CN117057777A - Comprehensive management method for operation and maintenance of power distribution network - Google Patents
Comprehensive management method for operation and maintenance of power distribution network Download PDFInfo
- Publication number
- CN117057777A CN117057777A CN202311006679.0A CN202311006679A CN117057777A CN 117057777 A CN117057777 A CN 117057777A CN 202311006679 A CN202311006679 A CN 202311006679A CN 117057777 A CN117057777 A CN 117057777A
- Authority
- CN
- China
- Prior art keywords
- distribution network
- data
- power data
- module
- fault
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007726 management method Methods 0.000 title claims abstract description 122
- 238000012423 maintenance Methods 0.000 title claims abstract description 19
- 238000012545 processing Methods 0.000 claims abstract description 71
- 238000011156 evaluation Methods 0.000 claims abstract description 56
- 238000007405 data analysis Methods 0.000 claims abstract description 39
- 238000012544 monitoring process Methods 0.000 claims abstract description 39
- 238000000034 method Methods 0.000 claims abstract description 11
- 238000003066 decision tree Methods 0.000 claims description 29
- 238000013210 evaluation model Methods 0.000 claims description 27
- 238000007781 pre-processing Methods 0.000 claims description 19
- 238000000354 decomposition reaction Methods 0.000 claims description 17
- 238000012216 screening Methods 0.000 claims description 9
- 238000012706 support-vector machine Methods 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 3
- 238000012217 deletion Methods 0.000 claims description 3
- 230000037430 deletion Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 3
- 238000011144 upstream manufacturing Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims 1
- 230000000694 effects Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 230000010354 integration Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/24323—Tree-organised classifiers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/20—Ensemble learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Data Mining & Analysis (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Evolutionary Computation (AREA)
- Operations Research (AREA)
- General Health & Medical Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Biology (AREA)
- Primary Health Care (AREA)
- Water Supply & Treatment (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The application relates to an operation and maintenance integrated management system and method for a power distribution network, wherein the system comprises a data acquisition module, a distribution network equipment fault processing module, a distribution network project management evaluation module, a distribution network power data analysis processing module and an integrated management module; the data acquisition module is used for acquiring monitoring data, distribution network project index data and power data of the distribution network equipment; the distribution network equipment fault processing module is used for determining the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment; the distribution network project management evaluation module is used for carrying out distribution network project later management evaluation according to the distribution network project index data; and the distribution network power data analysis processing module is used for carrying out distribution network configuration planning according to the power data so as to realize distribution network management auxiliary decision-making. Based on the application, the operation and maintenance management efficiency of the power distribution network can be improved.
Description
Technical Field
The application relates to the technical field of power distribution networks, in particular to a comprehensive management method for operation and maintenance of a power distribution network.
Background
In the field of distribution network, generally, each management system is independently set to perform operation and maintenance management of different projects, when a worker uses the system, the worker often needs to switch different operation and maintenance management platforms according to different requirements, and some operation and maintenance rely on manual recording, manual processing and the like, which is time-consuming and labor-consuming and has low efficiency.
Disclosure of Invention
The application aims to provide a comprehensive management system and method for operation and maintenance of a power distribution network, so as to improve the efficiency of operation and maintenance management of the power distribution network.
In order to achieve the above purpose, the embodiment of the application provides a comprehensive management system for operation and maintenance of a power distribution network, which comprises a comprehensive management module, a data acquisition module, a distribution network equipment fault processing module, a distribution network project management evaluation module and a distribution network power data analysis processing module, wherein the data acquisition module, the distribution network equipment fault processing module, the distribution network project management evaluation module and the distribution network power data analysis processing module are connected with the comprehensive management module;
the data acquisition module is used for acquiring monitoring data, distribution network project index data and power data of the distribution network equipment and transmitting the monitoring data, the distribution network project index data and the power data to the comprehensive management module;
the comprehensive management module is used for sending the monitoring data of the distribution network equipment to the distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module is used for determining the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
the comprehensive management module is used for sending the related data of the distribution network project index to the distribution network project management evaluation module, and the distribution network project management evaluation module is used for carrying out the post-management evaluation of the distribution network project according to the distribution network project index data;
the comprehensive management module is used for sending the power data to the distribution network power data analysis processing module, and the distribution network power data analysis processing module is used for carrying out distribution network configuration planning according to the power data so as to realize auxiliary decision-making of distribution network management.
