is the real-time decision progress of the expert personnel reflected in the second meeting record. Specifically, the determination of the real-time decision progress can be achieved based on semantic analysis technology;

[0130] S205, when the real-time decision progress matches the first sub-logic in the standard decision logic, determine whether there is any other second sub-logic after the first sub-logic in the standard decision logic;

[0131] In step S205, the standard decision logic has multiple sub-logics, and each sub-logic is sorted in a logical order; the real-time decision progress is consistent with the first sub-logic, which means that the real-time decision progress is consistent with the decision progress that the first sub-logic should proceed to;

[0132] S206, when it is determined that there is a condition, determining a logic sequence that meets the logic sequence condition from the second sub-logic;

[0133] In step S206, when there is another second sub-logic after the first sub-logic in the standard decision logic, a logic sequence that meets the logic sequence condition is determined from the second sub-logic; under the constraint of the logic sequence condition, the logic sequence can be used as a basis for generating expert conditions;

[0134] S207, generating expert conditions based on the condition generation template and according to the logic sequence;

[0135] In step S207, the expert condition is a condition for screening out the experts who need to be focused and use constraints; the experts screened out by the expert condition are suitable for executing the decision-making operation belonging to the logic sequence; the condition generation template is a template for the system to generate expert conditions according to the logic sequence, for example: the second sub-logic in the logic sequence is to analyze the cause of the failure of the power equipment, and the generated expert condition is to screen out the experts with the most experience in analyzing the cause of the failure of the power equipment;

[0136] S208. Based on the expert conditions and according to the personnel portraits of the experts in the expert group, determine the target expert personnel;

[0137] In step S208, the personnel portrait of the expert personnel includes at least: position, various types of experience, etc.; based on the expert conditions, the target expert personnel are screened out according to the personnel portrait;

[0138] S209, providing a focus prompt to the target expert personnel, and based on the use constraint template, correspondingly constraining the target expert personnel to use the digital model;

[0139] In step S209, the target expert personnel are prompted to focus, for example, prompting the expert personnel to keep up with the current meeting discussion and decision-making, and fully devote themselves to the meeting discussion process; the constraint template is used as a template for the system to constrain the target expert personnel to use the digital model, for example, constraining the target expert personnel to only see the content related to the current meeting discussion progress in the digital model, and not to see the rest of the content;

[0140] S210. Receive the hydropower and electricity supply optimization strategy input by the expert group;

[0141] In step S210, the expert group will eventually decide on the optimization strategy for hydropower and power supply and input it; generally, continuously optimizing the decision-making for hydropower and power supply is a long process, which requires the experts of the expert group to invest a lot of energy. The embodiment of the present invention introduces expert conditions, screens out target experts, and provides focus prompts and usage constraints of digital models to the target experts, so as to ensure that the target experts can keep up with the rhythm of the meeting discussion at a specific appropriate time and devote themselves to the meeting discussion. The target experts do not need to concentrate their attention all the time, so as to realize intelligent assistance to the experts, which is particularly humane; secondly, when generating expert conditions, a logical sequence is introduced to improve the accuracy, comprehensiveness and suitability of the generation of expert conditions;

[0142] The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the cumulative trigger value corresponding to the historical speeches of the experts and the threshold value of the trigger value; the historical speeches of the experts are the historical speeches of the experts in the online conference, which correspond to the trigger values, and the trigger values ​​represent the extent to which the experts have discussed and determined the meeting goals. For example, if the historical speech is "Let's determine the goal", the corresponding trigger value is 5, and the threshold value of the trigger value can be 80. When the cumulative trigger value corresponding to the historical speeches of the experts is greater than or equal to the threshold value of the trigger value, the meeting goal can be determined at the corresponding moment;

[0143] The starting time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the ending time is the time when the decision on the optimization strategy for ensuring the supply of water, electricity and power is completed; wherein, the time when the decision on the optimization strategy for ensuring the supply of water, electricity and power is completed is the time when the expert completes the decision on the optimization strategy for ensuring the supply of water, electricity and power;

