CN113128707A - Situation risk assessment method for distribution automation terminal - Google Patents
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Abstract
The invention relates to a situation risk assessment method for a distribution automation terminal, which comprises the steps of establishing a multidimensional influence factor system of the health state of the distribution automation terminal, establishing a multidimensional assessment index and an assessment model aiming at the distribution automation terminal, and calculating an assessment standard of the model to obtain an assessment result; and calculating the occurrence probability and the possible loss of the risk and the risk to obtain a risk value and an evaluation result. According to the risk assessment method, the comprehensive risk dynamics of the fuzziness and the randomness of the power distribution automation terminal faults are considered, the risk assessment is carried out on the power distribution automation terminal by introducing a quantitative risk value method through a credibility theory, the risk assessment method considering the randomness and the fuzziness of the component faults at the same time is provided, and the comprehensive risk assessment index of the operation of the power distribution automation system is given. The method and the system can timely find hidden dangers existing in the operation of the distribution automation terminal, early warning and processing are achieved, the terminal is enabled to be in a normal state from a fault, and the power supply reliability of a distribution network is remarkably improved.
Description
Technical Field
The invention belongs to the field of power distribution internet of things equipment state evaluation, and particularly relates to a power distribution automation terminal situation risk assessment method.
Background
Due to the difficulties of multiple complex factors, fast change of system situation, multiple uncertainty indexes, multiple nonlinear relations among factors and the like existing in the operation of the power distribution network, the comprehensive assessment and prediction difficulty of the operation risk of the power distribution network is high. At present, research on real-time evaluation of the operation risk of the power distribution network mainly focuses on the aspects of real-time load prediction, power grid short-circuit fault, cascading fault sending model and other static research and prediction of single risk source, and the research on real-time and dynamic risk evaluation of the operation comprehensive index of the whole power distribution network is less. The existing research methods for power distribution network operation risk assessment include traditional comprehensive risk assessment methods based on a hierarchical analysis method, a fuzzy comprehensive evaluation method, a grey correlation analysis method and the like, hidden dangers existing in the operation of a power distribution automation terminal cannot be found in time, early warning and early processing are achieved, and the power supply reliability of a distribution network is difficult to guarantee.
For the situation risk assessment of the distribution automation terminal, the existing method aims to calculate the state of the distribution secondary equipment and does not consider the multidimensional influence of the state of the distribution automation terminal, so that the establishment of a multidimensional assessment index system of the state of the distribution automation terminal is not complete, and the finally calculated state result of the distribution secondary equipment is not accurate enough.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a situation risk assessment method for a distribution automation terminal, which can predict hidden dangers of the distribution automation terminal based on multi-dimensional influence of the state of the distribution automation terminal, and can perform early warning and advanced processing.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
a situation risk assessment method for a power distribution automation terminal comprises the following steps:
step 1: researching and analyzing monitoring information required by state maintenance of various distribution automation terminals, and determining multidimensional influence factors of the state of the distribution automation terminals;
step 2: establishing a multi-dimensional evaluation index system of the state of the distribution automation terminal by combining the multi-dimensional influence factors of the distribution automation equipment;
and step 3: establishing a mapping relation between multidimensional influence factors and a multidimensional evaluation index system, and constructing a power distribution automation terminal situation multidimensional comprehensive evaluation model;
step 4, calculating, classifying and summarizing evaluation criteria of the power distribution automation terminal situation multi-dimensional comprehensive evaluation model to obtain an evaluation result;
step 5, according to the evaluation result, comprehensively calculating the occurrence probability and possible loss of the power distribution automation terminal fault, evaluating the risk value of the power distribution automation terminal, and obtaining a risk evaluation result;
step 6, dividing risk levels according to the risk values of the power distribution network, and matching corresponding risk levels according to risk evaluation results and specific conditions;
and 7, carrying out early warning processing on the terminal power distribution automatic terminal according to the risk grade obtained in the step 6.
Moreover, the multidimensional influencing factors of the distribution automation terminal state in the step 1 include: the equipment self running state factor, the time factor, the environment factor and the maintenance history.
Moreover, the operating state factors of the device comprise: a key hardware state, a direct current power supply state and a secondary loop state; the critical hardware states include: a power plug-in status; CPU plug-in state, remote measuring plug-in state, remote signalling plug-in state and remote control plug-in state; the secondary loop state includes: telemetering loop state, remote signaling loop state and remote control loop state; the time factors include: the new and old degree and the operating life of the equipment; the environmental factors include: temperature changes and humidity changes; the service history includes: family defects, number of overhauls, and failure occurrence history.