The embodiment of the application also provides a comprehensive management method for the operation and maintenance of the power distribution network based on the system, which comprises the following steps:
the data acquisition module acquires monitoring data, distribution network project index data and power data of the distribution network equipment and sends the monitoring data, the distribution network project index data and the power data to the comprehensive management module;
the comprehensive management module sends monitoring data of the distribution network equipment to the distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module determines the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
the comprehensive management module sends the relevant data of the distribution network project index to the distribution network project management evaluation module, and the distribution network project management evaluation module carries out the post-management evaluation of the distribution network project according to the distribution network project index data;
and the comprehensive management module sends the power data to the distribution network power data analysis processing module, and the distribution network power data analysis processing module performs distribution network configuration planning according to the power data to realize auxiliary decision-making of distribution network management.
Further, the distribution network equipment fault processing module determines a fault position, a fault range and a fault type of the distribution network equipment according to the monitoring data of the distribution network equipment, and specifically includes:
the distribution network equipment fault processing module determines the direction of current according to the monitoring data of the distribution network equipment, determines the upstream-downstream relation of the distribution network equipment in the distribution network according to the direction of the current, records the distribution network equipment in the current input direction as upstream equipment, and records the distribution network equipment in the current output direction as downstream equipment;
the distribution network equipment fault processing module generates a fault report according to the change characteristics of the monitoring data of all the distribution network equipment and the upstream-downstream relation in the distribution network, wherein the fault report comprises a fault position, a fault range and a fault type.
Further, the distribution network project management evaluation module performs distribution network project post management evaluation according to the distribution network project index data, and specifically includes:
constructing a distribution network project index system;
establishing a decision tree evaluation model according to the distribution network project index system, extracting classification rules through the decision tree evaluation model, and generating a classification rule base;
and analyzing the index data of the distribution network project by a comprehensive index system evaluation method and comparing the classification rule base to realize the later management evaluation of the distribution network project.
Further, the step of establishing a decision tree evaluation model according to the distribution network project index system, extracting classification rules through the decision tree evaluation model, and generating a classification rule base specifically comprises the following steps:
constructing a decision tree evaluation model by adopting an ID3 algorithm, wherein the data S is assumed to have m categories, and the occupancy rate of the data of the ith category in the total data is p i The entropy of the data S is:
wherein s is 1 ,s 2 ,…,s m Respectively the category of the data S;
if the feature A has v categories, the information entropy of the feature A is as follows:
wherein j represents the j-th class of feature A;
the difference between the entropy reduction before and after classification is the information gain, namely:
Gain(A)＝I(s 1 ,s 2 ,…,s m )-E(A)
calculating information gain of indexes in all distribution network project index systems, taking the index with the maximum information gain as a root node, leading out a branch for each attribute value, dividing a sample, carrying out new division on the branch nodes, finally constructing a decision tree evaluation model, and extracting classification rules according to the decision tree evaluation model to form a classification rule base.
Further, the distribution network power data analysis processing module performs distribution network configuration planning according to the power data to realize distribution network management auxiliary decision, and specifically includes:
the distribution network power data analysis processing module carries out preprocessing and variation modal decomposition on the power data;
screening the power data after preprocessing and variation modal decomposition through an extreme gradient lifting algorithm;
and inputting the screened power data into a support vector machine, and carrying out configuration planning prediction of the distribution network.
Further, the distribution network power data analysis processing module performs preprocessing and variation modal decomposition on power data, and specifically includes:
the distribution network power data analysis processing module is used for preprocessing the power data, including the complementation and deletion of the power data missing values, and decomposing the power data into k subsequences through variation modal decomposition after the preprocessing is finished:
wherein S (t) is the power data at time t, delta i (t) is a power data subsequence at time t.
Further, the filtering of the power data after preprocessing and variation modal decomposition by an extreme gradient lifting algorithm specifically comprises the following steps:
screening the generated power data subsequences through an extreme gradient lifting algorithm to obtain screened power data subsequences, wherein the screened power data subsequences are:
wherein S is 1 A is a power data sequence group n 、b n 、c n D n Is a key influencing factor.
