CN105389656A - Performance evaluation method of secondary equipment of power system - Google Patents
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Abstract
The invention relates to a performance evaluation method of secondary equipment of a power system. The provided method comprises the following steps: calculating an availability vector A; calculating a credibility matrix D; calculating an inherent ability vector S; and analyzing and determining a secondary equipment health state evaluation result. Compared with the existing in the prior art, performance evaluation can be carried out on the secondary equipment of the power system effectively; with combination of the risk state and operation and maintenance cost of the equipment, how the operation and maintenance work of the equipment is carried out is determined, thereby improving the operation level of the power grid enterprise.
Description
Technical field
The present invention relates to power system device efficiency estimation method, particularly the efficiency estimation method of secondary equipment in power system.
Background technology
Secondary equipment in power system is the important component part of electric system, and its function is the operating mode of monitoring the operation of the high voltage electric equipment of electrical energy production, conveying, assigning process, controlling, regulating, protect and provide equipment to run for operation maintenance personnel.
Along with the development of China's electrical network scale, the value volume and range of product of electrical secondary equipment also constantly increases.First, reliability and economy are the fundamental requirements to secondary equipment in power system, and the realization of second power equipment usefulness is the basis ensureing economy and reliability.The efficiency evaluation method applied in armament systems is applied to electric system by choosing of power equipment index.Realize the efficiency evaluation to second power equipment in electric system.
Summary of the invention
In order to solve the problem, the object of the invention is to provide a kind of secondary equipment in power system efficiency estimation method, thus provides foundation for the O&M of the equipment of power grid enterprises and assessment.
Object of the present invention can be achieved through the following technical solutions: a kind of efficiency estimation method for secondary equipment in power system, comprises the steps:
S100: according to history data and the health status calculating availability vector A of secondary equipment in power system;
S200: calculate reliability matrix D according to secondary device history data;
S300: the capability index choosing secondary device, calculates capability vector C;
S400: the usefulness E determining secondary device according to the availability vector A, the confidence level vector D that determine and capability vector C, computing formula is: E=ADC.
Wherein step S100 specifically comprises: obtain two basic datas according to the history data of secondary device and the health status of secondary device and implement this step.The running status of secondary device is divided into upstate and malfunction two states, determining availability vector A is bivector, A=[a
1, a
2], in A, element is determined according to the mean free error time MTBF of secondary device and average time for repair of breakdowns MTTR.A
1indication equipment is in the probability of upstate, for the mean free error time accounts for the proportion of mean free error time and average time for repair of breakdowns sum.A
2indication equipment is in the probability of malfunction, for average time for repair of breakdowns accounts for the proportion of mean free error time and average time for repair of breakdowns sum.Secondary device as typical electronic product, its unreliable degree and the equal obeys index distribution of device mean time before failure T.The secondary device working time enters stable operation stage, and can be similar to failure rate is constant λ.The mean free error time of secondary device is the inverse of secondary device failure rate, and secondary device failure rate is obtained by health status score and exponential form empirical correlation, and parameters of formula is obtained by least square fitting.
Analyze according to transformer station's operation/maintenance data, equipment average time for repair of breakdowns is the inverse of secondary device fault restoration rate, and the repair rate of equipment was obtained through curve by the defect repair time of secondary device.
Wherein step S200 comprises: calculate on equipment failure rate and fault restoration rate basis at S100 and carry out, initial time secondary device may be in upstate or malfunction any one, i.e. n=2, the credible matrix of secondary device can be expressed as:
Wherein d
11expression system is in normal condition when starting, and is still in normal condition in process of executing the task; d
12expression system is in normal condition when starting, and is in malfunction in process of executing the task; d
21expression system is in malfunction when starting, and is in normal condition in process of executing the task; d
22expression system is in malfunction when starting, and is still in malfunction in process of executing the task; In D, each element obtains data in D by solving state equation of transfer and obtains according to failure rate and fault restoration rate.
