CN110059913A - A kind of quantitative estimation method counted and the power failure of future-state is planned - Google Patents
A kind of quantitative estimation method counted and the power failure of future-state is planned Download PDFInfo
- Publication number
- CN110059913A CN110059913A CN201910128607.0A CN201910128607A CN110059913A CN 110059913 A CN110059913 A CN 110059913A CN 201910128607 A CN201910128607 A CN 201910128607A CN 110059913 A CN110059913 A CN 110059913A
- Authority
- CN
- China
- Prior art keywords
- power failure
- future
- state
- plan
- influence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a kind of quantitative estimation methods of the power failure plan of meter and future-state, include the following steps: S1, determine the data set of power failure project impact factor and determine the rank of influence degree；S2 plans two kinds of influence factors according to having a power failure, and determines that power failure Program Assessment index is safety index and economic indicator, and establish the valuation functions of safety index and economic indicator respectively；S3, future-state, which has a power failure, plans the classification and quantization of safety index and economic indicator, and safety index and economic indicator are divided into multiple classifications and corresponding setting quantized value section；S4 is ranked up quantitative evaluation result, and the maximum power failure of selection quantization assessed value is intended to be optimal power failure plan.The present invention has not only taken into account the safety of power failure plan, while considering its economy, so that the assessment of scheme more comprehensive and reasonable, enhances the feasibility of scheme on the basis of comprehensive analysis future-state has a power failure the influence factor planned.
Description
Technical field
The present invention relates to area power grid power failure planning fields, and in particular to the quantitative estimation method for the plan that has a power failure.
Background technique
The establishment needs of power transmission network power failure plan, which are taken into account, considers that the optimization of equipment power off time, load transfer, different have a power failure are appointed
The security constraint of power grid and the operation energy of work unit in alternative and harmony and power failure planning procedure between business
The factors such as power.This is a relative complex process for monthly plan establishment, needs to consider between power failure equipments characteristic and equipment
The factors such as relationship, and to the assessment for the power failure plan worked out need to power failure planning business understand in depth and long-term disposal
The experience of relevant issues, this proposes very high request to the professional ability of plan auditor.
Summary of the invention
The technical problem to be solved by the invention is to provide a kind of quantitative evaluation sides of the power failure plan of meter and future-state
Method, so that the assessment of scheme more comprehensive and reasonable, enhances the feasibility of scheme.
In order to solve the above technical problems, the present invention adopts the following technical scheme: what the power failure of a kind of meter and future-state was planned
Quantitative estimation method includes the following steps:
S1 determines the data set of power failure project impact factor and determines the rank of influence degree, wherein power failure project impact
Factor is divided into two kinds of influence factors of security classes and economy class, and each influence factor is divided at least two in two kinds of influence factors
A grade；
S2, according to have a power failure plan two kinds of influence factors, determine power failure Program Assessment index be safety index and economic indicator,
And the valuation functions of safety index and economic indicator are established respectively；
S3, future-state, which has a power failure, plans the classification and quantization of safety index and economic indicator, by safety index and economic indicator
It is divided into multiple classifications and corresponding setting quantized value section；
S4 is ranked up quantitative evaluation result, and the maximum power failure of selection quantization assessed value is intended to be optimal power failure meter
It draws.
Preferably, security classes influence factor includes: future-state grid operation mode, future-state power grid power output, maintenance front and back
Power flow transfer and important load electricity demand, are respectively defined as: v1_i, wherein i=1,2 ... 4.
Preferably, economy class influence factor includes: loss load economic value in the interruption maintenance time, inspection operation work
Human cost and repair apparatus cost；It is respectively defined as: v2_i, wherein i=1,2,3.
Preferably, each influence factor is divided into three grades according to the difference of influence degree.
