CN105303020A - AHP-based method for natural disaster risk assessment of power grid - Google Patents
AHP-based method for natural disaster risk assessment of power grid Download PDFInfo
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Abstract
The present invention provides an AHP-based method for natural disaster risk assessment of a power grid. The method comprises: performing statistical analysis on historical disasters and historical weather forecast information in a region in which an assessed power grid is located, and constructing a risk assessment indicator system through harm identification and vulnerability analysis; constructing a natural disaster risk estimation model of the assessed power grid by using an improved analytic hierarchy process; determining a relative weight of each assessment indicator by using the analytic hierarchy process; determining a risk value the of each assessment indicator based on a preset risk assessment standard; calculating a comprehensive risk value by using the risk value of each assessment indicator and the relative weight of each assessment indicator as an input value of the natural disaster risk assessment model; and establishing a risk level standard so as to obtain a final risk level of the assessed power grid. Impacts from the natural environment and the social environment are comprehensively considered, and comprehensive assessment that combines qualitative and quantitative assessment is performed on the natural disasters of a power grid, thereby providing a theoretical basis for ensuring safe and stable operation of the power grid and for reducing economic loss.
Description
Technical field
The invention belongs to power system security and risk assessment technology field, be specifically related to a kind of electrical network natural hybridized orbit appraisal procedure based on AHP.
Background technology
In recent years, along with the development of China's electric system, network system is also developed rapidly, network system working voltage grade improves constantly, network size also constantly expands, at present, China has defined Northeast China Power Grid, North China Power Telecommunication Network, Central China Power Grid, East China Power Grid, Northwest Grid and south electric network 6 large area electrical network transprovincially, and has basically formed complete long distance powedr transmission Net Frame of Electric Network.Power grid construction has become the Main way of China's power construction, and electric power netting safe running is the key ensureing whole Operation of Electric Systems safety.Once network system meets with accidental pollution event, be not only the loss of electrical network itself, bring the loss of great material, spirit, property aspect also to country and society simultaneously.Therefore, electrical network natural hybridized orbit is assessed, to adopt an effective measure, loss is reduced to minimum, have important practical significance.
In prior art, when assessing power grid risk, usually only considering the electrical specification of electric system, there is the problem that assessment result accuracy is limited.
Summary of the invention
For the defect that prior art exists, the invention provides a kind of electrical network natural hybridized orbit appraisal procedure based on AHP, in order to solve the problem.
The technical solution used in the present invention is as follows:
The invention provides a kind of electrical network natural hybridized orbit appraisal procedure based on AHP, comprise the following steps:
S1, carries out statistical study to the history the condition of a disaster of evaluated electrical network location and history Weather Forecast Information, is built the Risk Assessment Index System of described evaluated electrical network by Danger recognition, vulnerability analysis; Wherein, described Risk Assessment Index System is made up of several evaluation indexes; The one-level evaluation index that described evaluation index comprises is: natural cause influence index, electrical network characteristic index, combat a natural disaster restoring force index and social influence index; Each one-level evaluation index comprises several secondary evaluation indexs; Each secondary evaluation index also comprises several three-tiered evaluation indexs; By that analogy, multistage evaluation index system is formed;
S2, according to the membership between evaluation index at different levels in described Risk Assessment Index System, utilizes improved H to build the natural hybridized orbit assessment models of evaluated electrical network; Wherein, described natural hybridized orbit assessment models is by being from bottom to top sequentially made up of multiple layer; The evaluation index of every one deck is the evaluation index with one-level in assessment indicator system; Further, lower floor's evaluation index is the sub-index of corresponding evaluation index in upper strata;
S3, adopts analytical hierarchy process to determine the relative weighting of each evaluation index in described natural hybridized orbit assessment models;
S4, based on the risk assessment standard preset, determines the value-at-risk of each evaluation index;
S5, using the relative weighting of the value-at-risk of each evaluation index and each evaluation index as the input value of described natural hybridized orbit assessment models, calculates the integrated risk value of described evaluated electrical network;
S6, build risk level standard, described risk level standard is made up of w risk class; The corresponding value-at-risk interval of each risk class, is respectively: (x
on i, x
under i), i=1,2,3,4 ... w; Wherein, x
on i, x
under ifor the boundary value in each interval;
S7, what judge each risk class in the integrated risk value that S5 calculates and described risk level standard is subordinate to situation, obtains the ultimate risk grade of described evaluated electrical network.
