CN117913828A - Risk assessment method and system for power distribution system - Google Patents
Risk assessment method and system for power distribution system Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- 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
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- 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
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- 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
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Abstract
The invention belongs to the field of power distribution systems, and discloses a risk assessment method and a risk assessment system for a power distribution system, wherein the risk assessment method comprises the following steps: the load monitoring module is used for monitoring and analyzing the load risk of the power distribution system: marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a load coefficient of the monitoring object in a monitoring period; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through the load coefficient; according to the invention, on the premise of the load abnormal signal generated by the load monitoring module and the arc abnormal signal generated by the arc monitoring module, each monitoring object is analyzed and evaluated in the monitoring period by utilizing the concentration coefficient, so that the hidden risk power distribution equipment is marked and maintained, and the hidden risk power distribution equipment is conveniently found in the risk evaluation process of the power distribution system, thereby achieving the effect of improving the accuracy of the risk evaluation result.
Description
Technical Field
The invention belongs to the field of power distribution systems, relates to a data analysis technology, and particularly relates to a risk assessment method and a risk assessment system for a power distribution system.
Background
The distribution system is an indispensable part in industrial production and civil life, and has the function of sending a power supply to equipment such as cables, relays, switches, distribution transformers and the like and distributing the power supply to the required equipment, but in the use process, a plurality of hidden dangers exist, and the operation of the power system can be seriously influenced, and even electrical accidents can be caused.
The existing risk assessment method for the power distribution system cannot be combined with the risk monitoring data of each power distribution device to conduct comprehensive analysis, so that macroscopic system risk assessment cannot be considered with microscopic hidden risk analysis of each power distribution device, and the accuracy of the risk assessment result of the power distribution system is low.
Disclosure of Invention
The invention aims to provide a risk assessment method and a risk assessment system for a power distribution system, which are used for solving the problem that the accuracy of a risk assessment result of the existing risk assessment method for the power distribution system is low;
The technical problems to be solved by the invention are as follows: how to provide a risk assessment method and a system for a power distribution system, which can give consideration to both system risk assessment and implicit risk analysis of power distribution equipment.
The aim of the invention can be achieved by the following technical scheme:
A risk assessment system for a power distribution system, comprising a risk assessment platform, wherein the risk assessment platform is in communication connection with a load monitoring module, an arc monitoring module and a risk assessment module;
The load monitoring module is used for monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period; the load factor FZ of the monitored object in the monitoring period is obtained by carrying out numerical calculation on the linear temperature value XW, the high current value GL and the current increasing value ZL; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through a load coefficient FZ;
The arc monitoring module is used for monitoring and analyzing the arc risk of the power distribution system: acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period by carrying out numerical calculation on noise data ZS, peak-pressing data YF and table temperature data BW; judging whether the arc risk of the power distribution system in the monitoring period meets the requirement or not through an arc coefficient DH;
the risk assessment module is used for assessing and analyzing the operation risk of the power distribution system when the load state of the power distribution system does not meet the requirement or has arc risk, obtaining a concentration coefficient of a monitoring object in a monitoring period through the assessment and analysis, and judging whether the monitoring object has hidden risk in the monitoring period through the concentration coefficient.
As a preferred embodiment of the present invention, the line temperature value XW is a maximum value of a surface temperature value of the power supply line of the monitoring object in the monitoring period, the high current value GL is a maximum value of a current value of the power supply line of the monitoring object in the monitoring period, and the process of obtaining the increased current value ZL includes: and obtaining the maximum value and the minimum value of the current value of the power supply line of the monitoring object, and marking the difference value between the maximum value and the minimum value of the current value of the power supply line as a current increasing value ZL.