Preferably, step S2 includes；Assuming that there is K kind power failure plan, then power failure project impact factor is K kind when interruption maintenance
State successively carries out economic evaluation and security evaluation to the influence factor of K kind state,
(1) principal element of the economy of the economic evaluation function influences power failure plan of future-state power failure plan is to have a power failure
Loss load economic value in repair time, inspection operation work human cost and repair apparatus cost, then kth kind (k=1,
2 ... K) have a power failure obtains economic evaluation formula in the works are as follows:
In formula, C is the totle drilling cost of interruption maintenance plan consumption, and unit is member, Pk_lossHaving a power failure for kth kind, plan is lower to have a power failure
The load power of maintenance loss, TkHave a power failure plan lower maintenance plan total time for kth kind, PpriceFor the unit time of service personnel
Cost, vk_2_3 have a power failure for kth kind plans lower repair apparatus cost；
(2) factor of the safety of the security evaluation function influences power failure plan of future-state power failure plan is mainly power grid fortune
Each element in capable and load scene, therefore, Security Evaluation Model indicate are as follows:
S=f (v1_1,v1_2,v1_3,v1_4) (2)。
Preferably, v1_iMapping relations are realized using the method for Recognition with Recurrent Neural Network between S.
Preferably, economy and safety evaluation classification and quantization such as following table in step S3
Preferably, in two class indexs of the step S3 in order to evaluate power failure plan each index 4 classification grade sections,
Using SVM structural model, 4 classification grades construct 3 SVM sub-classifiers, and two class indexs need to construct 6 sub-classifiers altogether,
When constructing i-th of SVM sub-classifier, i=1,2 ... the sample data for belonging to the i-th grade risk is marked the class that is positive, no by .6
The sample data for belonging to i grade risk marks the class that is negative, and calculates separately each height point using categorised decision function to input data
The decision function value of class device, and classification corresponding to Selection of Function value maximum is the grade for having a power failure and planning the assessment of certain quantification of targets.
Preferably, by the resulting power failure planned economy quantification of targets assessed value of step S3 and safety index quantitative evaluation value into
Row weighted sum, shown in sum formula such as formula (3), weight coefficient β1And β2Respectively economic quantization assessed value and safety index amount
Change the weight coefficient of assessed value,
Y=f (C, S)=β1C+β2S (3)
The corresponding total quantization assessed value Y of some power failure plan is obtained to (3) formula, all Y values are carried out to be maximized operation
Optimal power failure plan can be obtained.
Compared with existing power failure Program Assessment measure, influence factor base of the present invention in the power failure plan of comprehensive analysis future-state
On plinth, the safety of power failure plan has not only been taken into account, while having considered its economy, so that the assessment of scheme is more comprehensive
Rationally, the feasibility of scheme is enhanced.In addition in terms of to numerous influence factor grade assessments, using the skill of support vector machines
Art eliminates the subjective impact in existing grade separation.
The specific technical solution of the present invention and its advantages will in the following detailed description in conjunction with attached drawing into
Row detailed description.
Detailed description of the invention
Present invention will be further described below with reference to the accompanying drawings and specific embodiments:
Fig. 1 is flow chart of the present invention；
Fig. 2 is somewhere electric network composition schematic diagram；
Fig. 3 is the electrical network figure of IEEE30 node.
Specific embodiment
The quantitative estimation method of the power failure plan of meter and future-state, includes the following steps:
S1 determines the data set of power failure project impact factor and determines the rank of influence degree
According to the object that power failure project impact factor influences, numerous influence factors are divided into two kinds: security classes, economy class；
Wherein security classes influence factor include: future-state grid operation mode, future-state power grid power output, maintenance front and back power flow transfer and
Important load electricity demand, is respectively defined as: v1_i(wherein, i=1,2 ... 4)；Economy class influence factor includes: the inspection that has a power failure
Repair loss load economic value, inspection operation work human cost and the repair apparatus cost in the time；It is respectively defined as: v2_i
(wherein, i=1,2,3).7 important factor in order are determined in total.Above-mentioned various security classes influence factors and economy class influence because
Element has no particular meaning in the present invention, and specific understanding can refer to the prior art.
