CN110346673A - It is a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology - Google Patents
It is a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology Download PDFInfo
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- CN110346673A CN110346673A CN201910436834.XA CN201910436834A CN110346673A CN 110346673 A CN110346673 A CN 110346673A CN 201910436834 A CN201910436834 A CN 201910436834A CN 110346673 A CN110346673 A CN 110346673A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
Abstract
The invention discloses a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology, it is determined including probability of malfunction diagnostic module, network topology reasonable evaluation module and the real-time value-at-risk of distribution system, using real-time prevention and control as target, from two levels of reasonability of the probability of malfunction of power distribution network main equipment and network topology structure, it chooses risk indicator and carries out quantization scheme design, application level analytic approach is planned as a whole to formulate each level index weights, the degree of risk of overall merit power distribution network operation.The present invention perfect assessment to distribution network system risk operating status of the severity of failure effect under heterogeneous networks topological structure by identification, facilitate the severity of frequent degree and failure effect that comprehensive consideration power distribution network breaks down, obtain the real-time value-at-risk of power distribution network, guidance is provided for subsequent control measure, is conducive to evade high risk equipment, strengthens the ability that power distribution network resists failure.
Description
Technical field
The invention belongs to power distribution network self-healing control and power system automation technology fields, are related to power distribution network risk assessment,
Specifically a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology.
Background technique
Power distribution network is located at electric system end, is the weight for being directly connected and distributing to user electric energy in electric system with user
Want link.According to statistics, the power-off event for occurring to be caused by distribution network failure accounts about the eight of electric power system fault stoppage in transit accident
At.Electric system power outage takes targetedly control to arrange there is state deteriorating, the increased evolving development process of risk
Apply the probability that can be effectively reduced power outage generation and loss.The construction of intelligent distribution network and real-time security monitoring technology
It continues to develop, carries out preventative adjustment before serious accident occurs for power grid, speedy recovery to health operating status provides firmly
Part basis, and assessment real-time to the operation risk of power distribution network, accurate is then the premise for implementing effective prevention and control.
The intelligent distribution network complicated network structure, device category is more, quantity is big, dispersion is wide, and the method for operation is changeable, and vulnerable to
The influence of various external factor causes risk assessment to be related to factor numerous, it is difficult to which careful quantization obtains accurate risk assessment knot
Fruit.The value-at-risk of system is the comprehensive consideration of probability of malfunction possibility and failure effect severity as a result, current power distribution network
Risk multi-panel is evaluated to equipment dependability, considers the factors such as external environment or system running state to the shadow of equipment outage probability
It rings, but considers deficiency with regard to its system network topology structure itself is rational, be unable to satisfy and power distribution network is instructed to run and control
It needs.
Summary of the invention
The technical problems to be solved by the present invention are: provide it is a kind of meter and the rational intelligent distribution network risk of network topology
Appraisal procedure, by the selection to power distribution network real time execution risk indicator, to probability of equipment failure and network topology reasonability into
Row comprehensive assessment.
The technical solution that the present invention is taken in order to solve the technical problem is as follows:
It is a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology, include the following steps:
(1) probability of malfunction diagnostic module: quantitatively evaluating is carried out to the risk operating status of equipment, recognizes the high failure of power distribution network
Probability electrical equipment；
(2) network topology reasonable evaluation module: quantitatively evaluating is carried out to the reasonability of network topology, realizes Judging fault
The more serious network topology structure of consequence；
(3) the real-time value-at-risk of distribution system determines: application level analytic approach is planned as a whole to formulate each level index weights, calculates event
Hinder probability risk value and network topology score value, said two devices are taken into real-time value-at-risk of the product as distribution system.