Wherein step S300 comprises: C is capability vector, and represent when secondary device is in each state, it completes the ability of own job task.According to the difference in functionality determination secondary device capability index of secondary device, and finally determine the intrinsic energy force value c of equipment, C=[c, 0] (secondary device has two kinds of original states, a capability, therefore C is 1 × 2 dimensional vector matrix).Choose the closely-related index with functional performance according to the difference in functionality of secondary device, the standard chosen is: the parameter of reflection equipment major function, Parameters variation affects huge index to functions of the equipments, the index of retrievable value of consult volume.Be the data type of each index agriculture products in the process of index for selection, the level threshold value of index, data unit information.
Different to the interact relation of capability according to index change, be the corresponding index utility function of each Index Establishment, main Types has: positive correlation type, negative correlation type, parabolic type and Boolean type etc.Determine the utility value of each index according to index utility function, it is 0 ~ 1 that the value of utility value is divided into, and the parameter of index utility function is determined the difference that capability affects size according to desired value, finally subitem utility value is weighted summation and obtains.Weight coefficient is obtained by analytical hierarchy process after expert's sequence by the importance degree of index is different.
Wherein step S400 comprises: need the availability matrix (vector) obtained by step S100, the feasibility matrix that step S200 obtains, and the capability matrix (vector) that step S300 obtains does the efficiency value that product obtains equipment.The performance ratings current according to the efficiency value determination equipment of equipment.Wherein efficiency value is efficient operation 0.95 ~ 1, and 0.8 ~ 0.95 is equilibrium state, and 0.6 ~ 0.8 is lower state, lower than 0.6 for poor.Draw the efficiency evaluation result of equipment accordingly.
The present invention contrasts prior art, has the following advantages:
1. the object of the present invention is to provide a kind of implementation method of secondary equipment in power system measures of effectiveness, the task performance of the method application ADC model to secondary device is assessed, be in the probability of upstate and state by analytical equipment and the probability of transfer occur and the crucial capability index of bonding apparatus, draw the efficiency value of equipment.Calculate according to equipment effectiveness value, the state understanding secondary device for operations staff provides foundation.
2. the present invention proposes the concept of secondary equipment in power system being carried out to measures of effectiveness, establish the method for carrying out measures of effectiveness, the history data of package, the defect information of equipment, and the data that the operating performance parameter of equipment etc. is multi-faceted, the formulation for Plant maintenance plan provides important reference information.
Accompanying drawing explanation
Fig. 1 is secondary equipment in power system potency method calculation flow chart.
Embodiment
ADC model thinks that system effectiveness is that expection system meets measuring of one group of particular task requirement degree, is the function of system availability, credibility and capability.Availability is the tolerance of the system state when starting to execute the task; Credibility is under the condition of the status when known system starts to execute the task, the tolerance of the system state of certain moment or multiple moment in the process of executing the task; Capability is in known system executes the task process under status condition, and system reaches the tolerance of the ability of task object.
The expression formula of this model is:
E＝ADC,
In formula, A is availability vector, A={a
1, a
2..., a
n, n is system starting state number when executing the task; D is the reliability matrix of N × N, d
i,jsystem by during original state i experience task to the probability transferring to state j at the end of task; C is capability vector matrix, if when equipment comprises multinomial capability, C is a matrix, c
i,kwhen representative system is in state j, complete probability or the amount of finishing the work of kth item subtask, system effectiveness is now a vector, and when equipment is only containing a kind of capability, C is one dimension matrix.
The present invention is based on the measures of effectiveness that secondary equipment in power system carried out by ADC model, in electric system, availability vector A, reliability matrix D and the secondary device capability vector C of secondary device has specific industry characteristic, availability vector A, reliability matrix D and secondary device capability index is determined, capability vector C be main contents of the present invention according to the usefulness of ADC model determination secondary device according to substation operation is actual.
Fig. 1 is secondary equipment in power system efficiency estimation method calculation flow chart.
The present invention comprises following steps:
S100: according to history data and the health status calculating availability vector A of secondary equipment in power system;
S200: calculate reliability matrix D according to secondary device history data;
S300: the capability index choosing secondary device, calculates capability vector C;
S400: the usefulness E determining secondary device according to the availability vector A, the confidence level vector D that determine and capability vector C.