Further, each influence factor is respectively divided into level-one, second level and three-level totally three according to the difference of influence degree
Grade.
S2 determines that power failure Program Assessment index is safety index and economic indicator, and establishes the valuation functions of the two.
Assuming that there is K kind power failure plan, then above-mentioned factor is K kind state when interruption maintenance, successively to the factor of state in K into
Row economic evaluation and security evaluation.
(1) the economic evaluation function of future-state power failure plan
The principal element for influencing the economy of power failure plan is loss load economic value in the interruption maintenance time, maintenance behaviour
Make work human cost and repair apparatus cost.Then kth kind (k=1,2 ... K) have a power failure in the works economic evaluation formula
Are as follows:
In formula, C is the totle drilling cost of interruption maintenance plan consumption, and unit is member.Pk_lossHaving a power failure for kth kind, plan is lower to have a power failure
The load power of maintenance loss, TkHave a power failure plan lower maintenance plan total time for kth kind.PpriceFor the unit time of service personnel
Cost, vk_2_3Have a power failure for kth kind and plans lower repair apparatus cost.
(2) the security evaluation function of future-state power failure plan
The factor for influencing the safety of power failure plan is mainly each element in operation of power networks and load scene (with v1_i,
I=1,2,3,4) therefore, Security Evaluation Model may be expressed as:
S=f (v1_1,v1_2, v1_3, v1_4) (2)
Due to v1_iIt is complicated and changeable with the relationship of S, and and time correlation, mapping relations are using circulation nerve net between the two
The method of network (RNN) is realized.
Recognition with Recurrent Neural Network model structure is shown in attached drawing 2, respectively input layer (input variable number is 4), the hidden layer (number of plies
It is determined as 3 layers) and output layer (output number is 4).Wherein, (v1_i, S) and it is input (the future-state power grid based on future-state data
The method of operation, future-state power grid power output, maintenance front and back power flow transfer and important load electricity demand) and its corresponding safety
Index classification result (very safe, safer, safe and dangerous one of four), U, V be respectively input layer and middle layer,
Parameter vector between middle layer and output layer.W is the parameter vector between the value and current time value at previous moment.
S3, the classification and quantization of future-state power failure program evaluation index
Plan to carry out superiority and inferiority comparison to have a power failure to K kind, need formula (1), (2) resulting economy and safety knot
Fruit is classified and is quantified, and is classified as shown in the table with quantized interval:
1 safety of table and safety evaluation classification and quantization table
4 classification grade sections of each index, can be used SVM structure in the 2 class indexs in order to evaluate power failure plan
Model.4 classification grades construct 3 SVM sub-classifiers, and two indices need to construct 6 sub-classifiers altogether.Constructing i-th of (i
=1,2 ... .6) SVM sub-classifier when, the sample data for belonging to the i-th grade risk label is positive class, i grade wind is not belonging to
The sample data of danger marks the class that is negative.The decision letter of each sub-classifier is calculated separately using categorised decision function to input data
Numerical value, and classification corresponding to Selection of Function value maximum is the grade for having a power failure and planning the assessment of certain quantification of targets.
Since two evaluation index classification quantitative models are all made of the identical more disaggregated models of SVM.In order to accelerate abundant benefit
Processing speed is improved with computing resource, the present invention uses multi-core parallel concurrent processing strategie.
S4 is ranked up quantitative evaluation result, and the maximum power failure of selection quantization assessed value is intended to be optimal power failure meter
It draws.
The resulting power failure planned economy quantification of targets assessed value of S3 and safety index quantitative evaluation value are weighted summation.
Shown in sum formula such as formula (3).Weight coefficient β1And β2The weight system of economy quantization assessed value and safety index quantitative evaluation value
Number.