The probability of malfunction diagnostic module: the failure stoppage in transit of controller switching equipment is the principal element for causing power distribution network power loss,
Therefore using the main electrical equipment in power distribution network: as research object, diagnosis power distribution network breaks down general for transformer and distribution line
Rate；It is codetermined in terms of wherein the operation risk of main electrical equipment is by ontology factor, external factor and historical record three；
(1) ontology factor:
Ontology factor refers to the operating condition and health degree of electrical equipment itself, is divided into electrical figureofmerit and refers to non-electric quantity
Two aspect of mark；
Electrical figureofmerit refers to the load current and voltage level at electrical equipment current time, equipment operate in overload or
The case where voltage out-of-limit, will lead to equipment protection tripping and cause fault outage；
Define equipment overload value-at-risk ROD, according to the overload risk journey for the size of current valuator device for flowing through equipment
Degree, when device current is less than or equal to the 80% of rated current, risk probability 0；With the increase for flowing through device current,
Risk probability increases, and speedup exponentially type up-trend；Equipment overload value-at-risk RODCalculation formula:
In formula, I is the electric current per unit value for flowing through equipment；λIFor the out-of-limit risk probability coefficient of electric current；
Define equipment voltage limit risk value RLV, bus voltage rating is set as 1.0p.u., when equipment voltage is in specified
When in ± 3% range of value, risk probability 0；With the increase for deviateing bus nominal voltage number, risk probability increases, and
Speedup exponentially type up-trend；Equipment voltage limit risk value RLVCalculation formula:
In formula, V is node current voltage per unit value, λVFor voltage limit risk probability coefficent；
Non-electric quantity index refers to the physicochemical property of electrical equipment, according to equipment practical operation situation, to transformer, distribution
Route is chosen different risk indicators and is analyzed；For transformer, by whether oil temperature situation, winding deform, casing connects
The own healths indexs such as line leader temperature, which are included in, considers range, the main transformer health indicator that value-at-risk setting is provided referring to professional standard
Data；For distribution line, its integrated degree being included in and considers range, value-at-risk is set referring to daily line walking data result, if
It finds that the case where distribution line damages increases route value-at-risk in time in line walking, is that transfer is negative in subsequent precautionary measures
Lotus to the lesser route of risk provides technological guidance；
(2) external factor:
External factor refers to influence of the terrible weather environment to equipment such as distribution line, transformers, by temperature, rainfall, wind
The factors such as speed determine that urban power distribution network is equipped with the devices such as microclimate station in different zones mostly, the meteorology according to observation device
Data, real-time assessment equipment are presently in the severe degree of meteorological condition；
Temperature factor: the raising of environment temperature generally can lead to transformer life since transformer heat dissipation in platform area is insufficient
Shorten, loss becomes larger, so that probability of malfunction be caused to increase；According to operating experience, temperature factor risk indicator RTCalculation formula:
In formula, λ is temperature risk factor, and T is this area's real time environment temperature；
Rainfall factor: the increase of rainfall can change the insulating sleeve dielectric loss constant of transformer or route, to be easy to
Cause insulation breakdown, leads to the generation of the dangerous situations such as equipment leakage；According to operating experience, temperature factor risk indicator RRIt calculates
Formula:
In formula, λR1、λR2Respectively rainfall failure risk coefficient, D are the real-time rainfall in this area；
Wind speed factor: wind speed is defined as apart from ground 10m height, the duration be 10min be in fashion into average speed
Degree；Overhead transmission line, which is easy to happen pole collapse accident, when wind-force is larger influences system safe and reliable operation, the extent of the destruction and frame of wind-force
Distance dependent of the ceases to be busy road away from wind regime center；According to statistics experience, wind speed factor risk index RWCalculation formula:
In formula, λWIt is expressed as wind-force failure risk coefficient；Corresponding to wind direction to the shadow of route wind load
It rings；Angle between wind direction and route；A is the severity parameter for describing wind-force；(x, y) is place on line；(μx,
μy) where maximum wind power at；σx、σyThe respectively calculating parameter of wind load is related to windage radius；
(3) historical record:
Historical record refers to the bad log of equipment: the failure of insulation ag(e)ing caused by such as equipment Years Of Service is longer is asked
Topic, the record of bad behavior problem of the faulty maintenance of equipment and with the familial defect problem occurred in producer's volume production equipment, these
In the case of think that the probability of device fails is higher, the probability of malfunction value-at-risk of equipment increases.