As a preferred embodiment of the present invention, a specific process for determining whether a load state of a power distribution system in a monitoring period meets a requirement includes: the load threshold FZmax is acquired, and the load factor FZ of the monitored object in the monitoring period is compared with the load threshold FZmax: if the load factor FZ is smaller than the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; if the load factor FZ is greater than or equal to the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; marking the ratio of the number of the load-carrying objects to the number of the monitoring objects in the monitoring period as a load-carrying coefficient of the monitoring period, acquiring a load-carrying threshold value, and comparing the load-carrying coefficient with the load-carrying threshold value: if the load-different coefficient is smaller than the load-different threshold, judging that the load state of the power distribution system in the monitoring period meets the requirement; if the load abnormal coefficient is larger than or equal to the load abnormal threshold, judging that the load state of the power distribution system in the monitoring period does not meet the requirement, generating a load abnormal signal, sending the load abnormal signal to a risk assessment platform, and sending the load abnormal signal to a risk assessment module after the risk assessment platform receives the load abnormal signal.
As a preferred embodiment of the present invention, the noise data ZS is a maximum value of a noise decibel value generated when the monitoring object is running in the monitoring period, the peak-to-peak data YF is a peak value of a pressure wave generated when the monitoring object is running in the monitoring period, and the surface temperature data BW is a maximum value of a surface temperature value of the monitoring object in the monitoring period.
As a preferred embodiment of the present invention, the specific process of determining whether the arc risk of the power distribution system in the monitoring period meets the requirement includes: an arc threshold DHmax is obtained and the arc coefficient DH is compared to the arc threshold DHmax: if the arc coefficient DH is smaller than the arc threshold DHmax, marking the corresponding monitoring object as an arc positive object; if the arc coefficient DH is larger than or equal to the arc threshold DHmax, marking the corresponding monitoring object as an arc abnormal object; marking the number ratio of the arc abnormal objects to the monitoring objects as the arc abnormal coefficient of the monitoring period, acquiring an arc abnormal threshold value, and comparing the arc abnormal coefficient with the arc abnormal threshold value: if the arc difference coefficient is smaller than the arc difference threshold value, judging that the arc risk of the power distribution system in the monitoring period meets the requirement; if the arc abnormal coefficient is larger than or equal to the arc abnormal threshold value, judging that the arc risk of the power distribution system in the monitoring period does not meet the requirement, generating an arc abnormal signal and sending the arc abnormal signal to a risk assessment platform, and sending the arc abnormal signal to a risk assessment module after the risk assessment platform receives the arc abnormal signal.
As a preferred embodiment of the present invention, the specific process of the risk assessment module for assessing and analyzing the running risk of the power distribution system includes: when the risk assessment module receives the load abnormal signal and the arc abnormal signal at the same time, a fire risk signal is generated and sent to a mobile phone terminal of a manager through the risk assessment module; otherwise, the risk assessment module forwards the received abnormal signal to the mobile phone terminal of the manager through the risk assessment module.
As a preferred embodiment of the present invention, the acquisition process of the concentration coefficient of the monitoring object in the monitoring period includes: arranging all monitoring time periods of the monitoring object in a monitoring period according to the sequence of the load coefficient FZ from large to small to obtain a load sequence of the monitoring object, arranging all monitoring time periods of the monitoring object in the monitoring period according to the sequence of the arc coefficient DH from large to small to obtain an arc sequence of the monitoring object, marking the absolute value of the difference value between the serial number of the monitoring time period in the load sequence and the serial number of the arc sequence as a centralized value of the monitoring time periods, and summing and averaging the centralized values of all the monitoring time periods to obtain the centralized coefficient of the monitoring object.
As a preferred embodiment of the present invention, the specific process for determining whether the monitored object has an implicit risk in the monitoring period includes: acquiring a concentration threshold value, and comparing the concentration coefficient with the concentration threshold value: if the concentration coefficient is smaller than the concentration threshold value, judging that the monitored object does not have hidden risks in the monitoring period; if the concentration coefficient is greater than or equal to the concentration threshold, judging that the monitoring object has hidden risk in the monitoring period, marking the corresponding monitoring object as a maintenance object, and sending the equipment number of the maintenance object to a mobile phone terminal of a manager through a risk assessment platform.