Preferably, in S1, described secondary evaluation index comprises:
Rainfall amount, icing situation and high wind conditions are as the secondary evaluation index of natural cause influence index;
Electrical network subtracts for load condition, power network line situation, Network Voltage Deviation and the mains frequency deviation secondary evaluation index as electrical network characteristic index;
Early warning processing power, material stock ability and repairing recovery capability are as combating a natural disaster the secondary evaluation index of restoring force index;
Area death toll, regional severely injured number, Area Inhabitants customer interrupted ratio and regional direct economic loss are as the secondary evaluation index of social influence index.
Preferably, S3 is specially:
S31, determines the relative importance of each evaluation index in described Risk Assessment Index System;
S32, is configured to consistent judgment matrix by described relative importance;
S33, calculates the eigenvalue of maximum corresponding to constructed consistent judgment matrix and corresponding proper vector, and after normalized, the proper vector obtained is the weight of corresponding evaluation index;
S34, advances layer by layer by the hierarchical relationship between index, obtains the weight of each index successively, finally obtains the weight that first class index is corresponding.
Preferably, S4 is specially:
Described evaluation index divides into qualitative assessment index and qualitative evaluation index;
For qualitative evaluation index, expertise scoring is adopted to determine the value-at-risk of described qualitative evaluation index;
For qualitative assessment index, fuzzy membership function is adopted to calculate the value-at-risk of described qualitative assessment index.
Beneficial effect of the present invention is as follows:
Electrical network natural hybridized orbit appraisal procedure based on AHP provided by the invention, breach the limitation of traditional appraisal procedure centered by power equipment physical characteristics, consider physical environment and all many-sided impacts of social environment, electrical network natural hybridized orbit is carried out to the comprehensive assessment of combination of qualitative and quantitative analysis, for guarantee power network safety operation, reduce economic loss provide theoretical foundation.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the electrical network natural hybridized orbit appraisal procedure based on AHP provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail:
As shown in Figure 1, the invention provides a kind of electrical network natural hybridized orbit appraisal procedure based on AHP, comprise the following steps:
S1, statistical study is carried out to the history the condition of a disaster of evaluated electrical network location and history Weather Forecast Information, by Danger recognition, vulnerability analysis, determine several evaluation indexes larger to electric power netting safe running influence degree, thus build the Risk Assessment Index System of described evaluated electrical network; Wherein, described Risk Assessment Index System is made up of several evaluation indexes; The one-level evaluation index that described evaluation index comprises is: natural cause influence index, electrical network characteristic index, combat a natural disaster restoring force index and social influence index; Each one-level evaluation index comprises several secondary evaluation indexs; Each secondary evaluation index also comprises several three-tiered evaluation indexs; By that analogy, multistage evaluation index system is formed;
By the impact investigated different regions disaster with suiting measures to local conditions a situation arises and cause electrical network, namely carry out Danger recognition and vulnerability analysis, the accuracy of power grid risk assessment can be improved further.
In practical application, rainfall amount, icing situation and high wind conditions can be used as the secondary evaluation index of natural cause influence index; Electrical network subtracts the secondary evaluation index that can be used as electrical network characteristic index for load condition, power network line situation, Network Voltage Deviation and mains frequency deviation; Early warning processing power, material stock ability and repairing recovery capability can be used as combats a natural disaster the secondary evaluation index of restoring force index; Area death toll, regional severely injured number, Area Inhabitants customer interrupted ratio and regional direct economic loss can be used as the secondary evaluation index of social influence index.
S2, according to the membership between evaluation index at different levels in described Risk Assessment Index System, utilizes improved H to build the natural hybridized orbit assessment models of evaluated electrical network; Wherein, described natural hybridized orbit assessment models adopts hierarchical structure, by being from bottom to top sequentially made up of multiple layer; The evaluation index of every one deck is the evaluation index of same one-level; Further, lower floor's evaluation index is the sub-index of corresponding evaluation index in upper strata;
S3, adopts analytical hierarchy process to determine the relative weighting of each evaluation index in described natural hybridized orbit assessment models;
This step is specially:
S31, determines the relative importance of each evaluation index in described Risk Assessment Index System;
Such as, compare the relative importance of two evaluation indexes, if evaluation index i and evaluation index j is of equal importance, then make C
ij=1; If evaluation index i is more important than evaluation index j, then make C
ij=2; If evaluation index i is important not as evaluation index j, then make C
ij=3.