The network topology reasonable evaluation module: Consequential Loss and network topology caused by distribution network failure it is reasonable
Property it is directly related, reasonable network topology structure make power distribution network have stronger fault ride-through capability, can after electric network fault
It promptly isolates failure and reduces the power loss of power consumer as far as possible, therefore lost from load transfer ability, trouble isolation serviceability and load
Start in terms of electric rate three, overall merit carried out to the network topology reasonability of power distribution network:
(1) load transfer ability:
Power loss load is turned the ability supplied by other backup power sources after load transfer ability refers to electric network fault, by interconnection between standing
Ratio, middle pressure interconnection ratio codetermine；
What interconnection ratio reflected between standing is a possibility that carrying out load transfer between power distribution network different substation；Middle pressure connection
The reflection of winding thread ratio is a possibility that carrying out load transfer between pressing feeder line in power distribution network；
(2) trouble isolation serviceability:
Trouble isolation serviceability, which refers to, carries out ability of the isolation control in minimum zone for failure, from route be averaged segments,
Automatism isolation technology coverage rate, intelligent switch are averagely segmented three aspect assessments of capacity, and the above three is power distribution network itself
Attribute is responsible for offer by related technical personnel；
(3) load power loss rate:
Load power loss rate, which refers to break down under current grid structure, causes the ratio of load power loss, from energy loss angle into
Row assessment, rate of energy loss calculation formula are as follows:
In formula, P indicates the impacted load that breaks down；PLOSTIt indicates not turned for load.
The real-time value-at-risk of the distribution system determines: the modeling of application level analytic approach carries out weight to the index of each level
Degree comparative analysis is wanted, Judgement Matricies simultaneously carry out consistency check, formulate the weighted value of each level index；By index risk
It is worth weighted accumulation, as probability of malfunction value-at-risk and network topology score value, said two devices take reality of the product as distribution system
When value-at-risk.Distribution system operation risk value WSCalculation formula:
WS=∑ (Ri×αi)×∑(Rj×βj)
In formula, RiFor each index value-at-risk of probability of malfunction diagnosis system；αiFor each index weights of probability of malfunction diagnosis system
Value；RjFor each index value-at-risk of network topology evaluation system；βjFor each index weights of network topology evaluation system.
The beneficial effects of the present invention are:
The invention proposes a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology, by establishing event
Barrier probabilistic diagnosis and network topology evaluation index system, the frequent degree and severity of comprehensive consideration distribution network failure, accurately
The real time execution risk of power distribution network is assessed, provides basis to implement prevention and control measure, is conducive to evade high risk equipment, strengthens distribution
Net resists the ability of failure.
Detailed description of the invention:
Fig. 1 is flow chart of the invention；
Fig. 2 is probability of malfunction diagnosis system figure in the present invention；
Fig. 3 is network topology reasonable evaluation system figure in the present invention；
Fig. 4 is power distribution network simulation model figure of the invention.
Specific embodiment
The present invention is further illustrated with example with reference to the accompanying drawing:
Embodiment 1, a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology, comprising the following steps:
Step 1: distribution network Load flow calculation data are substituted into formula, the out-of-limit risk of the electrical quantity of calculating transformer and route
Value；And the equipment health Evaluation result by overhauling department obtains the value-at-risk of equipment non-electric quantity；
Step 2: nearly one hour weather index, quantitative analysis temperature, rainfall are obtained according to the statistical data at microclimate station
The influence of amount and wind speed to power distribution network, obtains value-at-risk；
Step 3: the data over the years according to provided by maintenance department obtain risk to the historical factor overall merit of equipment
Value；
Step 4: using analytic hierarchy process (AHP) to " ontology factor " " external factor " and " history in probability of malfunction diagnosis system
Factor " three parts index is planned as a whole to formulate weight, calculates probability of equipment failure value-at-risk；
Step 5: analyzing interconnection and middle pressure interconnection ratio between the station of grid structure, calculate distribution network load and turn energy supply
Force estimation value；
Step 6: as provided by relevant departments " route be averaged segments " " automatism isolation technology coverage rate " " intelligently melts
Close and be averagely segmented capacity ", quantitative analysis is carried out to equipment self attributes, calculates trouble isolation serviceability value；
Step 7: rate of energy loss being calculated according to formula, obtains the load power loss rate under current grid structure；
Step 8: using analytic hierarchy process (AHP) to " load transfer ability " " trouble isolation serviceability " in network topology evaluation system
And " load power loss rate " two-part index is planned as a whole to formulate weight, calculates network topology score value；
Step 9: it is the integrated risk of power distribution network that probability of malfunction, which diagnoses value-at-risk multiplied by network topology scoring value-at-risk,
Value, can be used for subsequent risk analysis.