The invention also provides a risk assessment method for the power distribution system, which comprises the following steps:
Step one: monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period; the load factor FZ of the monitored object in the monitoring period is obtained by carrying out numerical calculation on the linear temperature value XW, the high current value GL and the current increasing value ZL; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through a load coefficient FZ;
Step two: monitoring and analyzing arc risks of the power distribution system: acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period by carrying out numerical calculation on noise data ZS, peak-pressing data YF and table temperature data BW; judging whether the arc risk of the power distribution system in the monitoring period meets the requirement or not through an arc coefficient DH;
Step three: and when the load state of the power distribution system does not meet the requirement or has arc risk, carrying out evaluation analysis on the operation risk of the power distribution system, obtaining a concentration coefficient of the monitoring object in the monitoring period through the evaluation analysis, and judging whether the monitoring object has hidden risk in the monitoring period through the concentration coefficient.
The invention has the following beneficial effects:
The load risk of the power distribution system can be monitored and analyzed through the load monitoring module, the running parameters of the power distribution equipment in each monitoring period are obtained in a periodic monitoring mode, and after calculation, the load state of the power distribution equipment is monitored and evaluated through the load coefficient of the monitoring object, so that the overall load state of the power distribution system is fed back according to the number proportion of the different monitoring objects in the monitoring object;
the arc risk of the power distribution system can be monitored and analyzed through the arc monitoring module, and each arc risk parameter is comprehensively analyzed and calculated in a monitoring period to obtain an arc coefficient, so that the arc coefficients of all monitoring objects are integrated to feed back the overall arc risk of the power distribution system, and early warning is timely carried out when abnormality occurs;
The risk assessment module can be used for assessing and analyzing the running risk of the power distribution system, generating a corresponding early warning signal according to the abnormal signal received by the risk assessment module, analyzing and assessing the hidden risk of each monitoring object in the monitoring period, and marking and maintaining the power distribution equipment with the hidden risk; in more detail, the risk assessment module utilizes the concentration coefficient to analyze and assess each monitoring object in the monitoring period on the premise of the load abnormal signal generated by the load monitoring module and the arc abnormal signal generated by the arc monitoring module, so as to mark and maintain the power distribution equipment with hidden risks, and the risk assessment module is convenient to find the power distribution equipment with hidden risks in the risk assessment process of the power distribution system, thereby achieving the effect of improving the accuracy of the risk assessment result.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
Fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the present embodiment provides a risk assessment system for a power distribution system, including a risk assessment platform, where the risk assessment platform is communicatively connected with a load monitoring module, an arc monitoring module, a risk assessment module, and a storage module.
The load monitoring module is used for monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period, wherein the line temperature value XW is the maximum value of the surface temperature value of a power supply line of the monitoring object in the monitoring period, the high current value GL is the maximum value of the current value of the power supply line of the monitoring object in the monitoring period, and the acquisition process of the current increasing value ZL comprises the following steps: obtaining the maximum value and the minimum value of the current value of the power supply line of the monitoring object, and marking the difference value between the maximum value and the minimum value of the current value of the power supply line as a current increasing value ZL; obtaining a load factor FZ of a monitored object in a monitoring period through a formula FZ=α1xW+α2GL+α3ZL, wherein α1, α2 and α3 are all proportional coefficients, and α1> α2 > α3 > 1; the load threshold FZmax is obtained through the storage module, and the load coefficient FZ of the monitored object in the monitoring period is compared with the load threshold FZmax: if the load factor FZ is smaller than the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; if the load factor FZ is greater than or equal to the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; marking the ratio of the number of the load-carrying objects to the number of the monitoring objects in the monitoring period as a load-carrying coefficient of the monitoring period, acquiring a load-carrying threshold value through a storage module, and comparing the load-carrying coefficient with the load-carrying threshold value: if the load-different coefficient is smaller than the load-different threshold, judging that the load state of the power distribution system in the monitoring period meets the requirement; if the load difference coefficient is larger than or equal to the load difference threshold value, judging that the load state of the power distribution system in the monitoring period does not meet the requirement, generating a load abnormal signal and sending the load abnormal signal to a risk assessment platform, and sending the load abnormal signal to a risk assessment module after the risk assessment platform receives the load abnormal signal; and monitoring and analyzing the load risk of the power distribution system, acquiring the operation parameters of the power distribution equipment in each monitoring period in a periodical monitoring mode, and monitoring and evaluating the load state of the power distribution equipment through the load coefficient of the monitoring object after calculation, so that the overall load state of the power distribution system is fed back according to the number proportion of the different monitoring objects in the monitoring object.