Y=f (C, S)=β1C+β2S (3)
The corresponding total quantization assessed value Y of some power failure plan is obtained to (3) formula, all Y values are carried out to be maximized operation
Optimal power failure plan can be obtained.
The method to facilitate the understanding of the present invention, this section are proposed by taking the power grid (as shown in Figure 3) of IEEE30 node as an example
Two power failure plans.Two power failure plan points are located at route 14 (being defined as plan 1) and route 19 and (are defined as plan 2)
For carrying out interruption maintenance, power failure plan quantitative evaluation is carried out.Detailed process is as follows:
S1 determines the major influence factors of two power failure plans and influences grade, and concrete outcome is as shown in Table 1 and Table 2.
1 interruption maintenance plan of table, 1 influence factor and influence grade
2 interruption maintenance plan of table, 2 influence factor and influence grade
S2 stops two by economic indicator function and safety index function using the influence factor and influence grade of S1
The economic index and safety indexes of electricity plan are assessed.
(1) economic evaluation.Using following:
In formula, C is the totle drilling cost of interruption maintenance plan consumption, and unit is member.Pk_lossHave a power failure for kth kind (k=1,2) and counts
Draw the load power of lower interruption maintenance loss, TkHave a power failure plan lower maintenance plan total time for kth kind.PpriceFor service personnel's
Long-run cost rate, vk_2_3Have a power failure for kth kind and plans lower repair apparatus cost.Each variable-value is as shown in Table 3 and Table 4.
Each variable of 3 interruption maintenance plan of table, 1 economic indicator and value
Each variable of 4 interruption maintenance plan of table, 2 economic indicator and value
By can be calculated, two kinds of power failures, which are planned to obtain power failure plan 1, needs to lose 3873 yuan, and power failure plan 2 needs to damage
Lose 4100 yuan.
(2) safety evaluation
Using RNN Recognition with Recurrent Neural Network model, after the completion of training, input variable is have a power failure plan 1 and the plan 2 that has a power failure:
Future-state grid operation mode, future-state power grid power output, maintenance front and back power flow transfer and important load electricity demand.Pass through
The index of security assessment of two plans is calculated as a result, after the value and economic index are combined normalized as shown in table 5.
S3, the classification and quantization of future-state power failure program evaluation index
1 and 2 two power failure plan of plan is classified and quantified using SVM model of the present invention, as a result such as table 5
It is shown.
Each index evaluation classification results and quantized value of the power failure of table 5 plan 1 and 2
S4 is ranked up quantitative evaluation result, and the maximum power failure of selection quantization assessed value is intended to be optimal power failure meter
It draws.
The overall evaluation of power failure plan 1 and power failure plan 2 is calculated separately using weighted sum formula (3).
Y=f (C, S)=β1C+β2S (3)
In formula, weight coefficient β1And β20.35 and 0.65 are taken respectively.The results are shown in Table 6 after calculating.
Each index evaluation value and overall evaluation comparison of the power failure of table 6 plan 1 and 2
The resulting overall evaluation of table 6 is compared and can be obtained, plan 1 will be better than by planning 2 comprehensive assessment effect, main former
Because be plan 2 in influence safety indexes most situational factors be better than plan 1, although its economic index with plan 1 phase
It is more weaker than slightly.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, is familiar with
The those skilled in the art should be understood that the present invention includes but is not limited to content described in specific embodiment above.It is any
Modification without departing from function and structure principle of the invention is intended to be included in the range of claims.
Claims (9)
1. a kind of quantitative estimation method of the power failure plan of meter and future-state, it is characterised in that include the following steps:
S1 determines the data set of power failure project impact factor and determines the rank of influence degree, wherein power failure project impact factor
It is divided into two kinds of influence factors of security classes and economy class, and each influence factor is divided at least two etc. in two kinds of influence factors
Grade；
S2 plans two kinds of influence factors according to having a power failure, and determines that power failure Program Assessment index is safety index and economic indicator, and divide
The valuation functions of safety index and economic indicator are not established；
S3, future-state, which has a power failure, plans the classification and quantization of safety index and economic indicator, and safety index and economic indicator are divided into
Multiple classifications and corresponding setting quantized value section；
S4 is ranked up quantitative evaluation result, and the maximum power failure of selection quantization assessed value is intended to be optimal power failure plan.