The embodiment of the application has the following beneficial effects:
and (3) comprehensive data acquisition: the system comprises a data acquisition module which can acquire monitoring data of distribution network equipment, data related to distribution network project indexes and power data. Thus, the comprehensive data information can be obtained, and accurate data support is provided for subsequent fault processing, project evaluation and decision making.
Fault handling is accurate: the distribution network equipment fault processing module can determine the fault position, the fault range and the fault type according to the monitoring data of the equipment. Therefore, the fault can be rapidly positioned, the processing time of the fault is reduced, and the reliability and stability of the power distribution network are improved.
Distribution network project management evaluation: the distribution network project management evaluation module in the system can perform later management evaluation according to project indexes. Therefore, the operation condition of the distribution network project can be evaluated and monitored, problems can be found in time, corresponding management measures can be taken, and the project management effect can be improved.
Power data analysis decision: and the distribution network power data analysis processing module performs configuration planning and auxiliary decision making according to the power data. By analyzing the power data, the supply and demand conditions can be known, the configuration of the distribution network is optimized, and the power transmission efficiency and quality are improved.
Comprehensive management and cooperative work: the integrated management module is connected with each module, can coordinate the work of each module and provides global management function. Therefore, the integration of operation and management of the power distribution network can be realized, and the working efficiency and the coordination capacity are improved.
In summary, the comprehensive management system scheme for the operation and maintenance of the power distribution network has the advantages of comprehensive data acquisition, accurate fault processing, project management evaluation, power data analysis decision and comprehensive management coordination, and can improve the operation efficiency, safety and reliability of the power distribution network.
Details and advantages of embodiments of the application that are not described in detail in the detailed description.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required in the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a comprehensive operation and maintenance management method for a power distribution network in an embodiment of the application.
Detailed Description
The detailed description of the drawings is intended as an illustration of the present embodiment of the application and is not intended to represent the only form in which the present application may be practiced. It is to be understood that the same or equivalent functions may be accomplished by different embodiments that are intended to be encompassed within the spirit and scope of the application.
The application provides an operation and maintenance integrated management system for a power distribution network, which comprises an integrated management module, and a data acquisition module, a distribution network equipment fault processing module, a distribution network project management evaluation module and a distribution network power data analysis processing module which are connected with the integrated management module;
the data acquisition module is used for acquiring monitoring data, distribution network project index data and power data of the distribution network equipment and transmitting the monitoring data, the distribution network project index data and the power data to the comprehensive management module;
the comprehensive management module is used for sending the monitoring data of the distribution network equipment to the distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module is used for determining the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
the comprehensive management module is used for sending the related data of the distribution network project index to the distribution network project management evaluation module, and the distribution network project management evaluation module is used for carrying out the post-management evaluation of the distribution network project according to the distribution network project index data;
the comprehensive management module is used for sending the power data to the distribution network power data analysis processing module, and the distribution network power data analysis processing module is used for carrying out distribution network configuration planning according to the power data so as to realize auxiliary decision-making of distribution network management.
Referring to fig. 1, another embodiment of the present application further provides a comprehensive management method for operation and maintenance of a power distribution network, which is implemented based on the system described in the foregoing embodiment, and includes the following steps:
step S10, a data acquisition module acquires monitoring data, distribution network project index data and power data of distribution network equipment and sends the monitoring data, the distribution network project index data and the power data to a comprehensive management module;
step S20, the comprehensive management module sends monitoring data of the distribution network equipment to a distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module determines the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
step S30, the comprehensive management module sends relevant data of the distribution network project index to a distribution network project management evaluation module, and the distribution network project management evaluation module carries out post management evaluation of the distribution network project according to the distribution network project index data;
and S40, the comprehensive management module sends the power data to a distribution network power data analysis processing module, and the distribution network power data analysis processing module performs distribution network configuration planning according to the power data to realize auxiliary decision-making of distribution network management.
Further, the distribution network equipment fault processing module determines a fault position, a fault range and a fault type of the distribution network equipment according to the monitoring data of the distribution network equipment, and specifically includes:
the distribution network equipment fault processing module determines the direction of current according to the monitoring data of the distribution network equipment, determines the upstream-downstream relation of the distribution network equipment in the distribution network according to the direction of the current, records the distribution network equipment in the current input direction as upstream equipment, and records the distribution network equipment in the current output direction as downstream equipment;
the distribution network equipment fault processing module generates a fault report according to the change characteristics of the monitoring data of all the distribution network equipment and the upstream-downstream relation in the distribution network, wherein the fault report comprises a fault position, a fault range and a fault type.