And in the step 2, a multi-dimensional evaluation index system of the state of the distribution automation terminal is established by combining online real-time information and offline input information.
Moreover, the online real-time information mode is that the health condition of the distribution automation terminal is reflected in real time by collecting the self real-time self-checking information and the environmental state information of the distribution automation terminal; the offline information input mode reflects the time history state and the familial health state of the distribution automation terminal through the inspection record and the maintenance history data.
Moreover, the specific implementation method of the step 4 is as follows: and according to the comprehensive online grading and offline grading results, obtaining a comprehensive evaluation result of the situation of the distribution automation terminal by using the online grading weight accounting for 60% and the offline grading weight accounting for 40%.
Moreover, the comprehensive evaluation result of the situation of the distribution automation terminal is divided into: serious abnormality, attention, normality and goodness, wherein the comprehensive score is 0-59 for serious abnormality, 60-74 for abnormality, 75-84 for attention, 85-94 for normality and 95-100 for goodness.
Moreover, the specific implementation method of step 5 is as follows: fitting the discrete corresponding points into a correlation curve of the distribution automation terminal situation and the average fault probability according to the corresponding relation between the distribution automation terminal operation situation and the fault occurrence probability, and fitting the distribution automation terminal average fault probability by adopting a negative exponential curve
S is a simplified calculation quantization value corresponding to the situation evaluation result of the distribution automation terminal, K is a proportionality coefficient, C is a curvature coefficient, N is a situation grade determined according to the situation evaluation method, and M is a situation grade determined according to the situation evaluation methodiThe number of the distribution automation terminals corresponding to each grade in the evaluation period is Q, and the number of the fault terminals in the evaluation period is Q.
Moreover, the specific implementation method of step 6 is as follows: the risk loss amount of the distribution automation terminal at the moment t is as follows:
wherein R is a risk value,
the method is characterized in that the average failure probability is adopted, L is a failure possible loss value, t is a certain moment, when R (t) is more than or equal to 1, the risk level I is used for indicating that the operation of the distribution automation terminal is in a dangerous situation, and the risk level is high and is represented by red; when 0.5 is not more than R (t)<1 hour, use II level risk to show distribution automation terminal fortuneThe row is in an alert state, the risk level is higher, and the row is represented by yellow; when 0.1 is not more than R (t)<At 0.5, the level III risk indicates that the distribution automation terminal is operating in a safe range, and the risk level is lower and is represented by green.
The invention has the advantages and positive effects that:
the evaluation result is obtained by calculating the evaluation standard of the situation of the distribution automation terminal; and calculating the occurrence probability and the possible loss of the risk value to obtain a risk value and an evaluation result, and finally obtaining a risk grade matched with the risk value and the evaluation result. According to the method, the risk evaluation is performed on the distribution automation terminal by considering the comprehensive risk dynamics of the fuzziness and the randomness of the distribution automation terminal fault occurrence and introducing the quantitative risk value through the credibility theory, the risk evaluation method considering the randomness and the fuzziness of the element fault simultaneously is provided, the comprehensive risk evaluation index of the distribution automation system operation is given, the hidden danger existing in the distribution automation terminal operation is found in time, early warning and advanced treatment are achieved, the terminal distribution automation terminal is adjusted to be in a normal state from the states of fault, recovery, emergency and the like, and the power supply reliability of the distribution network can be remarkably improved.
Drawings
Fig. 1 is a multidimensional influence factor analysis diagram of a distribution automation terminal state;
fig. 2 is a schematic structural diagram of a multi-dimensional evaluation index system of a distribution automation terminal state.
FIG. 3 is a diagram of a distribution automation FA test system according to the present invention;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
A situation risk assessment method for a power distribution automation terminal comprises the following steps:
step 1: and researching and analyzing monitoring information required by state maintenance of various distribution automation terminals, and determining multidimensional influence factors of the state of the distribution automation terminals.
As shown in fig. 1, the multidimensional influencing factors of the distribution automation terminal state include: the equipment self running state factor, the time factor, the environment factor and the maintenance history.
The operating state factors of the equipment comprise: a critical hardware state, a dc power state, and a secondary loop state. Further, the key hardware states include: a power plug-in status; CPU plug-in state, remote sensing plug-in state, remote signaling plug-in state and remote control plug-in state. The secondary loop states include: telemetering loop state, remote signaling loop state and remote control loop state;
the time factors include: the new and old degree and the operating life of the equipment;
environmental factors include: temperature changes and humidity changes;
the service history covers family defects, the number of service times and the history of fault occurrences.