2. the quantitative estimation method of the power failure plan of a kind of meter according to claim 1 and future-state, it is characterised in that: peace
Universal class influence factor includes: future-state grid operation mode, future-state power grid power output, maintenance front and back power flow transfer and important negative
Lotus electricity demand, is respectively defined as: v1_i, wherein i=1,2 ... 4.
3. the quantitative estimation method of the power failure plan of a kind of meter according to claim 2 and future-state, it is characterised in that: warp
Ji class influence factor includes: loss load economic value, inspection operation work human cost and maintenance in the interruption maintenance time
Equipment cost is respectively defined as: v2_i, wherein i=1,2,3.
4. the quantitative estimation method of the power failure plan of a kind of meter according to claim 3 and future-state, it is characterised in that: every
A influence factor is divided into three grades according to the difference of influence degree.
5. the quantitative estimation method of the power failure plan of a kind of meter according to claim 4 and future-state, it is characterised in that: step
Suddenly S2 includes；Assuming that there is K kind power failure plan, then power failure project impact factor is K kind state when interruption maintenance, successively to K kind shape
The influence factor of state carries out economic evaluation and security evaluation,
(1) the economic evaluation function of future-state power failure plan
The principal element of the economy of influence power failure plan is loss load economic value, inspection operation work in the interruption maintenance time
Make human cost and repair apparatus cost, then kth kind (k=1,2 ... K) have a power failure in the works economic evaluation formula are as follows:
In formula, C is the totle drilling cost of interruption maintenance plan consumption, and unit is member, Pk_lossHave a power failure for kth kind and plans lower interruption maintenance
The load power of loss, TkHave a power failure plan lower maintenance plan total time for kth kind, PpriceFor service personnel unit time at
This, vk_2_3Have a power failure for kth kind and plans lower repair apparatus cost；
(2) the security evaluation function of future-state power failure plan
The factor of the safety of influence power failure plan is mainly each element in operation of power networks and load scene, therefore, safety
Assessment models indicate are as follows:
S=f (v1_1,v1_2,v1_3,v1_4) (2)。
6. the quantitative estimation method of the power failure plan of a kind of meter according to claim 5 and future-state, it is characterised in that:
v1_iMapping relations are realized using the method for Recognition with Recurrent Neural Network between S.
7. the quantitative estimation method of the power failure plan of a kind of meter as claimed in any of claims 1 to 6 and future-state,
It is characterized by: economy and safety evaluation classification and quantization such as following table in step S3
8. the quantitative estimation method of the power failure plan of a kind of meter according to claim 7 and future-state, it is characterised in that: step
4 classification grade sections of each index in rapid two class indexs of the S3 in order to evaluate power failure plan, using SVM structural model, 4
A classification grade constructs 3 SVM sub-classifiers, and two class indexs need to construct 6 sub-classifiers altogether, is constructing i-th of SVM subclassification
When device, i=1,2 ... the sample data for belonging to the i-th grade risk is marked the class that is positive, is not belonging to the sample of i grade risk by .6
Data markers are negative class, calculate separately the decision function value of each sub-classifier using categorised decision function to input data, and
Classification corresponding to Selection of Function value maximum is the grade for having a power failure and planning the assessment of certain quantification of targets.