Further, the distribution network project management evaluation module performs distribution network project post management evaluation according to the distribution network project index data, and specifically includes:
constructing a distribution network project index system;
establishing a decision tree evaluation model according to the distribution network project index system, extracting classification rules through the decision tree evaluation model, and generating a classification rule base;
and analyzing the index data of the distribution network project by a comprehensive index system evaluation method and comparing the classification rule base to realize the later management evaluation of the distribution network project.
Specifically, the specific steps of the distribution network project management evaluation module for carrying out the distribution network project post-management evaluation according to the distribution network project index data are as follows:
constructing a distribution network project index system: firstly, a complete distribution network project index system is required to be constructed, wherein the index system comprises economic indexes, technical indexes, environment indexes and the like. These metrics may be determined based on the characteristics and goals of the distribution network project to evaluate various aspects of the distribution network project.
Establishing a decision tree evaluation model: and establishing a decision tree evaluation model based on the distribution network project index system. Decision trees are a commonly used classification and prediction algorithm, and can make decision judgment according to existing data and classification rules. The classification rules can be extracted through the model, and a classification rule base is generated for subsequent evaluation analysis.
Analyzing distribution network project index data: and analyzing the index data of the distribution network project by using a comprehensive index system evaluation method. The comprehensive index system evaluation method can comprehensively consider the weights and interrelationships of a plurality of indexes to obtain a comprehensive evaluation result. Meanwhile, according to the classification rule base of the established decision tree evaluation model, the distribution network project index data can be classified and evaluated.
Through the steps, the distribution network project management evaluation module can establish a decision tree evaluation model according to a distribution network project index system and generate a classification rule base, and the comprehensive index system evaluation method is utilized to analyze and evaluate distribution network project index data. Therefore, the post management of the distribution network project can be evaluated, problems and improvement measures can be found in time, and the effect and management level of the distribution network project are improved.
Further, the step of establishing a decision tree evaluation model according to the distribution network project index system, extracting classification rules through the decision tree evaluation model, and generating a classification rule base specifically comprises the following steps:
constructing a decision tree evaluation model by adopting an ID3 algorithm, wherein the data S is assumed to have m categories, and the occupancy rate of the data of the ith category in the total data is p i The entropy of the data S is:
wherein s is 1 ,s 2 ,…,s m Respectively the category of the data S;
if the feature A has v categories, the information entropy of the feature A is as follows:
wherein j represents the j-th class of feature A;
the difference between the entropy reduction before and after classification is the information gain, namely:
Gain(A)＝I(s 1 ,s 2 ,…,s m )-E(A)
calculating information gain of indexes in all distribution network project index systems, taking the index with the maximum information gain as a root node, leading out a branch for each attribute value, dividing a sample, carrying out new division on the branch nodes, finally constructing a decision tree evaluation model, and extracting classification rules according to the decision tree evaluation model to form a classification rule base.
For example, to calculate the information gain of the indexes in the index system of the distribution network project, the value range and the corresponding classification label of each index need to be known first, and then, a decision tree evaluation model is constructed and classification rules are extracted according to the following steps:
step 1 calculates entropy (entropy) of the overall data as uncertainty of the initial node.
Step 2, calculating an information gain (information gain) for each index, wherein the information gain of the index is the difference between the initial node entropy and the child node entropy divided by using the index.
And 3, finding out an index with the maximum information gain as a root node, and constructing a first layer decision node.
Step 4, for each attribute value of the root node, a branch is led out.
Step 5 for each branch node, repeat steps 2 to 4 until a certain stop condition is met, such as all samples belonging to the same class or reaching a maximum depth. In the leaf nodes, classification rules are extracted according to class statistics of the samples. For example, if a sample in a certain leaf node belongs to a category a, the extraction rule is "the sample with index 1 and with attribute value X belongs to the category a", a classification rule base is constructed, the classification rules extracted from all the leaf nodes are added into the rule base, a new sample can be classified according to the constructed decision tree evaluation model, the process of judging according to the decision node and the attribute value is followed, the layer-by-layer judgment is carried out until the leaf node is reached, and the category of the sample is determined according to the classification rule of the leaf node.