The arc monitoring module is used for monitoring and analyzing the arc risk of the power distribution system: acquiring noise data ZS, peak-pressing data YF and surface temperature data BW of a monitored object at the end time of a monitoring period, wherein the noise data ZS is the maximum value of a noise decibel value generated when the monitored object operates in the monitoring period, the peak-pressing data YF is the peak value of a pressure wave generated when the monitored object operates in the monitoring period, and the surface temperature data BW is the maximum value of a surface temperature value of the monitored object in the monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period through a formula DH=β1×ZS+β2×YF+β3×BW, wherein β1, β2 and β3 are all proportional coefficients, and β1 > β2 > β3 > 1; the arc threshold DHmax is obtained by the storage module, and the arc coefficient DH is compared to the arc threshold DHmax: if the arc coefficient DH is smaller than the arc threshold DHmax, marking the corresponding monitoring object as an arc positive object; if the arc coefficient DH is larger than or equal to the arc threshold DHmax, marking the corresponding monitoring object as an arc abnormal object; marking the number ratio of the arc abnormal objects to the monitoring objects as the arc abnormal coefficient of the monitoring period, acquiring an arc abnormal threshold value through a storage module, and comparing the arc abnormal coefficient with the arc abnormal threshold value: if the arc difference coefficient is smaller than the arc difference threshold value, judging that the arc risk of the power distribution system in the monitoring period meets the requirement; if the arc difference coefficient is larger than or equal to the arc difference threshold value, judging that the arc risk of the power distribution system in the monitoring period does not meet the requirement, generating an arc abnormal signal and sending the arc abnormal signal to a risk assessment platform, and sending the arc abnormal signal to a risk assessment module after the risk assessment platform receives the arc abnormal signal; and (3) monitoring and analyzing the arc risk of the power distribution system, comprehensively analyzing and calculating each arc risk parameter in a monitoring period to obtain arc coefficients, and feeding back the whole arc risk of the power distribution system by integrating the arc coefficients of all monitoring objects, and early warning in time when abnormality occurs.