Technical solution of the present invention is described in further detail with specific embodiment with reference to the accompanying drawings of the specification:
Power distribution network simulation model as shown in Fig. 4,3 transformers of the system, 16 distribution lines, 13 load sections
Point illustrates the calculating step and method of probability of malfunction by taking transformer 1 and route 5 as an example:
Step 1: the voltage and payload (taking per unit value) of each node being obtained by Load flow calculation, substitute into electrical quantity wind
Dangerous calculation formula, the value-at-risk that analysis can obtain voltage out-of-limit in electrical quantity is 0.38, and the out-of-limit value-at-risk of load is 0；By maintenance portion
It is 0.1 that the equipment health Evaluation result of door, which obtains non-electric quantity value-at-risk, both above ontology factor wind for constituting transformer 1
Danger value；
Step 2: nearly one hour weather index being obtained by the statistical data at microclimate station, temperature is 20 degrees Celsius, rainfall
Amount is 110mm, wind speed 3m/s, brings the value-at-risk calculation formula of external factor into, is obtained at this time by temperature and air speed influence
Threat probability values are 0, and the threat probability values influenced by rainfall are 0.2, and the above three constitutes the external factor risk of transformer 1
Value；
Step 3: the data over the years according to provided by maintenance department carry out quantitative analysis to the historical factor of equipment, obtain
The value-at-risk influenced by Years Of Service is 0.2, is 0.8 by the value-at-risk that failure logging obtains, house does not occur in equipment of the same clan
Race's property defect, value-at-risk 0, the above three constitute the historical factor value-at-risk of transformer 1；
Step 4: the modeling of application level analytic approach carries out significance level comparative analysis, structure to the above index at all levels
It makes judgment matrix and passes through consistency check, obtain each level index weights, be arranged by the value-at-risk and weight of each index
Value, the probability of malfunction value-at-risk that current device can be obtained with weighted calculation is 0.170.The probability of malfunction of route 5 can similarly be obtained
Value-at-risk is 0.309, as shown in table 1；
3 transformers in system and 16 routes are carried out with the value-at-risk meter of probability of equipment failure according to the method described above
It calculates, the failure risk value for being averaged to obtain the power distribution system equipment is 0.158.
1 probability of malfunction diagnostic result of table
The rational calculating step of topological structure and method are illustrated to the network topology assessment of analogue system grid structure:
Step 1: to assessing for the load transfer ability under current grid structure, it is assumed that higher level station between interconnection and
Middle pressure interconnection ratio is respectively 0.1,0.2, and both this constitutes load transfer capability evaluation value；
Step 2: technical attributes " route be averaged segments " when can obtain the construction of line are provided by the relevant technologies department " automatically
Three quantification of targets values of isolation technology coverage rate " " intelligent switch is averagely segmented capacity " be 0.7, the present invention in using not by every
Trouble isolation serviceability is characterized from the load that failure influences, therefore takes the 0.3 trouble isolation serviceability quantized value as network, this is net
Frame structure self attributes；
Step 3: according to the statistical method of load power loss rate in network topology evaluation system, rate of energy loss being quantified
It calculates, substitutes into above-mentioned energy loss calculation formula, obtaining rate of energy loss is 12.62%, this value characterizes the negative of current grid structure
Lotus power loss rate；
Step 4: the modeling of application level analytic approach carries out significance level comparative analysis, structure to the above index at all levels
It makes judgment matrix and passes through consistency check, obtain each level index weights, be arranged by the value-at-risk and weight of each index
Value, can obtain the network topology score value 0.155 under current grid structure, as shown in table 2 with weighted calculation.