Step 2: and establishing a multi-dimensional evaluation index system of the state of the distribution automation terminal by combining the multi-dimensional influence factors of the distribution automation equipment.
As shown in fig. 2, starting from the basic requirements of SMART criteria, a multi-dimensional influence factor of the distribution automation equipment is combined to establish a multi-dimensional evaluation index system of the distribution automation terminal state, and a mode of combining online real-time information and offline entry information is adopted.
The online real-time information mode is to reflect the health condition of the distribution automation terminal in real time by collecting the self real-time self-checking information and the environmental state information of the distribution automation terminal.
The offline information input mode reflects the time history state and the familial health state of the distribution automation terminal through the inspection record and the maintenance history data.
And step 3: and establishing a mapping relation between the multidimensional influence factors and multidimensional evaluation indexes, and establishing a multidimensional comprehensive evaluation model of the state of the power distribution automation terminal.
And establishing a mapping relation between the multidimensional influence factors and multidimensional evaluation indexes, and constructing a power distribution automation terminal state multidimensional comprehensive evaluation model from a time dimension, a space dimension, an object dimension and a phenomenon dimension. In order to determine the state of the distribution automation terminal, the measured values characterizing the state of the equipment need to be compared with corresponding standards, and corresponding state thresholds, i.e. alarm thresholds, should also be given. And establishing a comprehensive evaluation model of the state of the power distribution automation terminal through three-level evaluation of online grading, offline grading and comprehensive grading.
The method for constructing the multi-dimensional comprehensive evaluation model of the state of the power distribution automation terminal specifically comprises the following steps: establishing an online grading model, establishing an offline grading model and establishing a comprehensive grading model.
As shown in table one, the evaluation criteria are the online status self-test information of the distribution automation terminal. The online grading model is used for grading online state self-checking information, the online state self-checking information grading standard is obtained by adjusting parameter values in the data model according to a data model provided by an equipment manufacturer and by combining experience of actual field operation and calculating according to actual values of analog quantity or statistical information provided by the distribution automation terminal device.
Watch 1
And as shown in the second table, the power distribution automation terminal is scored based on the off-line information. The off-line grading model is used for off-line grading, the off-line grading standard is adjusted according to information provided by a power distribution automation terminal manufacturer and by combining with actual field operation experience, and then the off-line grading standard is calculated according to actual conditions of regular inspection, test and routing inspection.
Watch two
And 4, calculating, classifying and summarizing the evaluation standard of the distribution automation terminal situation multi-dimensional comprehensive evaluation model to obtain the evaluation result.
The specific implementation method of the step is as follows: and according to the comprehensive online grading and offline grading results, obtaining a comprehensive evaluation result of the situation of the distribution automation terminal by using the online grading weight accounting for 60% and the offline grading weight accounting for 40%.
The comprehensive evaluation result of the situation of the power distribution automation terminal is divided into: severe abnormalities, attention, normality, well, composite score criteria are shown in table three.
Watch III
And 2, comprehensively calculating the occurrence probability and the possible loss of the power distribution automation terminal fault according to the evaluation result, evaluating the risk value of the power distribution automation terminal, and obtaining a risk evaluation result.
The specific implementation method of the step is as follows: fitting the discrete corresponding points into a correlation curve of the distribution automation terminal situation and the average fault probability according to the corresponding relation between the distribution automation terminal operation situation and the fault occurrence probability, and fitting the distribution automation terminal average fault probability by adopting a negative exponential curve
S is a simplified calculation quantization value corresponding to the situation evaluation result of the distribution automation terminal, K is a proportionality coefficient, C is a curvature coefficient, N is a situation grade determined according to the situation evaluation method, and M is a situation grade determined according to the situation evaluation methodiThe number of the distribution automation terminals corresponding to each grade in the evaluation period is Q, and the number of the fault terminals in the evaluation period is Q.
And 3, dividing the risk level according to the risk value of the power distribution network, and matching the corresponding risk level according to the risk evaluation result and the specific situation.
The risk value in this step is determined by the average failure probability of the distribution automation terminal and the loss that may cause, and the distribution automation terminal risk loss uses the quantized risk value as an index, not only the probability that the distribution automation terminal breaks down is considered, but also the assets that may be lost due to the distribution automation terminal failure are considered, and the risk loss amount of the distribution automation terminal at the moment t is obtained:
wherein R is a risk value,
and the average failure probability is obtained, L is a failure possible loss value, t is a certain moment, after the risk evaluation of the distribution automation terminal is completed, the risk grading is given to the current operation condition of the distribution automation terminal, and different colors are respectively used for marking according to possible harm degrees so as to achieve the aim of being more visual. The influence and the hazard degree of the risk are distinguished according to the size, and the risk is divided into three grades, namely I grade, II grade and III grade according to the actual influence range of the distribution automation terminal. The distribution automation terminal risk classification is shown in table four.