Further, the distribution network power data analysis processing module performs distribution network configuration planning according to the power data to realize distribution network management auxiliary decision, and specifically includes:
the distribution network power data analysis processing module carries out preprocessing and variation modal decomposition on the power data;
screening the power data after preprocessing and variation modal decomposition through an extreme gradient lifting algorithm;
and inputting the screened power data into a support vector machine, and carrying out configuration planning prediction of the distribution network.
Specifically, the distribution network power data analysis processing module performs distribution network configuration planning according to power data, and the process of realizing auxiliary decision-making of distribution network management is as follows:
preprocessing and variational modal decomposition: first, the power data needs to be preprocessed, including noise removal, normalization, etc., to ensure the data quality. Then, the data is decomposed by adopting a variation modal decomposition technology, the data is decomposed into a plurality of modal components, and characteristic information of the data is extracted.
Extreme gradient lifting algorithm screening: and screening the power data subjected to pretreatment and variation modal decomposition by adopting an extreme gradient lifting algorithm. The algorithm is a machine learning algorithm based on decision tree integration, and can improve the accuracy of a prediction model through iterative training. By utilizing the algorithm to screen the power data, the characteristics which have important effects on configuration planning of the distribution network can be identified, and redundant information is reduced.
Support vector machine distribution network configuration planning prediction: and inputting the screened power data into a Support Vector Machine (SVM) model, and carrying out configuration planning prediction of the distribution network. The SVM is a machine learning algorithm that can classify and predict regression based on existing sample data. By training the SVM model, optimal values of different distribution network configuration parameters can be predicted according to the characteristics of the power data, so that an auxiliary decision is provided.
Through the process, the distribution network power data analysis processing module can perform preprocessing, feature screening and planning prediction on power data, and helps to realize optimization of distribution network configuration and assistance of decision. Therefore, the economical efficiency, the reliability and the sustainability of the distribution network can be improved, and scientific basis is provided for the management of the distribution network.
Further, the distribution network power data analysis processing module performs preprocessing and variation modal decomposition on power data, and specifically includes:
the distribution network power data analysis processing module is used for preprocessing the power data, including the complementation and deletion of the power data missing values, and decomposing the power data into k subsequences through variation modal decomposition after the preprocessing is finished:
wherein S (t) is the power data at time t, delta i (t) is a power data subsequence at time t.
Further, the filtering of the power data after preprocessing and variation modal decomposition by an extreme gradient lifting algorithm specifically comprises the following steps:
screening the generated power data subsequences through an extreme gradient lifting algorithm to obtain screened power data subsequences, wherein the screened power data subsequences are:
wherein S is 1 A is a power data sequence group n 、b n 、c n D n Is a key influencing factor.
Based on the description of the embodiments above, the embodiments of the present application have the following advantages:
and (3) comprehensive data acquisition: the system comprises a data acquisition module which can acquire monitoring data of distribution network equipment, data related to distribution network project indexes and power data. Thus, the comprehensive data information can be obtained, and accurate data support is provided for subsequent fault processing, project evaluation and decision making.
Fault handling is accurate: the distribution network equipment fault processing module can determine the fault position, the fault range and the fault type according to the monitoring data of the equipment. Therefore, the fault can be rapidly positioned, the processing time of the fault is reduced, and the reliability and stability of the power distribution network are improved.
Distribution network project management evaluation: the distribution network project management evaluation module in the system can perform later management evaluation according to project indexes. Therefore, the operation condition of the distribution network project can be evaluated and monitored, problems can be found in time, corresponding management measures can be taken, and the project management effect can be improved.
Power data analysis decision: and the distribution network power data analysis processing module performs configuration planning and auxiliary decision making according to the power data. By analyzing the power data, the supply and demand conditions can be known, the configuration of the distribution network is optimized, and the power transmission efficiency and quality are improved.
Comprehensive management and cooperative work: the integrated management module is connected with each module, can coordinate the work of each module and provides global management function. Therefore, the integration of operation and management of the power distribution network can be realized, and the working efficiency and the coordination capacity are improved.