9. the quantitative estimation method of the power failure plan of a kind of meter according to claim 7 and future-state, it is characterised in that: will
The resulting power failure planned economy quantification of targets assessed value of step S3 and safety index quantitative evaluation value are weighted summation, and summation is public
Shown in formula such as formula (3), weight coefficient β1And β2The weight system of respectively economic quantization assessed value and safety index quantitative evaluation value
Number,
Y=f (C, S)=β1C+β2S (3)
The corresponding total quantization assessed value Y of some power failure plan is obtained to (3) formula, all Y values are carried out to be maximized operation
Obtain optimal power failure plan.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910128607.0A CN110059913A (en) | 2019-02-21 | 2019-02-21 | A kind of quantitative estimation method counted and the power failure of future-state is planned |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910128607.0A CN110059913A (en) | 2019-02-21 | 2019-02-21 | A kind of quantitative estimation method counted and the power failure of future-state is planned |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110059913A true CN110059913A (en) | 2019-07-26 |
Family
ID=67315984
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910128607.0A Pending CN110059913A (en) | 2019-02-21 | 2019-02-21 | A kind of quantitative estimation method counted and the power failure of future-state is planned |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110059913A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112149972A (en) * | 2020-09-11 | 2020-12-29 | 中国地质大学（武汉） | Water delivery tunnel inspection cost evaluation method and equipment and storage equipment |
| CN112288290A (en) * | 2020-10-30 | 2021-01-29 | 广东电网有限责任公司 | Power failure plan arranging method and device, computer equipment and storage medium |
| CN112446615A (en) * | 2020-11-26 | 2021-03-05 | 深圳供电局有限公司 | Method for evaluating priority of uninterrupted operation |
| CN112465235A (en) * | 2020-12-01 | 2021-03-09 | 国网浙江杭州市富阳区供电有限公司 | Power failure interval prediction method for reducing electric quantity loss |
| CN112613179A (en) * | 2020-12-28 | 2021-04-06 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101251836A (en) * | 2008-04-07 | 2008-08-27 | 昆明理工大学 | Transmission line turnaround plan optimizing method for recording power off hidden loss |
| CN101764406A (en) * | 2009-12-24 | 2010-06-30 | 国电南瑞科技股份有限公司 | Maintenance scheduling safety evaluation method based on power generation loss and load supply adequacy |
| CN104156790A (en) * | 2014-08-22 | 2014-11-19 | 国家电网公司 | Method for optimizing and balancing power-cut schemes |
| CN105162111A (en) * | 2015-08-25 | 2015-12-16 | 国家电网公司 | Determination method considering power grid reliability for electronic device maintenance operation mode |
| CN106845755A (en) * | 2016-11-18 | 2017-06-13 | 中国电力科学研究院 | A kind of interruption maintenance planning professional skill appraisal procedure and system |
-
2019
- 2019-02-21 CN CN201910128607.0A patent/CN110059913A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101251836A (en) * | 2008-04-07 | 2008-08-27 | 昆明理工大学 | Transmission line turnaround plan optimizing method for recording power off hidden loss |
| CN101764406A (en) * | 2009-12-24 | 2010-06-30 | 国电南瑞科技股份有限公司 | Maintenance scheduling safety evaluation method based on power generation loss and load supply adequacy |
| CN104156790A (en) * | 2014-08-22 | 2014-11-19 | 国家电网公司 | Method for optimizing and balancing power-cut schemes |
| CN105162111A (en) * | 2015-08-25 | 2015-12-16 | 国家电网公司 | Determination method considering power grid reliability for electronic device maintenance operation mode |
| CN106845755A (en) * | 2016-11-18 | 2017-06-13 | 中国电力科学研究院 | A kind of interruption maintenance planning professional skill appraisal procedure and system |
Non-Patent Citations (3)
| Title |
|---|
| WAN HUA ETAL.: "Risk based voltage security assessment", 《IEEE TRANSACTIONS ON POWER SYSTEMS》 * |
| 林兴良: "基于风险管理的配网检修计划优化研究", 《企业技术开发》 * |