2 network topology assessment result of table
The failure risk value of power distribution system equipment is 0.158 in the simulation example, and the score value of network topology is
0.155, the two product is 2.4 × 10-2, i.e., resulting distribution network system risk is calculated in simulation model the method for the present invention
Value.
Claims (4)
1. a kind of meter and the rational intelligent distribution network methods of risk assessment of network topology, which is characterized in that the method includes
Following steps:
(1) probability of malfunction diagnostic module: quantitatively evaluating is carried out to the risk operating status of equipment, recognizes the high probability of malfunction of power distribution network
Electrical equipment；
(2) network topology reasonable evaluation module: quantitatively evaluating is carried out to the reasonability of network topology, realizes Judging fault consequence
More serious network topology structure；
(3) the real-time value-at-risk of distribution system determines: application level analytic approach is planned as a whole to formulate each level index weights, and it is general to calculate failure
Said two devices are taken real-time value-at-risk of the product as distribution system by rate value-at-risk and network topology score value.
2. meter according to claim 1 and the rational intelligent distribution network methods of risk assessment of network topology, feature exist
In: the probability of malfunction diagnostic module is by the comprehensive analysis structure to apparatus body factor, external factor and historical factor
Forming apparatus probability of malfunction value-at-risk；
Wherein ontology factor refers to the operating condition and health degree of electrical equipment itself, from electrical figureofmerit and non-electric quantity index
The probability of two aspect diagnostic device failures；
Wherein external factor refers to influence of the terrible weather environment to equipment, from the temperature of equipment operating environment, rainfall, wind speed three
The probability of a aspect diagnostic device failure；
Wherein historical record refers to the bad log of equipment: horizontal, failure logging and equipment of the same clan from equipment Years Of Service
Record the probability of three aspect diagnostic device failures.
3. meter according to claim 1 and the rational intelligent distribution network methods of risk assessment of network topology, feature exist
In: the network topology reasonable evaluation module is by load transfer ability, trouble isolation serviceability and the load to network
The comprehensive analysis of power loss rate calculates network topology structure score value；
After wherein load transfer ability refers to grid collapses, load is turned the ability supplied, interconnection ratio between slave station by other branches
Two example, middle pressure interconnection ratio aspect analysis assessments；
Wherein trouble isolation serviceability, which refers to, carries out ability of the isolation control in minimum zone for failure, from route be averaged segments,
Automatism isolation technology coverage rate, intelligent switch are averagely segmented three aspect analysis assessments of capacity；
Wherein load power loss rate, which refers to break down under current network topology structure, causes the ratio of load power loss, from energy loss angle
Degree analysis assessment.
4. meter according to claim 1 and the rational intelligent distribution network methods of risk assessment of network topology, feature exist
In: the real-time value-at-risk determination of distribution system is the modeling of application level analytic approach, carries out significance level to the index of each level
Comparative analysis, Judgement Matricies simultaneously carry out consistency check, formulate the weighted value of each level index, index value-at-risk is weighted
Cumulative, as probability of malfunction value-at-risk and network topology score value, said two devices take real-time risk of the product as distribution system
Value.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111191355A (en) * | 2019-12-23 | 2020-05-22 | 贵州电网有限责任公司 | Relay protection device operation risk assessment method based on severity |
| CN111738546A (en) * | 2020-05-19 | 2020-10-02 | 无锡融合大数据创新中心有限公司 | Power equipment state evaluation system |
| CN111798029A (en) * | 2020-05-29 | 2020-10-20 | 广州供电局有限公司黄埔供电局 | Join in marriage net production safety risk early warning system |
| CN112348697A (en) * | 2020-10-21 | 2021-02-09 | 国网天津市电力公司 | Power grid running state comprehensive evaluation method and device based on big data |
| CN112434947A (en) * | 2020-11-25 | 2021-03-02 | 国网湖北省电力有限公司咸宁供电公司 | Intelligent evaluation method and equipment for power distribution network and storage medium |
| CN112651662A (en) * | 2021-01-12 | 2021-04-13 | 国电南瑞科技股份有限公司 | Method and system for minimizing risk of cascading failures of power grid under multi-fire disaster |
| CN112862218A (en) * | 2021-03-17 | 2021-05-28 | 广东电网有限责任公司 | Power equipment out-of-service management system |
| CN112966385A (en) * | 2021-03-12 | 2021-06-15 | 上海交通大学 | Method and system for identifying topology weak points of power distribution network frame |
| CN113052473A (en) * | 2021-03-31 | 2021-06-29 | 贵州电网有限责任公司 | Power grid risk analysis method based on fault rate and static safety analysis |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104156881A (en) * | 2014-06-20 | 2014-11-19 | 天津大学 | Comprehensive power distribution network fault risk assessment method |
| CN106056314A (en) * | 2016-06-29 | 2016-10-26 | 李明洋 | Risk assessment method for intelligent distribution network |
| CN106786546A (en) * | 2017-01-11 | 2017-05-31 | 南京工业大学 | Distribution network failure recovery policy optimization method based on risk assessment |
| US20180278055A1 (en) * | 2017-03-22 | 2018-09-27 | Cooper Technologies Company | System and method for asset health monitoring using multi-dimensional risk assessment |
| CN108681800A (en) * | 2017-12-06 | 2018-10-19 | 国网新疆电力有限公司乌鲁木齐供电公司 | A kind of fortune inspection methods of risk assessment of distributed new access power distribution network |
-
2019
- 2019-05-23 CN CN201910436834.XA patent/CN110346673A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104156881A (en) * | 2014-06-20 | 2014-11-19 | 天津大学 | Comprehensive power distribution network fault risk assessment method |
| CN106056314A (en) * | 2016-06-29 | 2016-10-26 | 李明洋 | Risk assessment method for intelligent distribution network |
| CN106786546A (en) * | 2017-01-11 | 2017-05-31 | 南京工业大学 | Distribution network failure recovery policy optimization method based on risk assessment |
| US20180278055A1 (en) * | 2017-03-22 | 2018-09-27 | Cooper Technologies Company | System and method for asset health monitoring using multi-dimensional risk assessment |
| CN108681800A (en) * | 2017-12-06 | 2018-10-19 | 国网新疆电力有限公司乌鲁木齐供电公司 | A kind of fortune inspection methods of risk assessment of distributed new access power distribution network |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111191355A (en) * | 2019-12-23 | 2020-05-22 | 贵州电网有限责任公司 | Relay protection device operation risk assessment method based on severity |
| CN111738546A (en) * | 2020-05-19 | 2020-10-02 | 无锡融合大数据创新中心有限公司 | Power equipment state evaluation system |
| CN111798029A (en) * | 2020-05-29 | 2020-10-20 | 广州供电局有限公司黄埔供电局 | Join in marriage net production safety risk early warning system |
| CN112348697A (en) * | 2020-10-21 | 2021-02-09 | 国网天津市电力公司 | Power grid running state comprehensive evaluation method and device based on big data |
| CN112434947A (en) * | 2020-11-25 | 2021-03-02 | 国网湖北省电力有限公司咸宁供电公司 | Intelligent evaluation method and equipment for power distribution network and storage medium |
| CN112651662A (en) * | 2021-01-12 | 2021-04-13 | 国电南瑞科技股份有限公司 | Method and system for minimizing risk of cascading failures of power grid under multi-fire disaster |
| CN112651662B (en) * | 2021-01-12 | 2022-09-20 | 国电南瑞科技股份有限公司 | Method and system for minimizing risk of cascading failures of power grid under multi-fire disaster |
| CN112966385A (en) * | 2021-03-12 | 2021-06-15 | 上海交通大学 | Method and system for identifying topology weak points of power distribution network frame |
| CN112862218A (en) * | 2021-03-17 | 2021-05-28 | 广东电网有限责任公司 | Power equipment out-of-service management system |
| CN113052473A (en) * | 2021-03-31 | 2021-06-29 | 贵州电网有限责任公司 | Power grid risk analysis method based on fault rate and static safety analysis |
| CN113052473B (en) * | 2021-03-31 | 2024-03-22 | 贵州电网有限责任公司 | Power grid risk analysis method based on fault rate and static safety analysis |
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Application publication date: 20191018 |