S32, is configured to consistent judgment matrix by described relative importance;
S33, calculates the eigenvalue of maximum corresponding to constructed consistent judgment matrix and corresponding proper vector, and after normalized, the proper vector obtained is the weight of corresponding evaluation index;
S34, advances layer by layer by the hierarchical relationship between index, obtains the weight of each index successively, finally obtains the weight that first class index is corresponding.
Compared with traditional AHP method, the present invention, under guarantee result accurately prerequisite, had both been convenient to expert and had been made accurate judgment, additionally reduced the calculated amount brought because of the inconsistency of judgment matrix, thus made fast convergence rate, iterations few.
S4, based on the risk assessment standard preset, determines the value-at-risk of each evaluation index;
When determining the value-at-risk of evaluation index, can for operation of power networks situation, according to the expertise knowledge of the relevant criterion each place such as " rescue of electric power safety accident emergency and regulations of investigating " and " China Nanfang Grid Co., Ltd's electrical production accident investigation code ", agriculture products value-at-risk.
Based on mentioned above principle, evaluation index can divide into qualitative assessment index and qualitative evaluation index;
For qualitative evaluation index, expertise scoring is adopted to determine the value-at-risk of described qualitative evaluation index;
For qualitative assessment index, fuzzy membership function is adopted to calculate the wind value of described qualitative assessment index.
S5, using the relative weighting of the value-at-risk of each evaluation index and each evaluation index as the input value of described natural hybridized orbit assessment models, calculates the integrated risk value of described evaluated electrical network;
S6, build risk level standard, described risk level standard is made up of w risk class; The corresponding value-at-risk interval of each risk class, is respectively: (x
on i, x
under i), i=1,2,3,4 ... w; Wherein, x
on i, x
under ifor the boundary value in each interval;
Such as, 5 risk class can be built, be respectively: be outstanding, good, general, to worsen and serious.
S7, what judge each risk class in the integrated risk value that S5 calculates and described risk level standard is subordinate to situation, obtains the ultimate risk grade of described evaluated electrical network.
For certain province key city electrical network, the history the statistics of geological disaster situation according to this area is analyzed, and by Danger recognition, vulnerability analysis, sets up the Risk Assessment Index System of this area.Choosing affects more natural cause index to this city and has: rainfall, icing, strong wind; Electrical network characteristic index has: subtract for load, line conditions, voltage deviation, frequency departure; Combating a natural disaster restoring force index has: early warning processing power, material stock ability, repairing recovery capability; Social influence index has: death toll, severely injured number, resident's customer interrupted ratio, direct economic loss.
AHP (analytical hierarchy process, AnalyticHierarchyProcess) method is utilized to build this urban distribution network natural hybridized orbit assessment models; Be specially: the contrast matrix T=(t constructing each level
ij)
n × n, utilize range method be translated into corresponding judgment matrix T'=(t '
ij)
n × n.Utilize Matlab to calculate eigenvalue of maximum and the characteristic of correspondence vector thereof of each judgment matrix, and carry out consistency check.Utilize defined method to calculate the value-at-risk of each evaluation index, after each value-at-risk is quantized according to the regulation in " rescue of electric power safety accident emergency and regulations of investigating ", be worth scale by strong breeze danger, calculate the integrated risk value of electrical network.
In sum, the electrical network natural hybridized orbit appraisal procedure based on AHP provided by the invention, has the following advantages:
(1) limitation of traditional appraisal procedure centered by power equipment physical characteristics is breached, consider physical environment and all many-sided impacts of social environment, electrical network natural hybridized orbit is carried out to the comprehensive assessment of combination of qualitative and quantitative analysis, for guarantee power network safety operation, reduce economic loss provide theoretical foundation;
(2) apply the determination that revised simplex algorithm carries out index weights, not only can obtain assessment result accurately, and simplify calculating process, fast convergence rate, iterations are few;
(3) organically combine qualitative analysis and quantitative test, make that evaluation process is simple and easy to do, assessment result is with a high credibility, thus provide comparatively practical theoretical foundation for defence disaster, urgent danger prevention; By the realization of the method, actively set up electrical network natural hybridized orbit evaluating system, to tackle precipitate disaster, rationally take to dodge the precautionary measures, improve electrical network withstand natural calamities ability, reduce every loss;
(4) the present invention can prevent and reduce the harm of various disaster to power equipment effectively, reduce electric network fault and power outage, to the robustness strengthening electrical network, ensure power grid security economical operation, thus effectively for national economy service has great importance.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should look protection scope of the present invention.