Wherein step S100 specifically comprises: obtain two basic datas according to the history data of secondary device and the health status of secondary device and implement this step.The running status of secondary device is divided into upstate and malfunction two states, determining availability vector A is bivector, A=[a
1, a
2], in A, element is determined according to the mean free error time MTBF of secondary device and average time for repair of breakdowns MTTR.A
1indication equipment is in the probability of upstate, for the mean free error time accounts for the proportion of mean free error time and average time for repair of breakdowns sum.A
2indication equipment is in the probability of malfunction, for average time for repair of breakdowns accounts for the proportion of mean free error time and average time for repair of breakdowns sum.Secondary device as typical electronic product, its unreliable degree and the equal obeys index distribution of device mean time before failure T.The secondary device working time enters stable operation stage, and can be similar to failure rate is constant λ.The mean free error time of secondary device is the inverse of secondary device failure rate, and secondary device failure rate is obtained by health status score and exponential form empirical correlation, and parameters of formula is obtained by least square fitting.
Analyze according to transformer station's operation/maintenance data, equipment average time for repair of breakdowns is the inverse of secondary device fault restoration rate, and the repair rate of equipment was obtained through curve by the defect repair time of secondary device.
Wherein step S200 comprises: calculate on equipment failure rate and fault restoration rate basis at S100 and carry out, initial time secondary device may be in upstate or malfunction any one, i.e. n=2, the credible matrix of secondary device can be expressed as:
Wherein d
11expression system is in normal condition when starting, and is still in normal condition in process of executing the task; d
12expression system is in normal condition when starting, and is in malfunction in process of executing the task; d
21expression system is in malfunction when starting, and is in normal condition in process of executing the task; d
22expression system is in malfunction when starting, and is still in malfunction in process of executing the task; In D, each element obtains data in D by solving state equation of transfer and obtains according to failure rate and fault restoration rate.
Wherein step S300 comprises: C is capability vector, and represent when secondary device is in each state, it completes the ability of own job task.According to the difference in functionality determination secondary device capability index of secondary device, and finally determine the intrinsic energy force value c of equipment, C=[c, 0] (n=2, k=1).Choose the closely-related index with functional performance according to the difference in functionality of secondary device, the standard chosen is: the parameter of reflection equipment major function, Parameters variation affects huge index to functions of the equipments, the index of retrievable value of consult volume.Be the data type of each index agriculture products in the process of index for selection, the level threshold value of index, data unit information.
Different to the interact relation of capability according to index change, be the corresponding index utility function of each Index Establishment, main Types has: positive correlation type, negative correlation type, parabolic type and Boolean type etc.Determine the utility value of each index according to index utility function, it is 0 ~ 1 that the value of utility value is divided into, and the parameter of index utility function is determined the difference that capability affects size according to desired value, finally subitem utility value is weighted summation and obtains.Weight coefficient is obtained by analytical hierarchy process after expert's sequence by the importance degree of index is different.
Wherein step S400 comprises: need the availability matrix (vector) obtained by step S100, the feasibility matrix that step S200 obtains, and the capability matrix (vector) that step S300 obtains does the efficiency value that product obtains equipment.The performance ratings current according to the efficiency value determination equipment of equipment.Wherein efficiency value is efficient operation 0.95 ~ 1, and 0.8 ~ 0.95 is equilibrium state, and 0.6 ~ 0.8 is lower state, lower than 0.6 for poor.Draw the efficiency evaluation result of equipment accordingly.
Below in conjunction with drawings and Examples, the present invention is further described in detail.Should be understood that these embodiments are only not limited to scope of the present invention for illustration of the present invention.In addition should be understood that read the present invention lecture content after, those skilled in the art can make various change or amendment to the present invention, these equivalent form of values fall within equally the application pay claims limited range.
Based on a secondary equipment in power system efficiency estimation method for ADC model, embodiment is as follows:
This embodiment supposes that the data that the present invention needs have obtained as follows: the state evaluation of merge cells must be divided into 90 points, pair time precision be 0.9 μ s, punctual precision is 3 μ s/30min, samples to Forwarding Latency 1ms, light mouth transmitted power is-14db ~-20db, has SV storm rejection ability.