Watch four
| Risk level flag | Red colour | Yellow colour | Green colour |
| Risk level classification | Class I | Class II | Class III |
| Risk value R | R≥1 | 0.5≤R<1 | 0.1≤R<0.5 |
And 4, carrying out early warning processing on the terminal power distribution automation terminal according to the risk grade obtained in the step 3.
According to the situation risk assessment method for the distribution automation terminal, a typical FA fault handling hand-ring network distribution automation test system is taken as an example to verify an overhaul model. If the FTU at the position of the section switch A5 breaks down before the next scheduled maintenance, a fault signal cannot be sent, and the loss of power of 5-6 of the load is caused; if the FTU at the position of the interconnection switch A6 sends a fault before the next scheduled maintenance, the FTU cannot receive a load transfer signal, and the downstream area of the fault point cannot recover power supply, so that the loads 5-6 and 7-9 lose power loss, and the loss caused when the terminal at the position of the interconnection switch breaks down is larger.
And selecting a line for constructing feeder automation in an actual distribution automation system in a certain area as an example, and counting the corresponding operating load condition, as shown in the table five.
Watch five
| Load point | Type of user | Average load (MW) | Maximum load (MW) | Load rating |
| 1～2 | Residential user | 1.67 | 2.14 | 3 |
| 3 | Residential user | 0.93 | 1.45 | 3 |
| 5～6 | Industrial user | 0.81 | 1.22 | 3 |
| 7～9 | Industrial user | 1.15 | 1.86 | 2 |
| 10～12 | Government organization | 0.78 | 1.19 | 3 |
| 13～15 | Business user | 0.85 | 1.35 | 3 |
And (4) inquiring relevant standards of distribution automation and maintenance technology guide rules, and combining historical maintenance records of the area to obtain various expenses of maintenance projects, and calculating maintenance cost. The distribution terminal takes the FTU as an example, and calculates the FTU fault loss cost and the overhaul cost at the interconnection switch a6 and the section switch a5, respectively, as shown in table six, the fault loss calculation result of the distribution automation terminal is shown, as shown in table seven, the overhaul cost calculation result is shown, and the fault loss calculation process is shown in fig. 3.
Watch six
Watch seven
Assuming that the comprehensive situation quantitative scores of the switches A5 and A6 under the normal situation are all 80 points, the corresponding average failure rate is 2.5%, the planned maintenance is carried out in 15 days per month, the actual cost curve relationship can be obtained by continuously calculating the daily maintenance cost and the daily failure risk cost of 1-30 days per month, and the corresponding time of the intersection point of the two curves is the optimal situation maintenance date. The calculated optimal situation overhaul dates of the A5 switch and the A6 switch are 23 and 9 respectively, namely the optimal overhaul time is the optimized overhaul time, and after the optimized overhaul is indirect, the fault risk cost exceeds the overhaul cost, so that overhaul is carried out at the optimal time, the overhaul cost can be controlled at a lower level, and the fault risk is prevented from being further aggravated. The economic and reliable combination is realized, and the finally obtained optimized maintenance decision is obtained.
It should be emphasized that the embodiments described herein are illustrative rather than restrictive, and thus the present invention is not limited to the embodiments described in the detailed description, but also includes other embodiments that can be derived from the technical solutions of the present invention by those skilled in the art.
Claims (9)
1. A situation risk assessment method for a power distribution automation terminal is characterized by comprising the following steps: the method comprises the following steps:
step 1: researching and analyzing monitoring information required by state maintenance of various distribution automation terminals, and determining multidimensional influence factors of the state of the distribution automation terminals;
step 2: establishing a multi-dimensional evaluation index system of the state of the distribution automation terminal by combining the multi-dimensional influence factors of the distribution automation equipment;
and step 3: establishing a mapping relation between multidimensional influence factors and a multidimensional evaluation index system, and constructing a power distribution automation terminal situation multidimensional comprehensive evaluation model;
step 4, calculating, classifying and summarizing evaluation criteria of the power distribution automation terminal situation multi-dimensional comprehensive evaluation model to obtain an evaluation result;
step 5, according to the evaluation result, comprehensively calculating the occurrence probability and possible loss of the power distribution automation terminal fault, evaluating the risk value of the power distribution automation terminal, and obtaining a risk evaluation result;
step 6, dividing risk levels according to the risk values of the power distribution network, and matching corresponding risk levels according to risk evaluation results and specific conditions;
and 7, carrying out early warning processing on the terminal power distribution automatic terminal according to the risk grade obtained in the step 6.