The risk assessment module is used for assessing and analyzing the running risk of the power distribution system: when the risk assessment module receives the load abnormal signal and the arc abnormal signal at the same time, a fire risk signal is generated and sent to a mobile phone terminal of a manager through the risk assessment module; otherwise, the risk assessment module forwards the received abnormal signal to a mobile phone terminal of a manager through the risk assessment module; arranging all monitoring periods of a monitoring object in a monitoring period according to the sequence of the load coefficient FZ from large to small to obtain a load sequence of the monitoring object, arranging all monitoring periods of the monitoring object in the monitoring period according to the sequence of the arc coefficient DH from large to small to obtain an arc sequence of the monitoring object, marking the absolute value of the difference value between the serial number of the monitoring period in the load sequence and the serial number of the arc sequence as a centralized value of the monitoring period, summing the centralized values of all the monitoring periods to obtain a centralized coefficient of the monitoring object, acquiring a centralized threshold value through a storage module, and comparing the centralized coefficient with the centralized threshold value: if the concentration coefficient is smaller than the concentration threshold value, judging that the monitored object does not have hidden risks in the monitoring period; if the concentration coefficient is greater than or equal to the concentration threshold value, judging that the monitoring object has hidden risk in the monitoring period, marking the corresponding monitoring object as a maintenance object, and sending the equipment number of the maintenance object to a mobile phone terminal of a manager through a risk assessment platform; the operation risk of the power distribution system is evaluated and analyzed, a corresponding early warning signal is generated according to the abnormal signal received by the risk evaluation module, meanwhile, the hidden risk of each monitoring object in the monitoring period is analyzed and evaluated, and the power distribution equipment with the hidden risk is marked and maintained, so that the accuracy of a risk evaluation result is improved;
The storage module is used for storing the threshold value of the power distribution system in the risk assessment process, and comparing the threshold value with the corresponding numerical value, wherein the threshold value specifically comprises a load threshold FZmax, a load different threshold value, an arc threshold DHmax, an arc different threshold value and a concentration threshold value.
The working principle of the risk assessment system for the power distribution system is that when the risk assessment system works, a monitoring period is generated and divided into a plurality of monitoring periods, power distribution equipment of the power distribution system is marked as a monitoring object, a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring periods are obtained, and a load coefficient FZ is obtained by carrying out numerical value calculation; marking a monitoring object as a load-carrying object or a load-carrying object through a load coefficient FZ, marking the ratio of the number of the load-carrying objects to the number of the monitoring objects in a monitoring period as a load-carrying coefficient of the monitoring period, and judging whether the load state of the power distribution system in the monitoring period meets the requirement through the load-carrying coefficient; acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period, and performing numerical calculation to obtain an arc coefficient DH; marking a monitoring object as an arc positive object or an arc abnormal object through an arc coefficient DH, marking the number ratio of the arc abnormal object to the monitoring object as an arc abnormal coefficient of a monitoring period, and judging whether the arc risk of the power distribution system in the monitoring period meets the requirement through the arc abnormal coefficient; and evaluating and analyzing the running risk of the power distribution system, obtaining a concentration coefficient of the monitoring object, and judging whether the monitoring object has hidden risk in the monitoring period or not through the concentration coefficient.
Example two
As shown in fig. 2, the present embodiment provides a risk assessment method for a power distribution system, including the following steps:
Step one: monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period; the load factor FZ of the monitored object in the monitoring period is obtained by carrying out numerical calculation on the linear temperature value XW, the high current value GL and the current increasing value ZL; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through a load coefficient FZ;
Specifically, marking a monitoring object as a load-carrying object or a load-carrying object through a load coefficient FZ, marking the ratio of the number of the load-carrying objects to the number of the monitoring objects in a monitoring period as a load-carrying coefficient of the monitoring period, and judging whether the load state of the power distribution system in the monitoring period meets the requirement through the load-carrying coefficient;
Step two: monitoring and analyzing arc risks of the power distribution system: acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period by carrying out numerical calculation on noise data ZS, peak-pressing data YF and table temperature data BW; judging whether the arc risk of the power distribution system in the monitoring period meets the requirement or not through an arc coefficient DH;
Specifically, marking a monitoring object as an arc positive object or an arc abnormal object through an arc coefficient DH, marking the number ratio of the arc abnormal object to the monitoring object as an arc abnormal coefficient of a monitoring period, and judging whether the arc risk of the power distribution system in the monitoring period meets the requirement through the arc abnormal coefficient;
Step three: and when the load state of the power distribution system does not meet the requirement or has arc risk, carrying out evaluation analysis on the operation risk of the power distribution system, obtaining a concentration coefficient of the monitoring object in the monitoring period through the evaluation analysis, and judging whether the monitoring object has hidden risk in the monitoring period through the concentration coefficient.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: the formula fz=α1 xw+α2 gl+α3 zl; collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding load coefficient for each group of sample data; substituting the set load coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 5.32, 3.17 and 2.85 respectively;
The size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding load coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the load factor is directly proportional to the value of the line temperature value.