Obtain the number of times record that the health status call of secondary device in a period of time in the past and secondary device break down, according to the experimental formula of above-mentioned data by the computing equipment failure rate of least square fitting method determination secondary device.
Can obtain the current failure rate of equipment according to the health status score of equipment under the experimental formula determined and current state, in this example, the failure rate of this merge cells is:
λ＝8640*e
-0.15958*ISE＝8640*e
-0.15958*90＝0.005
Analyze merge cells repair data over the years, can show that the repair rate of unit interval equipment is μ=0.329 by exponential curve fitting.
The determination of availability matrix A.The upstate of merge cells has upstate and malfunction two kinds.Therefore availability vector: A=[a
1a
2].
The mean free error time of secondary device and average time for repair of breakdowns are respectively the inverse of equipment failure rate and fault restoration rate, then equipment at the probability of upstate and malfunction as shown in the formula calculating.
A=[0.985,0.015] is obtained as calculated in this example.
In credible matrix D, each element is only relevant with fault restoration rate with the failure rate of secondary device, obtains computing formula as follows by solving state solution of equation:
The reliability matrix calculated in this example
Capability Matrix C needs the capability index according to the function apparatus for establishing of equipment, choosing of index is set up according to the selection standard of aforesaid index, choose following index explain as the capability index of merge cells and the information such as data type, the threshold value of index, the utility function type of index of index by being combined Elementary Function analysis, as shown in the table.
Merge cells capability index is as shown in the table,
The utility value of each index at current time is determined according to index utility function.The weight of each index obtains according to analytical hierarchy process.As shown in the table:
| Index | Desired value | Standard | Utility value | Index weights |
| Pair time precision | 0.95μs | 1μs | 0.9 | 0.2 |
| Punctual precision | 3μs/30min | <4μs/30min | 1 | 0.2 |
| Sampling is to Forwarding Delay | 1ms | <2ms | 1 | 0.1 |
| Measuring accuracy | Nothing | Nothing | 1 | 0.1 |
| Light mouth transmitted power | -16db～-18DB | -14～-20dB | 1 | 0.1 |
| Quality changes | Do not change | Do not change | 1 | 0.1 |
| SV storm suppresses | Have | Have | 1 | 0.2 |
Show that the intrinsic energy force value of this merge cells is: c=0.98, capability vector C=[0.980]
t.
The efficiency value obtaining merge cells in the present embodiment according to ADC analytic approach is:
Above to invention has been detailed introduction, herein concrete operation method of the present invention and operating process are described in detail, for helping, method of the present invention and core concept are understood to embodiment, simultaneously to one of ordinary skill in the art, according to thought of the present invention, embodiment and range of application all will change, in sum, this description should not be construed as limitation of the present invention again.
Claims (8)
1., for an efficiency estimation method for secondary equipment in power system, it is characterized in that comprising the steps:
S100: according to history data and the health status calculating availability vector A of secondary equipment in power system;
S200: calculate reliability matrix D according to secondary device history data;
S300: the capability index choosing secondary device, calculates capability vector C;
S400: the usefulness E determining secondary device according to the availability vector A, the confidence level vector D that determine and capability vector C, computing formula is: E=ADC.
2. method according to claim 1, is characterized in that: wherein step S100 specifically comprises: obtain two basic datas according to the history data of secondary device and the health status of secondary device and implement this step; The running status of secondary device is divided into upstate and malfunction two states, determining availability vector A is bivector, A=[a
1, a
2], in A, element is determined according to the mean free error time MTBF of secondary device and average time for repair of breakdowns MTTR, a
1indication equipment is in the probability of upstate, for the mean free error time accounts for the proportion of mean free error time and average time for repair of breakdowns sum, and a
2indication equipment is in the probability of malfunction, for average time for repair of breakdowns accounts for the proportion of mean free error time and average time for repair of breakdowns sum.