Claims (4)
1., based on an electrical network natural hybridized orbit appraisal procedure of AHP, it is characterized in that, comprise the following steps:
S1, carries out statistical study to the history the condition of a disaster of evaluated electrical network location and history Weather Forecast Information, is built the Risk Assessment Index System of described evaluated electrical network by Danger recognition, vulnerability analysis; Wherein, described Risk Assessment Index System is made up of several evaluation indexes; The one-level evaluation index that described evaluation index comprises is: natural cause influence index, electrical network characteristic index, combat a natural disaster restoring force index and social influence index; Each one-level evaluation index comprises several secondary evaluation indexs; Each secondary evaluation index also comprises several three-tiered evaluation indexs; By that analogy, multistage evaluation index system is formed;
S2, according to the membership between evaluation index at different levels in described Risk Assessment Index System, utilizes improved H to build the natural hybridized orbit assessment models of evaluated electrical network; Wherein, described natural hybridized orbit assessment models is by being from bottom to top sequentially made up of multiple layer; The evaluation index of every one deck is the evaluation index with one-level in assessment indicator system; Further, lower floor's evaluation index is the sub-index of corresponding evaluation index in upper strata;
S3, adopts analytical hierarchy process to determine the relative weighting of each evaluation index in described natural hybridized orbit assessment models;
S4, based on the risk assessment standard preset, determines the value-at-risk of each evaluation index;
S5, using the relative weighting of the value-at-risk of each evaluation index and each evaluation index as the input value of described natural hybridized orbit assessment models, calculates the integrated risk value of described evaluated electrical network;
S6, build risk level standard, described risk level standard is made up of w risk class; The corresponding value-at-risk interval of each risk class, is respectively: (x
on i, x
under i), i=1,2,3,4 ... w; Wherein, x
on i, x
under ifor the boundary value in each interval;
S7, what judge each risk class in the integrated risk value that S5 calculates and described risk level standard is subordinate to situation, obtains the ultimate risk grade of described evaluated electrical network.
2. the electrical network natural hybridized orbit appraisal procedure based on AHP according to claim 1, is characterized in that, in S1, described secondary evaluation index comprises:
Rainfall amount, icing situation and high wind conditions are as the secondary evaluation index of natural cause influence index;
Electrical network subtracts for load condition, power network line situation, Network Voltage Deviation and the mains frequency deviation secondary evaluation index as electrical network characteristic index;
Early warning processing power, material stock ability and repairing recovery capability are as combating a natural disaster the secondary evaluation index of restoring force index;
Area death toll, regional severely injured number, Area Inhabitants customer interrupted ratio and regional direct economic loss are as the secondary evaluation index of social influence index.
3. the electrical network natural hybridized orbit appraisal procedure based on AHP according to claim 1, it is characterized in that, S3 is specially:
S31, determines the relative importance of each evaluation index in described Risk Assessment Index System;
S32, is configured to consistent judgment matrix by described relative importance;
S33, calculates the eigenvalue of maximum corresponding to constructed consistent judgment matrix and corresponding proper vector, and after normalized, the proper vector obtained is the weight of corresponding evaluation index;
S34, advances layer by layer by the hierarchical relationship between index, obtains the weight of each index successively, finally obtains the weight that first class index is corresponding.