In summary, the comprehensive management system scheme for the operation and maintenance of the power distribution network has the advantages of comprehensive data acquisition, accurate fault processing, project management evaluation, power data analysis decision and comprehensive management coordination, and can improve the operation efficiency, safety and reliability of the power distribution network.
The foregoing description of embodiments of the application has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. The comprehensive management system for the operation and maintenance of the power distribution network is characterized by comprising a comprehensive management module, a data acquisition module, a distribution network equipment fault processing module, a distribution network project management evaluation module and a distribution network power data analysis processing module, wherein the data acquisition module, the distribution network equipment fault processing module, the distribution network project management evaluation module and the distribution network power data analysis processing module are connected with the comprehensive management module;
the data acquisition module is used for acquiring monitoring data, distribution network project index data and power data of the distribution network equipment and transmitting the monitoring data, the distribution network project index data and the power data to the comprehensive management module;
the comprehensive management module is used for sending the monitoring data of the distribution network equipment to the distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module is used for determining the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
the comprehensive management module is used for sending the related data of the distribution network project index to the distribution network project management evaluation module, and the distribution network project management evaluation module is used for carrying out the post-management evaluation of the distribution network project according to the distribution network project index data;
the comprehensive management module is used for sending the power data to the distribution network power data analysis processing module, and the distribution network power data analysis processing module is used for carrying out distribution network configuration planning according to the power data so as to realize auxiliary decision-making of distribution network management.
2. The comprehensive management method for operation and maintenance of the power distribution network based on the system implementation of claim 1 is characterized by comprising the following steps:
the data acquisition module acquires monitoring data, distribution network project index data and power data of the distribution network equipment and sends the monitoring data, the distribution network project index data and the power data to the comprehensive management module;
the comprehensive management module sends monitoring data of the distribution network equipment to the distribution network equipment fault processing module in real time, and the distribution network equipment fault processing module determines the fault position, the fault range and the fault type of the distribution network equipment according to the monitoring data of the distribution network equipment;
the comprehensive management module sends the relevant data of the distribution network project index to the distribution network project management evaluation module, and the distribution network project management evaluation module carries out the post-management evaluation of the distribution network project according to the distribution network project index data;
and the comprehensive management module sends the power data to the distribution network power data analysis processing module, and the distribution network power data analysis processing module performs distribution network configuration planning according to the power data to realize auxiliary decision-making of distribution network management.
3. The method according to claim 2, wherein the distribution network equipment fault handling module determines a fault location, a fault range and a fault type of the distribution network equipment according to the monitoring data of the distribution network equipment, and specifically includes:
the distribution network equipment fault processing module determines the direction of current according to the monitoring data of the distribution network equipment, determines the upstream-downstream relation of the distribution network equipment in the distribution network according to the direction of the current, records the distribution network equipment in the current input direction as upstream equipment, and records the distribution network equipment in the current output direction as downstream equipment;
the distribution network equipment fault processing module generates a fault report according to the change characteristics of the monitoring data of all the distribution network equipment and the upstream-downstream relation in the distribution network, wherein the fault report comprises a fault position, a fault range and a fault type.
4. A method according to claim 3, wherein the distribution network project management evaluation module performs distribution network project post-management evaluation according to the distribution network project index data, and specifically includes:
constructing a distribution network project index system;
establishing a decision tree evaluation model according to the distribution network project index system, extracting classification rules through the decision tree evaluation model, and generating a classification rule base;
and analyzing the index data of the distribution network project by a comprehensive index system evaluation method and comparing the classification rule base to realize the later management evaluation of the distribution network project.
5. The method according to claim 4, wherein the establishing a decision tree evaluation model according to the distribution network project index system extracts classification rules through the decision tree evaluation model to generate a classification rule base, specifically comprises:
constructing a decision tree evaluation model by adopting an ID3 algorithm, wherein the data S is assumed to have m categories, and the occupancy rate of the data of the ith category in the total data is p i The entropy of the data S is:
wherein s is 1 ,s 2 ,…,s m Respectively the category of the data S;
if the feature A has v categories, the information entropy of the feature A is as follows:
wherein j represents the j-th class of feature A;
the difference between the entropy reduction before and after classification is the information gain, namely:
Gain(A)＝I(s 1 ,s 2 ,…,s m )-E(A)
calculating information gain of indexes in all distribution network project index systems, taking the index with the maximum information gain as a root node, leading out a branch for each attribute value, dividing a sample, carrying out new division on the branch nodes, finally constructing a decision tree evaluation model, and extracting classification rules according to the decision tree evaluation model to form a classification rule base.