3. method according to claim 1, it is characterized in that: wherein step S200 comprises: calculate on equipment failure rate and fault restoration rate basis at S100 and carry out, initial time secondary device may be in upstate or malfunction any one, i.e. n=2, the credible matrix of secondary device can be expressed as:
Wherein d
11expression system is in normal condition when starting, and is still in normal condition in process of executing the task; d
12expression system is in normal condition when starting, and is in malfunction in process of executing the task; d
21expression system is in malfunction when starting, and is in normal condition in process of executing the task; d
22expression system is in malfunction when starting, and is still in malfunction in process of executing the task; In D, each element obtains data in D by solving state equation of transfer and obtains according to failure rate and fault restoration rate.
4. method according to claim 1, is characterized in that: wherein step S300 comprises: C is capability vector, and represent when secondary device is in each state, it completes the ability of own job task; According to the difference in functionality determination secondary device capability index of secondary device, and finally determine the intrinsic energy force value c of equipment, C=[c, 0] (secondary device has two kinds of original states, a capability, therefore C is 1 × 2 dimensional vector matrix); Choose the closely-related index with functional performance according to the difference in functionality of secondary device, the standard chosen is: the parameter of reflection equipment major function, and Parameters variation affects huge index to functions of the equipments, the index of retrievable value of consult volume; Be the data type of each index agriculture products in the process of index for selection, the level threshold value of index, data unit information.
5. method according to claim 4, it is characterized in that: different to the interact relation of capability according to index change, for the corresponding index utility function of each Index Establishment, the utility value of each index is determined according to index utility function, it is 0 ~ 1 that the value of utility value is divided into, the parameter of index utility function is determined the difference that capability affects size according to desired value, finally subitem utility value is weighted summation and obtains.
6. method according to claim 5, is characterized in that: described weight coefficient is obtained by analytical hierarchy process after expert's sequence by the importance degree of index is different.
7. method according to claim 5, is characterized in that: the main Types of described index utility function has: positive correlation type, negative correlation type, parabolic type and Boolean type.
8. method according to claim 1, it is characterized in that: the performance ratings current according to the efficiency value determination equipment of equipment, wherein efficiency value is efficient operation 0.95 ~ 1,0.8 ~ 0.95 is equilibrium state, 0.6 ~ 0.8 is lower state, lower than 0.6 for poor, draw the efficiency evaluation result of equipment accordingly.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106655162A (en) * | 2016-11-09 | 2017-05-10 | 广东电网有限责任公司电力科学研究院 | Multi-target optimized dispatch decision evaluation method for power system |
| CN107122557A (en) * | 2017-05-03 | 2017-09-01 | 国网上海市电力公司 | A kind of transformer split cooling system efficiency evaluation method |
| CN107169195A (en) * | 2017-05-11 | 2017-09-15 | 国网上海市电力公司 | A kind of Split type transformer cooling system efficiency evaluation method |
| CN109300076A (en) * | 2018-11-15 | 2019-02-01 | 中车株洲电力机车有限公司 | A kind of rail traffic vehicles failure data analyzing method |
| CN110209515A (en) * | 2019-06-06 | 2019-09-06 | 广东电网有限责任公司 | A kind of reliability estimation method, device, equipment and storage medium |
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2015
- 2015-11-06 CN CN201510758231.3A patent/CN105389656A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106655162A (en) * | 2016-11-09 | 2017-05-10 | 广东电网有限责任公司电力科学研究院 | Multi-target optimized dispatch decision evaluation method for power system |
| CN107122557A (en) * | 2017-05-03 | 2017-09-01 | 国网上海市电力公司 | A kind of transformer split cooling system efficiency evaluation method |
| CN107169195A (en) * | 2017-05-11 | 2017-09-15 | 国网上海市电力公司 | A kind of Split type transformer cooling system efficiency evaluation method |
| CN109300076A (en) * | 2018-11-15 | 2019-02-01 | 中车株洲电力机车有限公司 | A kind of rail traffic vehicles failure data analyzing method |
| CN110209515A (en) * | 2019-06-06 | 2019-09-06 | 广东电网有限责任公司 | A kind of reliability estimation method, device, equipment and storage medium |
| CN110209515B (en) * | 2019-06-06 | 2023-05-16 | 广东电网有限责任公司 | Reliability evaluation method, device, equipment and storage medium |
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Application publication date: 20160309 |