The foregoing is merely illustrative and explanatory of the invention, as various modifications and additions may be made to the particular embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the scope of the invention.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention.
Claims (9)
1. A risk assessment system for a power distribution system, comprising a risk assessment platform, wherein the risk assessment platform is in communication connection with a load monitoring module, an arc monitoring module and a risk assessment module;
The load monitoring module is used for monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period; the load factor FZ of the monitored object in the monitoring period is obtained by carrying out numerical calculation on the linear temperature value XW, the high current value GL and the current increasing value ZL; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through a load coefficient FZ;
The arc monitoring module is used for monitoring and analyzing the arc risk of the power distribution system: acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period by carrying out numerical calculation on noise data ZS, peak-pressing data YF and table temperature data BW; judging whether the arc risk of the power distribution system in the monitoring period meets the requirement or not through an arc coefficient DH;
the risk assessment module is used for assessing and analyzing the operation risk of the power distribution system when the load state of the power distribution system does not meet the requirement or has arc risk, obtaining a concentration coefficient of a monitoring object in a monitoring period through the assessment and analysis, and judging whether the monitoring object has hidden risk in the monitoring period through the concentration coefficient.
2. The risk assessment system for a power distribution system according to claim 1, wherein the line temperature value XW is a maximum value of a surface temperature value of a power supply line of a monitoring object in a monitoring period, the high current value GL is a maximum value of a current value of the power supply line of the monitoring object in the monitoring period, and the obtaining process of the increased current value ZL includes: and obtaining the maximum value and the minimum value of the current value of the power supply line of the monitoring object, and marking the difference value between the maximum value and the minimum value of the current value of the power supply line as a current increasing value ZL.
3. A risk assessment system for a power distribution system according to claim 2 wherein the specific process of determining whether the load condition of the power distribution system during the monitoring period meets the requirements comprises: the load threshold FZmax is acquired, and the load factor FZ of the monitored object in the monitoring period is compared with the load threshold FZmax: if the load factor FZ is smaller than the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; if the load factor FZ is greater than or equal to the load threshold FZmax, marking the corresponding monitoring object as a load-carrying object; marking the ratio of the number of the load-carrying objects to the number of the monitoring objects in the monitoring period as a load-carrying coefficient of the monitoring period, acquiring a load-carrying threshold value, and comparing the load-carrying coefficient with the load-carrying threshold value: if the load-different coefficient is smaller than the load-different threshold, judging that the load state of the power distribution system in the monitoring period meets the requirement; if the load abnormal coefficient is larger than or equal to the load abnormal threshold, judging that the load state of the power distribution system in the monitoring period does not meet the requirement, generating a load abnormal signal, sending the load abnormal signal to a risk assessment platform, and sending the load abnormal signal to a risk assessment module after the risk assessment platform receives the load abnormal signal.
4. A risk assessment system for an electrical distribution system according to claim 3 wherein the noise data ZS is the maximum value of the noise decibel value generated when the monitoring object is running in the monitoring period, the peak pressure data YF is the peak value of the pressure wave generated when the monitoring object is running in the monitoring period, and the surface temperature data BW is the maximum value of the monitoring object surface temperature value in the monitoring period.