2. The power distribution automation terminal situation risk assessment method according to claim 1, characterized in that: the multidimensional influence factors of the distribution automation terminal state in the step 1 comprise: the equipment self running state factor, the time factor, the environment factor and the maintenance history.
3. The power distribution automation terminal situation risk assessment method according to claim 2, characterized in that: the running state factors of the equipment comprise: a key hardware state, a direct current power supply state and a secondary loop state; the critical hardware states include: a power plug-in status; CPU plug-in state, remote measuring plug-in state, remote signalling plug-in state and remote control plug-in state; the secondary loop state includes: telemetering loop state, remote signaling loop state and remote control loop state; the time factors include: the new and old degree and the operating life of the equipment; the environmental factors include: temperature changes and humidity changes; the service history includes: family defects, number of overhauls, and failure occurrence history.
4. The power distribution automation terminal situation risk assessment method according to claim 1, characterized in that: and 2, establishing a multi-dimensional evaluation index system of the state of the distribution automation terminal in the step 2 by adopting a mode of combining online real-time information and offline input information.
5. The power distribution automation terminal situation risk assessment method according to claim 4, characterized in that: the online real-time information mode is that the health condition of the distribution automation terminal is reflected in real time by collecting self real-time self-checking information and environmental state information of the distribution automation terminal; the offline information input mode reflects the time history state and the familial health state of the distribution automation terminal through the inspection record and the maintenance history data.
6. The power distribution automation terminal situation risk assessment method according to claim 4, characterized in that: the specific implementation method of the step 4 comprises the following steps: and according to the comprehensive online grading and offline grading results, obtaining a comprehensive evaluation result of the situation of the distribution automation terminal by using the online grading weight accounting for 60% and the offline grading weight accounting for 40%.
7. The power distribution automation terminal situation risk assessment method according to claim 6, characterized in that: the situation comprehensive evaluation result of the distribution automation terminal is divided into: serious abnormality, attention, normality and goodness, wherein the comprehensive score is 0-59 for serious abnormality, 60-74 for abnormality, 75-84 for attention, 85-94 for normality and 95-100 for goodness.
8. The power distribution automation terminal situation risk assessment method according to claim 1, characterized in that: the specific implementation method of the step 5 is as follows: fitting the discrete corresponding points into a correlation curve of the distribution automation terminal situation and the average fault probability according to the corresponding relation between the distribution automation terminal operation situation and the fault occurrence probability, and fitting the distribution automation terminal average fault probability by adopting a negative exponential curve
Wherein S is a simplified calculation quantitative value corresponding to the situation evaluation result of the distribution automation terminalK is a proportionality coefficient, C is a curvature coefficient, N is a situation grade determined according to a situation evaluation method, MiThe number of the distribution automation terminals corresponding to each grade in the evaluation period is Q, and the number of the fault terminals in the evaluation period is Q.
9. The power distribution automation terminal situation risk assessment method according to claim 1, characterized in that: the specific implementation method of the step 6 comprises the following steps: the risk loss amount of the distribution automation terminal at the moment t is as follows:
wherein R is a risk value,
the method is characterized in that the average failure probability is adopted, L is a failure possible loss value, t is a certain moment, when R (t) is more than or equal to 1, the risk level I is used for indicating that the operation of the distribution automation terminal is in a dangerous situation, and the risk level is high and is represented by red; when 0.5 is not more than R (t)<When 1, indicating that the operation of the distribution automation terminal is in an alert state by using II-level risks, wherein the risk level is higher and is represented by yellow; when 0.1 is not more than R (t)<At 0.5, the level III risk indicates that the distribution automation terminal is operating in a safe range, and the risk level is lower and is represented by green.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114157034A (en) * | 2021-12-08 | 2022-03-08 | 国网四川省电力公司电力科学研究院 | Comprehensive monitoring method for multidimensional state of distribution automation terminal |
| CN114285592A (en) * | 2021-11-08 | 2022-04-05 | 国网浙江省电力有限公司宁波供电公司 | Security scoring and judging method for distribution automation terminal |
| CN117974071A (en) * | 2024-03-29 | 2024-05-03 | 杭州欣美成套电器制造有限公司 | Electric power system intelligent management method and device based on multidimensional analysis |
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| CN117974071A (en) * | 2024-03-29 | 2024-05-03 | 杭州欣美成套电器制造有限公司 | Electric power system intelligent management method and device based on multidimensional analysis |
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