4. the electrical network natural hybridized orbit appraisal procedure based on AHP according to claim 1, it is characterized in that, S4 is specially:
Described evaluation index divides into qualitative assessment index and qualitative evaluation index;
For qualitative evaluation index, expertise scoring is adopted to determine the value-at-risk of described qualitative evaluation index;
For qualitative assessment index, fuzzy membership function is adopted to calculate the value-at-risk of described qualitative assessment index.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN112365100A (en) * | 2020-12-08 | 2021-02-12 | 国网四川省电力公司内江供电公司 | Power grid disaster early warning and coping method based on disaster risk comprehensive assessment |
| CN114065127A (en) * | 2021-11-04 | 2022-02-18 | 国网辽宁省电力有限公司电力科学研究院 | Regional power grid environment risk assessment method |
| CN114202404A (en) * | 2021-11-12 | 2022-03-18 | 招银云创信息技术有限公司 | Post-loan inspection processing method, system, apparatus, device, medium, and program product |
| CN114254963A (en) * | 2022-03-01 | 2022-03-29 | 航天宏图信息技术股份有限公司 | Natural disaster comprehensive risk assessment method and device, electronic equipment and storage medium |
| 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 |
| CN115510669A (en) * | 2022-10-11 | 2022-12-23 | 昆明理工大学 | Power transmission line seismic loss assessment method based on GIS fuzzy analysis |
| CN115713239A (en) * | 2022-12-07 | 2023-02-24 | 中国南方电网有限责任公司超高压输电公司广州局 | Operation and maintenance risk prediction method and device, computer equipment and storage medium |
| US11693763B2 (en) | 2019-07-30 | 2023-07-04 | General Electric Company | Resilient estimation for grid situational awareness |
| CN116562681A (en) * | 2023-03-30 | 2023-08-08 | 深圳市城市公共安全技术研究院有限公司 | Forest recovery evaluation method and device after disaster, storage medium and electronic equipment |
| US12141052B2 (en) | 2023-05-22 | 2024-11-12 | General Electric Company | Resilient estimation for grid situational awareness |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103439593A (en) * | 2013-07-31 | 2013-12-11 | 国家电网公司 | Distributed power grid risk assessment system and distributed power grid risk assessment method based on fault feature of electric circuit |
-
2014
- 2014-07-14 CN CN201410334145.5A patent/CN105303020A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103439593A (en) * | 2013-07-31 | 2013-12-11 | 国家电网公司 | Distributed power grid risk assessment system and distributed power grid risk assessment method based on fault feature of electric circuit |
Non-Patent Citations (4)
| Title |
|---|
| 何永秀等: "城市电网规划自然灾害风险评价研究", 《电工技术学报》 * |
| 周景等: "基于AHP的电网自然灾害风险评估方法", 《电力建设》 * |
| 赵云飞等: "层次分析法及其在电力系统中的应用", 《电力自动化设备》 * |
| 金菊良等: "改进的层次分析法及其在自然灾害风险识别中的应用", 《自然灾害学报》 * |
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| CN112365100A (en) * | 2020-12-08 | 2021-02-12 | 国网四川省电力公司内江供电公司 | Power grid disaster early warning and coping method based on disaster risk comprehensive assessment |
| CN112365100B (en) * | 2020-12-08 | 2024-05-10 | 国网四川省电力公司内江供电公司 | Disaster risk comprehensive assessment-based power grid disaster early warning and response method |
| CN114065127A (en) * | 2021-11-04 | 2022-02-18 | 国网辽宁省电力有限公司电力科学研究院 | Regional power grid environment risk assessment method |
| CN114202404A (en) * | 2021-11-12 | 2022-03-18 | 招银云创信息技术有限公司 | Post-loan inspection processing method, system, apparatus, device, medium, and program product |
| CN114254963B (en) * | 2022-03-01 | 2022-05-20 | 航天宏图信息技术股份有限公司 | Natural disaster comprehensive risk assessment method and device, electronic equipment and storage medium |
| CN114254963A (en) * | 2022-03-01 | 2022-03-29 | 航天宏图信息技术股份有限公司 | Natural disaster comprehensive risk assessment method and device, electronic equipment and storage medium |
| 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 |
| CN115510669A (en) * | 2022-10-11 | 2022-12-23 | 昆明理工大学 | Power transmission line seismic loss assessment method based on GIS fuzzy analysis |
| CN115713239B (en) * | 2022-12-07 | 2024-04-02 | 中国南方电网有限责任公司超高压输电公司广州局 | Operation and maintenance risk prediction method, device, computer equipment and storage medium |
| CN115713239A (en) * | 2022-12-07 | 2023-02-24 | 中国南方电网有限责任公司超高压输电公司广州局 | Operation and maintenance risk prediction method and device, computer equipment and storage medium |
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| US12141052B2 (en) | 2023-05-22 | 2024-11-12 | General Electric Company | Resilient estimation for grid situational awareness |
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