5. The risk assessment system for a power distribution system of claim 4, wherein the specific process of determining whether the arc risk of the power distribution system during the monitoring period meets the requirement comprises: an arc threshold DHmax is obtained and the arc coefficient DH is compared to the arc threshold DHmax: if the arc coefficient DH is smaller than the arc threshold DHmax, marking the corresponding monitoring object as an arc positive object; if the arc coefficient DH is larger than or equal to the arc threshold DHmax, marking the corresponding monitoring object as an arc abnormal object; marking the number ratio of the arc abnormal objects to the monitoring objects as the arc abnormal coefficient of the monitoring period, acquiring an arc abnormal threshold value, and comparing the arc abnormal coefficient with the arc abnormal threshold value: if the arc difference coefficient is smaller than the arc difference threshold value, judging that the arc risk of the power distribution system in the monitoring period meets the requirement; if the arc abnormal coefficient is larger than or equal to the arc abnormal threshold value, judging that the arc risk of the power distribution system in the monitoring period does not meet the requirement, generating an arc abnormal signal and sending the arc abnormal signal to a risk assessment platform, and sending the arc abnormal signal to a risk assessment module after the risk assessment platform receives the arc abnormal signal.
6. The risk assessment system for a power distribution system of claim 5, wherein the risk assessment module performs an assessment analysis of the operational risk of the power distribution system comprising: when the risk assessment module receives the load abnormal signal and the arc abnormal signal at the same time, a fire risk signal is generated and sent to a mobile phone terminal of a manager through the risk assessment module; otherwise, the risk assessment module forwards the received abnormal signal to the mobile phone terminal of the manager through the risk assessment module.
7. The risk assessment system for a power distribution system of claim 6, wherein the process of acquiring the concentration factor of the monitored subject during the monitoring period comprises: arranging all monitoring time periods of the monitoring object in a monitoring period according to the sequence of the load coefficient FZ from large to small to obtain a load sequence of the monitoring object, arranging all monitoring time periods of the monitoring object in the monitoring period according to the sequence of the arc coefficient DH from large to small to obtain an arc sequence of the monitoring object, marking the absolute value of the difference value between the serial number of the monitoring time period in the load sequence and the serial number of the arc sequence as a centralized value of the monitoring time periods, and summing and averaging the centralized values of all the monitoring time periods to obtain the centralized coefficient of the monitoring object.
8. The risk assessment system for a power distribution system of claim 7, wherein the specific process of determining whether the monitored object has an implicit risk during the monitoring period comprises: acquiring a concentration threshold value, and comparing the concentration coefficient with the concentration threshold value: if the concentration coefficient is smaller than the concentration threshold value, judging that the monitored object does not have hidden risks in the monitoring period; if the concentration coefficient is greater than or equal to the concentration threshold, judging that the monitoring object has hidden risk in the monitoring period, marking the corresponding monitoring object as a maintenance object, and sending the equipment number of the maintenance object to a mobile phone terminal of a manager through a risk assessment platform.
9. A risk assessment method for a power distribution system, the risk assessment method for a power distribution system using the risk assessment system for a power distribution system according to any one of claims 1 to 8, comprising the steps of:
Step one: monitoring and analyzing the load risk of the power distribution system: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, marking power distribution equipment of a power distribution system as a monitoring object, and acquiring a line temperature value XW, a high current value GL and a current increasing value ZL of the monitoring object in the monitoring period; the load factor FZ of the monitored object in the monitoring period is obtained by carrying out numerical calculation on the linear temperature value XW, the high current value GL and the current increasing value ZL; judging whether the load state of the power distribution system in the monitoring period meets the requirement or not through a load coefficient FZ;
Step two: monitoring and analyzing arc risks of the power distribution system: acquiring noise data ZS, peak-pressing data YF and table temperature data BW of a monitoring object at the end time of a monitoring period; obtaining an arc coefficient DH of a monitored object in a monitoring period by carrying out numerical calculation on noise data ZS, peak-pressing data YF and table temperature data BW; judging whether the arc risk of the power distribution system in the monitoring period meets the requirement or not through an arc coefficient DH;
Step three: and when the load state of the power distribution system does not meet the requirement or has arc risk, carrying out evaluation analysis on the operation risk of the power distribution system, obtaining a concentration coefficient of the monitoring object in the monitoring period through the evaluation analysis, and judging whether the monitoring object has hidden risk in the monitoring period through the concentration coefficient.
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