| 汤伟 等: "基于支持向量机的大电网运行风险量化评估", 《合肥工业大学学报（自然科学版）》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112149972A (en) * | 2020-09-11 | 2020-12-29 | 中国地质大学（武汉） | Water delivery tunnel inspection cost evaluation method and equipment and storage equipment |
| CN112149972B (en) * | 2020-09-11 | 2022-06-24 | 中国地质大学（武汉） | Water delivery tunnel inspection cost evaluation method and equipment and storage equipment |
| CN112288290A (en) * | 2020-10-30 | 2021-01-29 | 广东电网有限责任公司 | Power failure plan arranging method and device, computer equipment and storage medium |
| CN112288290B (en) * | 2020-10-30 | 2023-06-09 | 广东电网有限责任公司 | Power outage plan arrangement method and device, computer equipment and storage medium |
| CN112446615A (en) * | 2020-11-26 | 2021-03-05 | 深圳供电局有限公司 | Method for evaluating priority of uninterrupted operation |
| CN112446615B (en) * | 2020-11-26 | 2023-10-20 | 深圳供电局有限公司 | Uninterrupted operation priority evaluation method |
| CN112465235A (en) * | 2020-12-01 | 2021-03-09 | 国网浙江杭州市富阳区供电有限公司 | Power failure interval prediction method for reducing electric quantity loss |
| CN112465235B (en) * | 2020-12-01 | 2023-08-04 | 国网浙江杭州市富阳区供电有限公司 | Power failure interval prediction method for reducing electric quantity loss |
| CN112613179A (en) * | 2020-12-28 | 2021-04-06 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
| CN112613179B (en) * | 2020-12-28 | 2022-11-08 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110059913A (en) | A kind of quantitative estimation method counted and the power failure of future-state is planned | |
| CN105139095A (en) | Power distribution network running state evaluation method based on attribute area module | |
| CN104318482A (en) | Comprehensive assessment system and method of smart distribution network | |
| CN109670675B (en) | Method and device for evaluating running state of charging pile | |
| CN104037943B (en) | A kind of voltage monitoring method and system that improve grid voltage quality | |
| CN104408562B (en) | A kind of photovoltaic system generating efficiency comprehensive estimation method based on BP neural network | |
| CN108428045A (en) | A kind of distribution network operation health state evaluation method | |
| CN106505593A (en) | A kind of method of the analysis of distribution transforming three-phase imbalance and load adjustment based on big data | |
| CN108320043A (en) | A kind of distribution network equipment state diagnosis prediction method based on electric power big data | |
| CN103761690A (en) | Evaluation method based on voltage reactive power control system in grid system | |
| CN102902882A (en) | Method for evaluating operation quality of information systems | |
| CN110111024A (en) | Scientific and technological achievement market valuation method based on AHP model of fuzzy synthetic evaluation | |
| WO2021164118A1 (en) | Ac/dc bulk power grid dynamic security risk situation rolling prospective early warning method and system | |
| CN103632203A (en) | Distribution network power supply area division method based on comprehensive evaluation | |
| CN107832973A (en) | A kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation | |
| CN110489783B (en) | QNNN-based low-voltage transformer area line loss rate reasonable range estimation method | |
| CN107358332A (en) | A kind of dispatching of power netwoks runs lean evaluation method | |
| CN103996147A (en) | Comprehensive evaluation method for power distribution network | |
| CN104331844A (en) | Power network infrastructure project investment decision-making method | |
| CN110826228B (en) | Regional power grid operation quality limit evaluation method | |
| CN110490409B (en) | DNN-based low-voltage transformer area line loss rate benchmarking value setting method | |
| CN107153845A (en) | A kind of isolated island detection method of the adaptive grid-connected photovoltaic system based on machine learning | |
| CN108921322A (en) | A kind of ultra-short term node load prediction technique and system based on Spot Price | |
| CN110348674A (en) | A kind of power grid risk assessment method, system and computer readable storage medium | |
| CN106845752A (en) | A kind of extensive extra-high voltage interconnected network receives electric Scale Evaluation system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190726 |