[0144] Wherein, the logical sequence conditions include:

[0145] The sum of the importance of each second sub-logic in the logic sequence falls within the threshold range of the sum of importance; wherein, the importance corresponding to the second sub-logic represents the importance of the execution of the second sub-logic for the realization of the meeting goal, and the threshold range of the sum of importance can be 50 to 80; ensuring that the sum of the importance of each second sub-logic in the logic sequence falls within the threshold range of the sum of importance can make the second sub-logic in the logic sequence require appropriate experts to continuously execute; improving the suitability and accuracy of logic sequence screening;

[0146] The logic type of the first second sub-logic in the logic sequence matches the standard logic type. The standard logic type is the logic type that requires the attention of experts, for example: the statistics of losses caused by supply failure. The other second sub-logics after the second sub-logic are logically related to the second sub-logic. Therefore, ensuring that the logic type of the first second sub-logic in the logic sequence matches the standard logic type can make each second sub-logic in the logic sequence require the attention of experts; further improving the suitability and accuracy of logic sequence screening.

[0147] In one embodiment, after executing the hydropower supply optimization strategy, the method further includes:

[0148] Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results;

[0149] The evaluation results will be pushed to the expert group.

[0150] The execution evaluation system contains evaluation results corresponding to different implementation situations of the hydropower and electric power supply optimization strategy. Therefore, based on the execution evaluation system, the execution of the hydropower and electric power supply optimization strategy can be evaluated, and the evaluation results can be obtained and pushed to the expert group.

[0151] In one embodiment, after pushing the evaluation results to the expert group, the method further includes:

[0152] When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

[0153] After reviewing the evaluation results, the expert group will make a decision on the optimization strategy for the secondary hydropower supply. After the decision is made, the secondary hydropower supply optimization strategy will be implemented.

[0154] The embodiment of the present invention provides a smart management system for ensuring water and electricity supply. Figure 2 As shown, including:

[0155] A generation module 1 is used to generate a digital model based on multimodal process information for ensuring the supply of hydropower and electricity;

[0156] Auxiliary module 2 is used to assist the expert group in making decisions on the optimization strategy for hydropower supply based on the digital model;

[0157] The first execution module 3 is used to execute the optimization strategy for ensuring the supply of hydropower and electricity.

[0158] The generation module generates a digital model based on multi-modal process information for ensuring the supply of hydropower and electricity, including:

[0159] Generate evolution rules based on multimodal process information;

[0160] Based on the evolution rules, the initial model is evolved and configured to obtain a digital model;

[0161] The step of generating evolution rules based on multimodal process information includes:

[0162] Based on the generation time of each of the multiple process items in the multimodal process information, each process item is divided into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold;

[0163] Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain the qualitative label of each process item set;

[0164] Based on the calibration knowledge graph, each qualitative label is calibrated to obtain the calibration order of each qualitative label;

[0165] Generate evolution rules:

[0166] Based on the process demonstration template, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high.

[0167] When at least one qualitatively labeled process item set under the same i-th order is requested for demonstration:

[0168] If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order;

[0169] If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order;

[0170] If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order;

[0171] Among them, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

[0172] The auxiliary module assists the expert group in making decisions on the optimization strategy for hydropower supply based on the digital model, including:

[0173] When the expert group holds an online meeting in the online meeting room, the digital model is pushed into the online meeting room;

[0174] Determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval;

[0175] Based on the standard decision logic library and meeting objectives, determine the standard decision logic;

[0176] Determine the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval;

[0177] When the real-time decision progress matches the first sub-logic in the standard decision logic, determining whether there is other second sub-logic after the first sub-logic in the standard decision logic;

[0178] When it is determined that the condition is yes, a logic sequence that meets the logic sequence condition is determined from the second sub-logic;

[0179] Generate expert conditions based on condition generation templates and logical sequences;

[0180] Based on the expert conditions, target experts are determined according to the personnel portraits of each expert in the expert group;