6. The method of claim 5, wherein the distribution network power data analysis processing module performs distribution network configuration planning according to the power data, and implements distribution network management assistance decision making, and specifically includes:
the distribution network power data analysis processing module carries out preprocessing and variation modal decomposition on the power data;
screening the power data after preprocessing and variation modal decomposition through an extreme gradient lifting algorithm;
and inputting the screened power data into a support vector machine, and carrying out configuration planning prediction of the distribution network.
7. The method of claim 6, wherein the distribution network power data analysis processing module performs preprocessing and variation modal decomposition on the power data, and specifically comprises:
the distribution network power data analysis processing module is used for preprocessing the power data, including the complementation and deletion of the power data missing values, and decomposing the power data into k subsequences through variation modal decomposition after the preprocessing is finished:
wherein S (t) is the power data at time t, delta i (t) is a power data subsequence at time t.
8. The method according to claim 7, wherein the filtering of the preprocessed and decomposed power data by the extreme gradient lifting algorithm specifically comprises:
screening the generated power data subsequences through an extreme gradient lifting algorithm to obtain screened power data subsequences, wherein the screened power data subsequences are:
wherein S is 1 A is a power data sequence group n 、b n 、c n D n Is a key influencing factor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311006679.0A CN117057777A (en) | 2023-08-10 | 2023-08-10 | Comprehensive management method for operation and maintenance of power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311006679.0A CN117057777A (en) | 2023-08-10 | 2023-08-10 | Comprehensive management method for operation and maintenance of power distribution network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117057777A true CN117057777A (en) | 2023-11-14 |
Family
ID=88663853
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311006679.0A Pending CN117057777A (en) | 2023-08-10 | 2023-08-10 | Comprehensive management method for operation and maintenance of power distribution network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117057777A (en) |
-
2023
- 2023-08-10 CN CN202311006679.0A patent/CN117057777A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110609759B (en) | Fault root cause analysis method and device | |
| WO2021184630A1 (en) | Method for locating pollutant discharge object on basis of knowledge graph, and related device | |
| CN114816909B (en) | Real-time log detection early warning method and system based on machine learning | |
| CN108470022B (en) | Intelligent work order quality inspection method based on operation and maintenance management | |
| CN105335752A (en) | Principal component analysis multivariable decision-making tree-based connection manner identification method | |
| CN110472671B (en) | Multi-stage-based fault data preprocessing method for oil immersed transformer | |
| CN111639497A (en) | Abnormal behavior discovery method based on big data machine learning | |
| CN111176953B (en) | Abnormality detection and model training method, computer equipment and storage medium | |
| CN111507504A (en) | Adaboost integrated learning power grid fault diagnosis system and method based on data resampling | |
| CN112364928A (en) | Random forest classification method in transformer substation fault data diagnosis | |
| CN114201374A (en) | Operation and maintenance time sequence data anomaly detection method and system based on hybrid machine learning | |
| CN115906160B (en) | Information processing method and system based on artificial intelligence analysis | |
| CN115719283A (en) | Intelligent accounting management system | |
| CN116976318A (en) | Intelligent auditing system for switching operation ticket of power grid based on deep learning and model reasoning | |
| CN116843955A (en) | Microorganism classification and identification method and system based on computer vision | |
| CN109594967A (en) | A kind of lock of tool drilling detection method for early warning based on well logging big data | |
| CN113891342B (en) | Base station inspection method and device, electronic equipment and storage medium | |
| CN109635008B (en) | Equipment fault detection method based on machine learning | |
| CN117216713A (en) | Fault delimiting method, device, electronic equipment and storage medium | |
| CN111209955A (en) | Airplane power supply system fault identification method based on deep neural network and random forest | |
| CN117057777A (en) | Comprehensive management method for operation and maintenance of power distribution network | |
| CN115987692A (en) | Safety protection system and method based on flow backtracking analysis | |
| CN116126807A (en) | Log analysis method and related device | |
| CN115392710A (en) | Wind turbine generator operation decision method and system based on data filtering | |
| CN111680572B (en) | Dynamic judgment method and system for power grid operation scene |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |