CN112365100A - Power grid disaster early warning and coping method based on disaster risk comprehensive assessment - Google Patents
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Abstract
The invention discloses a power grid disaster early warning and coping method based on disaster risk comprehensive assessment, and relates to the technical field of power system disaster early warning. The method comprises the following steps: s1, determining a risk reference value of each early warning grade according to historical data; s2, determining disaster fault probabilities corresponding to different disaster types under different disaster grades; s3, acquiring disaster monitoring information of different areas of the early warning power grid in real time, determining real-time disaster types and disaster grades, and judging real-time disaster influence weights of different disaster types on the power grid under different disaster grades; s4, weighting and multiplying the real-time disaster influence weight and the disaster failure probability to obtain a region failure risk value; s5, determining the regional power grid line weight of different regions; s6, weighting and multiplying the regional power grid line weight and the regional real-time fault expectation rate to obtain a total fault risk value; and S7, comparing the real-time overall fault risk value with the fault rate standard value to determine an early warning level.
Description
Technical Field
The invention relates to the technical field of disaster early warning of power systems, in particular to a power grid disaster early warning and corresponding method based on disaster risk comprehensive evaluation.
Background
Natural disasters are important factors of power grid accidents, and especially serious consequences caused by serious natural disasters are not inconstant. In recent years, the number of disaster events caused by global extreme climate change is increased obviously, and in addition, the insulation capability of a power distribution network circuit is poor, the radiating network structure has more single-loop designs and weak disaster resistance, the difficulty of controlling the safe and stable operation of a power grid is increased due to frequent occurrence of the disaster events, and higher requirements are provided for reliable power supply of the power grid. Natural disasters affecting an electric power system in China have the characteristics of diversity, frequency, regionality and the like, and in order to enhance the capability of a power grid to cope with catastrophe, a disaster early warning mechanism is further established
Disaster risk assessment is a means of risk analysis or observation of the external environment to determine the nature, extent and degree of risk.
Disclosure of Invention
The existing power grid disaster early warning method has many defects, and the outstanding defects are that an early warning model is simple, disaster assessment data is single in source and analysis, and accurate early warning on a power grid cannot be achieved.
Therefore, in the technical field of power system disaster early warning, a more accurate power grid disaster early warning method needs to be provided. Therefore, the invention provides a power grid disaster early warning and handling method based on disaster risk comprehensive assessment, which solves the problems by the following technical points:
a power grid disaster early warning method based on disaster risk comprehensive evaluation,the method is characterized by comprising the following steps: s1, determining a risk reference value A of each early warning grade according to historical dataZWherein Z is the warning level; s2, determining the disaster failure probability P corresponding to different disaster types under different disaster gradesijWherein i is the disaster type and j is the disaster grade; s3, acquiring disaster monitoring information of different areas of the early warning power grid in real time, determining real-time disaster types and disaster grades, and judging real-time disaster influence weights H of different disaster types on the power grid under different disaster gradesij(ii) a S4, weighting the influence of real-time disasters HijAnd probability of disaster failure PijObtaining the area fault risk value by weighted multiplication
Wherein X is the area serial number, ni is the total number of disaster types, and nj is the total number of disaster grades; s5, determining regional power grid line weight B of different regionsx(ii) a S6, weighting the regional power grid line BxAnd regional real-time fault expectation rate QxWeighted multiplication is carried out to obtain an overall fault risk value
Wherein nx is the total number of predicted regions; s7, comparing the real-time overall fault risk value M with the fault rate standard value AZAnd comparing and determining the early warning level.
As described above, the invention provides a power grid disaster early warning method based on disaster risk comprehensive assessment. Generally, disasters are accompanied, such as in high mountain canyon areas with large slope ratios, and large-scale rainfall not only causes flood disasters but also landslides. In the invention, disasters of different types and grades are monitored and determined in real time through monitoring data, and the disaster influence weight and the fault risk value causing the fault to the power grid are weighted and calculated, so that the regional fault risk value of a detection area can be comprehensively evaluated. And because the population, economic conditions, distribution network line trend and the configuration of power transmission equipment in the regions are different, the importance degree in the power grid is different among different detection regions. Therefore, the power grid line weight is assigned to each region, and the calculated region fault risk value is weighted and calculated to obtain a region with a larger range: such as the overall fault risk value of a certain county or a local city, so as to issue comprehensive regional power grid early warning.
The further technical scheme is as follows:
the risk reference is determined by the total loss of capacity caused by historical grid faults.
The disaster types i comprise icing, pollution flashover, lightning, wind, mountain fire, flood and landslide, and the disaster grade j is divided into general grade I disaster, heavier grade II disaster, serious grade III disaster and grade IV disaster. The power transmission and transformation equipment such as overhead transmission lines and the like are exposed in the atmospheric environment for a long time, and whether the equipment can safely and reliably operate is closely related to the external environment. The disaster type in the technical characteristic is selected as a common disaster type with a large influence in power grid operation. The disaster grade is divided into four grades to accord with the habit of dividing the disaster grade in China.
The disaster failure probability
Said C isijCounting the frequency of power grid faults within time under the conditions that the disaster type is i and the disaster grade is j; said DijThe total number of times of disaster occurrence with the disaster type i and the disaster grade j in the statistical time is calculated. In the technical characteristics, the fault rate under the action of disasters of a certain type grade in a research and statistics time interval is obtained by statistically analyzing the fault record data of the power grid line for many years, and the historical fault rate is used as a prediction model of the fault probability.
The disaster influence weight HijThe method is obtained by comparing the economic loss degrees of disasters with different disaster types i and different disaster grades j in history. Namely, the assignment of the disaster influence weight under a certain type of grade is positively correlated with the loss of the disaster influence weight to the economy, and the disaster which can cause large loss can be paid higher attention in the early warning process.
The regional power grid line weight BxFrom the economic transmission capacity of the regional power gridAnd determining the length of the power grid line. The division of the regional line weight enables power system operators to perform disaster prevention deployment on different regions in a targeted manner, and meanwhile, a basis is provided for unifying disaster risk data of a plurality of regions in subsequent steps.
The invention also provides a power grid disaster responding method based on the comprehensive disaster risk assessment, which comprises the following steps of:
the power grid disaster coping method based on disaster risk comprehensive evaluation is characterized by comprising the following steps: s1, detecting disaster risks, and carrying out disaster early warning on real-time monitoring data, wherein the disaster early warning method is any one of the disaster early warning methods; s2, preparing materials and rush-repair teams according to the disaster early warning level; s3, making emergency response to the disaster, and scheduling a rush-repair team to perform on-site disposal on the disaster; and S4, completing disaster disposal, and analyzing and evaluating the disaster.
The scheduling method of the rush-repair team comprises the following steps: s3.1, determining regional power grid line weight B of different regionsx(ii) a S3.2, calculating real-time first-aid repair capability indexes Y of different first-aid repair teamsαtWherein alpha is the serial number of the emergency repair team; s3.3, establishing regional power grid line weight B of disaster occurrence placexAnd the real-time first-aid repair capability index Y of the first-aid repair teamαtAnd allocating rush-repair teams based on the corresponding relations. In the technical characteristics, importance difference of a power grid in different regions and capability difference of different emergency repair teams are considered in scheduling of the emergency repair teams. The emergency maintenance team with the capacity equivalent to the importance degree of the area with the power grid fault is allocated in a targeted mode, and the influence degree and the range caused by the fault can be reduced as far as possible. Wherein the regional power grid line weights B of different regionsxAnd the value is kept consistent with the value obtained in the disaster early warning method.
Real-time first-aid repair capability index of first-aid repair team
Wherein Y isαThe criterion index of emergency repair capability for the emergency repair team, the function U (t) being the emergency repair teamAnd t is the accumulated working time of the emergency maintenance team in the disaster response. In the technical characteristics, according to the number of emergency repair teams, the types and the number configuration condition of emergency repair materials, the professional knowledge skill level of the whole team and the emergency repair speed, each emergency repair team is assigned with an emergency repair capability reference index Yα. And as the rush-repair team executes the rush-repair work of one fault, the configured corresponding materials are reduced due to use, the rush-repair personnel can carry out the work along with the development of the rush-repair work, the physical strength can also be reduced, the corresponding rush-repair efficiency can also be reduced, namely when the rush-repair team repairs the fault, the fault can also cause the rush-repair team to have certain loss. In order to describe the degree of wear suffered by the emergency crew due to the ongoing emergency repair process, a loss function u (t) of the emergency crew is defined as a function of time t. And quantitatively calculating to obtain the real-time emergency repair capability index of the emergency repair team, so that the power grid operator can master the condition of the emergency repair team more intuitively in the fault repair process.
Compared with the prior art, the invention has the beneficial effects that:
the invention is scientific and reasonable. Compared with the prior art, the method and the device have the advantages that different influences on the power grid caused by different types, grades, regional differences and the like of disasters are considered, all influencing factors are subjected to assignment quantitative analysis, the power grid fault risk value of the whole region is comprehensively evaluated, and therefore the grade of power grid disaster early warning is judged. Meanwhile, the invention also provides a disaster coping method based on the early warning method. When allocating the rush-repair teams to solve the fault caused by the disaster, the real-time rush-repair capability of different rush-repair teams and the importance difference of the power grid among different areas are fully considered, the rush-repair teams are allocated in a targeted manner, and the influence range and the influence degree caused by the fault are reduced as much as possible.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a step diagram of a power grid disaster coping method based on disaster risk comprehensive assessment according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1:
the power grid disaster early warning method based on disaster risk comprehensive assessment is characterized by comprising the following steps: s1, determining a risk reference value A of each early warning grade according to historical dataZWherein Z is the warning level; s2, determining the disaster failure probability P corresponding to different disaster types under different disaster gradesijWherein i is the disaster type and j is the disaster grade; s3, acquiring disaster monitoring information of different areas of the early warning power grid in real time, determining real-time disaster types and disaster grades, and judging real-time disaster influence weights H of different disaster types on the power grid under different disaster gradesij(ii) a S4, weighting the influence of real-time disasters HijAnd probability of disaster failure PijObtaining the area fault risk value by weighted multiplication
Wherein X is the area serial number, ni is the total number of disaster types, and nj is the total number of disaster grades; s5, determining regional power grid line weight B of different regionsx(ii) a S6, weighting the regional power grid line BxAnd regional real-time fault expectation rate QxWeighted multiplication is carried out to obtain an overall fault risk value
Wherein nx is the total number of predicted regions; s7, comparing the real-time overall fault risk value M with the fault rate standard value AZAnd comparing and determining the early warning level.
As described above, the invention provides a power grid disaster early warning method based on disaster risk comprehensive assessment. Generally, disasters are accompanied, such as in high mountain canyon areas with large slope ratios, and large-scale rainfall not only causes flood disasters but also landslides. In the invention, disasters of different types and grades are monitored and determined in real time through monitoring data, and the disaster influence weight and the fault risk value causing the fault to the power grid are weighted and calculated, so that the regional fault risk value of a detection area can be comprehensively evaluated. And because the population, economic conditions, distribution network line trend and the configuration of power transmission equipment in the regions are different, the importance degree in the power grid is different among different detection regions. Therefore, the power grid line weight is assigned to each region, and the calculated region fault risk value is weighted and calculated to obtain a region with a larger range: such as the overall fault risk value of a certain county or a local city, so as to issue comprehensive regional power grid early warning.
Example 2:
this example is further defined on the basis of example 1:
the risk reference is determined by the total loss of capacity caused by historical grid faults.
The disaster types i comprise icing, pollution flashover, lightning, wind, mountain fire, flood and landslide, and the disaster grade j is divided into general grade I disaster, heavier grade II disaster, serious grade III disaster and grade IV disaster. The power transmission and transformation equipment such as overhead transmission lines and the like are exposed in the atmospheric environment for a long time, and whether the equipment can safely and reliably operate is closely related to the external environment. The disaster type in the technical characteristic is selected as a common disaster type with a large influence in power grid operation. The disaster grade is divided into four grades to accord with the habit of dividing the disaster grade in China.
The disaster failure probability
Said C isijCounting the frequency of power grid faults within time under the conditions that the disaster type is i and the disaster grade is j; said DijThe total number of times of disaster occurrence with the disaster type i and the disaster grade j in the statistical time is calculated. In the technical characteristics, the fault rate under the action of disasters of a certain type of grade in a research and statistics time interval is obtained by statistically analyzing the fault record data of the power grid line for years, and the historical fault rate is used as the faultA predictive model of the barrier probability.
The disaster influence weight HijThe method is obtained by comparing the economic loss degrees of disasters with different disaster types i and different disaster grades j in history. Namely, the assignment of the disaster influence weight under a certain type of grade is positively correlated with the loss of the disaster influence weight to the economy, and the disaster which can cause large loss can be paid higher attention in the early warning process.
The regional power grid line weight BxThe economic transmission capacity of the regional power grid and the length of the power grid line are determined. The division of the regional line weight enables power system operators to perform disaster prevention deployment on different regions in a targeted manner, and meanwhile, a basis is provided for unifying disaster risk data of a plurality of regions in subsequent steps.
Example 3:
as shown in fig. 1, based on the power grid disaster early warning method for comprehensive disaster risk assessment, the invention further provides a power grid disaster responding method based on comprehensive disaster risk assessment, which comprises the following steps:
the power grid disaster coping method based on disaster risk comprehensive evaluation is characterized by comprising the following steps: s1, detecting disaster risks, and carrying out disaster early warning on real-time monitoring data, wherein the disaster early warning method is any one of the disaster early warning methods; s2, preparing materials and rush-repair teams according to the disaster early warning level; s3, making emergency response to the disaster, and scheduling a rush-repair team to perform on-site disposal on the disaster; and S4, completing disaster disposal, and analyzing and evaluating the disaster.
The scheduling method of the rush-repair team comprises the following steps: s3.1, determining regional power grid line weight B of different regionsx(ii) a S3.2, calculating real-time first-aid repair capability indexes Y of different first-aid repair teamsαtWherein alpha is the serial number of the emergency repair team; s3.3, establishing regional power grid line weight B of disaster occurrence placexAnd the real-time first-aid repair capability index Y of the first-aid repair teamαtAnd allocating rush-repair teams based on the corresponding relations. In the technical characteristics, the dispatching of the emergency repair teams takes the importance difference of the power grid among different regions and the importance difference among different emergency repair teams into considerationThe difference in capacity. The emergency maintenance team with the capacity equivalent to the importance degree of the area with the power grid fault is allocated in a targeted mode, and the influence degree and the range caused by the fault can be reduced as far as possible. Wherein the regional power grid line weights B of different regionsxAnd the value is kept consistent with the value obtained in the disaster early warning method.
Real-time first-aid repair capability index of first-aid repair team
Wherein Y isαThe function U (t) is a loss function of the emergency maintenance team, and t is the accumulated working time of the emergency maintenance team in the disaster response. In the technical characteristics, according to the number of emergency repair teams, the types and the number configuration condition of emergency repair materials, the professional knowledge skill level of the whole team and the emergency repair speed, each emergency repair team is assigned with an emergency repair capability reference index Yα. And as the rush-repair team executes the rush-repair work of one fault, the configured corresponding materials are reduced due to use, the rush-repair personnel can carry out the work along with the development of the rush-repair work, the physical strength can also be reduced, the corresponding rush-repair efficiency can also be reduced, namely when the rush-repair team repairs the fault, the fault can also cause the rush-repair team to have certain loss. In order to describe the degree of wear suffered by the emergency crew due to the ongoing emergency repair process, a loss function u (t) of the emergency crew is defined as a function of time t. And quantitatively calculating to obtain the real-time emergency repair capability index of the emergency repair team, so that the power grid operator can master the condition of the emergency repair team more intuitively in the fault repair process.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. The power grid disaster early warning method based on disaster risk comprehensive assessment is characterized by comprising the following steps:
s1 determining risk reference value A of each early warning grade according to historical dataZWherein Z is the warning level;
s2 determining disaster failure probability P corresponding to different disaster types under different disaster gradesijWherein i is the disaster type and j is the disaster grade;
s3, disaster monitoring information of different areas of the early warning power grid is obtained in real time, real-time disaster types and disaster grades are determined, and real-time disaster influence weights H of different disaster types on the power grid under different disaster grades are judgedij；
S4 weighting the influence of real-time disasterijAnd probability of disaster failure PijObtaining the area fault risk value by weighted multiplication
Wherein X is the area serial number, ni is the total number of disaster types, and nj is the total number of disaster grades;
s5 determining regional power grid line weight B of different regionsx；
S6 weighting the regional power grid line BxAnd regional real-time fault expectation rate QxWeighted multiplication is carried out to obtain an overall fault risk value
Wherein nx is the total number of predicted regions;
s7 comparing the real-time total failure risk value M with the failure rate standard value AZAnd comparing and determining the early warning level.
2. The power grid disaster early warning method based on disaster risk comprehensive assessment according to claim 1, wherein the risk reference value is determined by total capacity loss caused by historical power grid faults.
3. The power grid disaster early warning method based on disaster risk comprehensive assessment according to claim 1, wherein the disaster types i include icing, pollution flashover, lightning, wind, mountain fire, flood and landslide, and the disaster grades j are divided into general grade i, heavy grade ii, severe grade iii and severe grade iv disasters.
4. The power grid disaster early warning method based on disaster risk comprehensive assessment as claimed in claim 1, wherein the disaster failure probability
Said C isijCounting the frequency of power grid faults within time under the conditions that the disaster type is i and the disaster grade is j; said DijThe total number of times of disaster occurrence with the disaster type i and the disaster grade j in the statistical time is calculated.
5. The power grid disaster early warning method based on disaster risk comprehensive assessment as claimed in claim 1, wherein the disaster influence weight HijThe method is obtained by comparing the economic loss degrees of disasters with different disaster types i and different disaster grades j in history.
6. The power grid disaster early warning method based on disaster risk comprehensive assessment as claimed in claim 1, wherein the regional power grid line weight BxThe economic transmission capacity of the regional power grid and the length of the power grid line are determined.
7. The power grid disaster coping method based on disaster risk comprehensive evaluation is characterized by comprising the following steps:
s1, disaster risks are detected, disaster early warning is carried out on real-time monitoring data, and the disaster early warning method is the disaster early warning method according to any one of claims 1-6;
s2, preparing to deal with materials and rush-repair teams according to the disaster early warning level;
s3, making an emergency response to the disaster, and scheduling a rush-repair team to perform on-site disposal on the disaster;
and S4, completing disaster disposal, and analyzing and evaluating the disaster.
8. The power grid disaster responding method based on disaster risk comprehensive assessment as claimed in claim 7, wherein the dispatching method of the emergency repair team is as follows:
s3.1 determining regional power grid line weights B of different regionsx；
S3.2 calculating real-time first-aid repair capability index Y of different first-aid repair teamsαtWherein alpha is the serial number of the emergency repair team;
s3.3 establishing regional power grid line weight B of disaster sitexAnd the real-time first-aid repair capability index Y of the first-aid repair teamαtAnd allocating rush-repair teams based on the corresponding relations.
9. The power grid disaster response method based on disaster risk comprehensive assessment as claimed in claim 8, wherein real-time first-aid repair capability index of the first-aid repair team
Wherein Y isαThe function U (t) is a loss function of the emergency maintenance team, and t is the accumulated working time of the emergency maintenance team in the disaster response.
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| CN116187769A (en) * | 2023-05-04 | 2023-05-30 | 四川省安全科学技术研究院 | Urban flood disaster risk studying and judging method based on scene simulation |
| CN117688475A (en) * | 2024-02-04 | 2024-03-12 | 山东电工时代能源科技有限公司 | Disaster prediction-based energy network assessment method, system, terminal and storage medium |
| WO2024113182A1 (en) * | 2022-11-29 | 2024-06-06 | 宁德时代新能源科技股份有限公司 | Battery risk level determination method, apparatus, storage medium and battery management system |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012198886A (en) * | 2011-03-10 | 2012-10-18 | Yamaguchi Univ | Sediment disaster occurring risk evaluation system according to volcanic activity level and program thereof |
| US20130132045A1 (en) * | 2011-11-21 | 2013-05-23 | International Business Machines Corporation | Natural Disaster Forecasting |
| CN104299116A (en) * | 2014-11-14 | 2015-01-21 | 国家电网公司 | Quantitative evaluation method for security risk of operation of power network |
| CN104318320A (en) * | 2014-10-11 | 2015-01-28 | 中国南方电网有限责任公司 | Static safety analysis based power grid meteorological disaster risk assessment method and device |
| CN104331843A (en) * | 2014-10-30 | 2015-02-04 | 华中科技大学 | Transformer fault risk assessment method based on bowknot model |
| CN105303020A (en) * | 2014-07-14 | 2016-02-03 | 国家电网公司 | AHP-based method for natural disaster risk assessment of power grid |
| CN106228283A (en) * | 2016-07-13 | 2016-12-14 | 国网湖南省电力公司 | Transmission line forest fire calamity source appraisal procedure and system |
| CN107563641A (en) * | 2017-08-31 | 2018-01-09 | 东北大学 | A kind of meter and the power distribution network of disaster preference combat a natural disaster more scene differentiation planing methods |
| CN108537367A (en) * | 2018-03-20 | 2018-09-14 | 广东电网有限责任公司惠州供电局 | Power transmission line comprehensive methods of risk assessment under a kind of more meteorological disasters |
| CN111062604A (en) * | 2019-12-12 | 2020-04-24 | 国家电网有限公司大数据中心 | Power grid service risk assessment method, device and equipment based on meteorological disasters |
-
2020
- 2020-12-08 CN CN202011422432.3A patent/CN112365100B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012198886A (en) * | 2011-03-10 | 2012-10-18 | Yamaguchi Univ | Sediment disaster occurring risk evaluation system according to volcanic activity level and program thereof |
| US20130132045A1 (en) * | 2011-11-21 | 2013-05-23 | International Business Machines Corporation | Natural Disaster Forecasting |
| CN105303020A (en) * | 2014-07-14 | 2016-02-03 | 国家电网公司 | AHP-based method for natural disaster risk assessment of power grid |
| CN104318320A (en) * | 2014-10-11 | 2015-01-28 | 中国南方电网有限责任公司 | Static safety analysis based power grid meteorological disaster risk assessment method and device |
| CN104331843A (en) * | 2014-10-30 | 2015-02-04 | 华中科技大学 | Transformer fault risk assessment method based on bowknot model |
| CN104299116A (en) * | 2014-11-14 | 2015-01-21 | 国家电网公司 | Quantitative evaluation method for security risk of operation of power network |
| CN106228283A (en) * | 2016-07-13 | 2016-12-14 | 国网湖南省电力公司 | Transmission line forest fire calamity source appraisal procedure and system |
| CN107563641A (en) * | 2017-08-31 | 2018-01-09 | 东北大学 | A kind of meter and the power distribution network of disaster preference combat a natural disaster more scene differentiation planing methods |
| CN108537367A (en) * | 2018-03-20 | 2018-09-14 | 广东电网有限责任公司惠州供电局 | Power transmission line comprehensive methods of risk assessment under a kind of more meteorological disasters |
| CN111062604A (en) * | 2019-12-12 | 2020-04-24 | 国家电网有限公司大数据中心 | Power grid service risk assessment method, device and equipment based on meteorological disasters |
Non-Patent Citations (1)
| Title |
|---|
| 尚慧玉 等: "灾害天气条件下电力系统故障诊断特征匹配方法", 《电力建设》, vol. 39, no. 10, pages 37 - 43 * |
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|---|---|---|---|---|
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| CN114819259A (en) * | 2022-03-11 | 2022-07-29 | 国网浙江省电力有限公司绍兴供电公司 | Method for evaluating regional disasters based on disaster power indexes |
| CN115021415A (en) * | 2022-08-01 | 2022-09-06 | 国网浙江省电力有限公司台州供电公司 | Power system anti-typhoon method and platform based on digital live data |
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| CN117688475A (en) * | 2024-02-04 | 2024-03-12 | 山东电工时代能源科技有限公司 | Disaster prediction-based energy network assessment method, system, terminal and storage medium |
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