[0181] Providing focus reminders to target experts, and accordingly constraining the target experts’ use of digital models based on the use of constraint templates;

[0182] Receive input from the expert group on strategies to optimize the supply of hydropower and electricity;

[0183] The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the threshold value of the cumulative trigger value corresponding to the historical speeches of the experts that is greater than or equal to the sum of the trigger values;

[0184] The start time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the end time is the time when the decision on the optimization strategy for ensuring the supply of hydropower and electricity is completed;

[0185] Wherein, the logical sequence conditions include:

[0186] The sum of the importance of each second sub-logic in the logic sequence falls within a threshold range of the sum of importance;

[0187] The logic type of the first and second sub-logic in the logic sequence matches the standard logic type.

[0188] After the first execution module executes the hydropower supply optimization strategy, it also includes:

[0189] Evaluation module for:

[0190] Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results;

[0191] The evaluation results will be pushed to the expert group.

[0192] After the evaluation module pushes the evaluation results to the expert group, the method further includes:

[0193] The second execution module is used for:

[0194] When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

[0195] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for intelligent management of hydropower supply, characterized in that: include: Generate digital models based on multimodal process information for ensuring hydropower and electricity supply; Based on the digital model, assist the expert group in making decisions on the optimization strategy for hydropower supply; Implement strategies to optimize the supply of hydropower and electricity; The method of generating a digital model based on multi-modal process information of ensuring the supply of hydropower and electricity includes: Generate evolution rules based on multimodal process information; Based on the evolution rules, the initial model is evolved and configured to obtain a digital model; The step of generating evolution rules based on multimodal process information includes: Based on the generation time of each of the multiple process items in the multimodal process information, each process item is divided into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold; Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain the qualitative label of each process item set; Based on the calibration knowledge graph, each qualitative label is calibrated to obtain the calibration order of each qualitative label; Generate evolution rules: Based on the process demonstration template, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high. When at least one qualitatively labeled process item set under the same i-th order is requested for presentation: If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order; If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order; If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order; Wherein, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

2. The intelligent management method for ensuring hydropower supply as claimed in claim 1, characterized in that: The digital model is used to assist the expert group in making decisions on the optimization strategy for ensuring the supply of hydropower, including: When the expert group holds an online meeting in the online meeting room, the digital model is pushed into the online meeting room; Determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval; Based on the standard decision logic library and meeting objectives, determine the standard decision logic; Determine the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval; When the real-time decision progress matches the first sub-logic in the standard decision logic, determining whether there is other second sub-logic after the first sub-logic in the standard decision logic; When it is determined that the condition is yes, a logic sequence that meets the logic sequence condition is determined from the second sub-logic; Generate expert conditions based on condition generation templates and logical sequences; Based on the expert conditions, target experts are determined according to the personnel portraits of each expert in the expert group; Providing focus reminders to target experts, and accordingly constraining the target experts’ use of digital models based on the use of constraint templates; Receive input from the expert group on strategies to optimize the supply of hydropower and electricity; The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the threshold value of the cumulative trigger value corresponding to the historical speeches of the experts that is greater than or equal to the sum of the trigger values; The start time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the end time is the time when the decision on the optimization strategy for ensuring the supply of hydropower and electricity is completed; Wherein, the logical sequence conditions include: The sum of the importance of each second sub-logic in the logic sequence falls within a threshold range of the sum of importance; The logic type of the first and second sub-logic in the logic sequence matches the standard logic type.

3. The intelligent management method for ensuring the supply of hydropower and electricity according to claim 1, characterized in that: After the implementation of the hydropower and electricity supply optimization strategy, it also includes: Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results; The evaluation results will be pushed to the expert group.

4. The intelligent management method for ensuring the supply of hydropower and electricity as claimed in claim 3, characterized in that: After the evaluation results are pushed to the expert group, the following steps are also included: When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

5. A smart management system for ensuring the supply of hydropower and electricity, characterized in that: include: A generation module for generating a digital model based on multimodal process information for ensuring the supply of hydropower and electricity; Auxiliary module, used to assist the expert group in making decisions on optimization strategies for hydropower supply based on digital models; The first execution module is used to execute the optimization strategy for ensuring the supply of hydropower and electricity; The generation module generates a digital model based on multi-modal process information for ensuring the supply of hydropower and electricity, including: Generate evolution rules based on multimodal process information; Based on the evolution rules, the initial model is evolved and configured to obtain a digital model; The step of generating evolution rules based on multimodal process information includes: Based on the generation time of each of the multiple process items in the multimodal process information, each process item is divided into multiple process item sets; wherein the generation time difference between two process items in the same process item set is less than or equal to a time difference threshold; Based on the qualitative knowledge graph, each process item set is qualitatively processed to obtain the qualitative label of each process item set; Based on the calibration knowledge graph, each qualitative label is calibrated to obtain the calibration order of each qualitative label; Generate evolution rules: Based on the process demonstration template, the process item sets of all qualitative labels under the same calibration order are demonstrated in order from low to high. When at least one qualitatively labeled process item set under the same i-th order is requested for presentation: If i≤t1, simultaneously demonstrate the process item sets of all qualitative labels under the same first i calibration order; If i ≥ t2, simultaneously demonstrate the process item sets of all qualitative labels under the same i-th calibration order and the same post-Ni order; If t1<i<t2, simultaneously demonstrate the process item sets of all qualitative labels under the same ijth calibration order to the i+jth calibration order; Wherein, i=1,2,3,…,N; N is the highest value of the calibration order; t1 and t2 are the first order thresholds; j is the second order threshold.

6. The intelligent management system for ensuring water and electricity supply as claimed in claim 5, characterized in that: The auxiliary module assists the expert group in making decisions on the optimization strategy for hydropower supply based on the digital model, including: When the expert group holds an online meeting in the online meeting room, the digital model is pushed into the online meeting room; Determining a meeting goal based on a first meeting record generated in the online conference room within a first time interval; Based on the standard decision logic library and meeting objectives, determine the standard decision logic; Determine the real-time decision progress based on the second meeting record generated in the online conference room within the second time interval; When the real-time decision progress matches the first sub-logic in the standard decision logic, determining whether there is other second sub-logic after the first sub-logic in the standard decision logic; When it is determined that the condition is yes, a logic sequence that meets the logic sequence condition is determined from the second sub-logic; Generate expert conditions based on condition generation templates and logical sequences; Based on the expert conditions, target experts are determined according to the personnel portraits of each expert in the expert group; Providing focus reminders to target experts, and accordingly constraining the target experts’ use of digital models based on the use of constraint templates; Receive input from the expert group on strategies to optimize the supply of hydropower and electricity; The starting time of the first time interval is the time when the first expert speaks in the online conference room, and the ending time is the threshold value of the cumulative trigger value corresponding to the historical speeches of the experts that is greater than or equal to the sum of the trigger values; The start time of the second time interval is the time when the first expert speaks in the online conference room after the end time of the first time interval, and the end time is the time when the decision on the optimization strategy for ensuring the supply of hydropower and electricity is completed; Wherein, the logical sequence conditions include: The sum of the importance of each second sub-logic in the logic sequence falls within a threshold range of the sum of importance; The logic type of the first and second sub-logic in the logic sequence matches the standard logic type.

7. The intelligent management system for ensuring water and electricity supply as claimed in claim 5, characterized in that: After the first execution module executes the hydropower and electricity supply optimization strategy, it also includes: Evaluation module for: Based on the implementation evaluation system, the implementation of the hydropower and electricity supply optimization strategy is evaluated to obtain the evaluation results; The evaluation results will be pushed to the expert group.

8. The intelligent management system for ensuring water and electricity supply as claimed in claim 7, characterized in that: After the evaluation module pushes the evaluation results to the expert group, the method further includes: The second execution module is used for: When the expert group decides on the optimization strategy for securing the secondary hydropower supply, the relay will execute the optimization strategy for securing the secondary hydropower supply.

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