CN103413048A - Method for determining optimal retirement time of power grid equipment based on three-parameter Weibull distribution - Google Patents
Method for determining optimal retirement time of power grid equipment based on three-parameter Weibull distribution Download PDFInfo
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Abstract
The invention discloses a method for determining the optimal retirement time of power grid equipment based on three-parameter Weibull distribution, which comprises the following steps: establishing an equipment failure rate model based on a Weibull distribution rule; carrying out parameter estimation on the failure rate model to obtain a failure rate function; and determining the optimal retirement time of the equipment according to the failure rate function. Compared with the prior art, the method has the following advantages: 1. the method has universality; 2. compared with the two-parameter Weibull distribution, the three-parameter Weibull distribution has stronger fitting capability on various experimental data, particularly has higher fitting precision on power grid equipment which is characterized by loss failure, and can better reflect the actual condition of equipment failure; 3. the method can provide relatively accurate optimal decommissioning time of the equipment, thereby providing scientific and quantitative definition standards for formulating asset life cycle management strategies (particularly operation and maintenance strategies and decommissioning strategies), fully exerting the value of the equipment, and reducing energy waste and economic loss.
Description
Technical field
The present invention relates to electric power enterprise equipment full life cycle management technical field, relate more specifically to a kind ofly based on three parameters of Weibull, determine the grid equipment method of best retired time.
Background technology
For formulating assets life cycle management operating strategy, the best retired time of grid equipment is a very important reference value.Yet in actual applications current, the aspect that always rests on qualitative analysis that defines to the best retired time of grid equipment, mainly with designed life of equipment, serviceable life reference value, in on-site experiences such as the fortune time limits as basis for estimation, shortage science, quantitative standard and boundary, therefore easily cause equipment retired in advance, its value is not fully exerted, and causes energy dissipation and economic loss.
Therefore, be necessary to provide the method for improved best retired time of definite grid equipment a kind of to overcome above-mentioned defect.
Summary of the invention
The purpose of this invention is to provide and a kind ofly based on three parameters of Weibull, determine the grid equipment method of best retired time, for formulating assets life cycle management operating strategies (especially O&M strategy and retired strategy), provide science, quantitative defining standard, give full play to the equipment self-value, reduce energy dissipation and economic loss.
For achieving the above object, the invention provides and a kind ofly based on three parameters of Weibull, determine the grid equipment method of best retired time, comprising:
Based on Weibull distribution rule apparatus for establishing failure-rate models;
Described failure-rate models is carried out to parameter estimation to obtain the crash rate function, and described parameter comprises form parameter, scale parameter and location parameter;
According to described crash rate function, determine the best retired time of equipment.
Compared with prior art, because method of the present invention is first based on Weibull distribution rule apparatus for establishing failure model, again failure-rate models is carried out to parameter estimation to obtain the crash rate function, finally according to the crash rate function, determines the best retired time of equipment, make the method possess following advantage:
1. historical experience shows, the life distribution type Exponential distribution of grid equipment, Weibull distribution, normal distribution ratio account for more than 80%, and exponential distribution and normal distribution are the special cases of Weibull distribution, so the present invention with Weibull distribution rule apparatus for establishing failure-rate models, finally determines the best retired time of equipment and has universality;
2. for two parameters of Weibull, three parameters of Weibull are stronger for various types of experimental data capability of fitting, especially those be take to loss failure as the grid equipment fitting precision of feature is higher, more can reflect the actual conditions of equipment failure;
3. a best retired time of relatively accurate equipment can be provided, thereby science, quantitative defining standard are provided for formulating assets life cycle management operating strategies (especially O&M strategy and retired strategy), give full play to the equipment self-value, reduced energy dissipation and economic loss.
By following description also by reference to the accompanying drawings, it is more clear that the present invention will become, and these accompanying drawings are for explaining embodiments of the invention.
The accompanying drawing explanation
Fig. 1 is the process flow diagram of the inventive method one embodiment.
Fig. 2 is O&M cost curve of the present invention and the retired cost of disposal curve map of discounting.
Embodiment
With reference now to accompanying drawing, describe embodiments of the invention, in accompanying drawing, similar element numbers represents similar element.
Please refer to Fig. 1, the SF6 isolating switch of take is example, describes the concrete steps of the inventive method in detail.As shown in Figure 1, the method comprises:
S101, based on Weibull distribution rule apparatus for establishing failure-rate models; Be specially, suppose that the accumulative total failure probability F (t) of equipment in life cycle management obeys the Weibull distribution rule with form parameter m, scale parameter η, tri-variable elements of location parameter γ, is expressed as
Obtaining thus purpose of breaker failure rate model is
It should be noted that, the crash rate (failure rate) of grid equipment in life cycle management is the function of time, is called tub curve because its regularity of distribution is bathtub shapes, is divided into earlier failure period, accidental failure period and wear-out failure period three phases.Weibull distribution can the fit tub curve, and above-mentioned three phases correspondingly-shaped parameter m respectively is less than 1(and is greater than zero), equal 1, be greater than 1 three kinds of situations;
S102, carry out pre-service to equipment sample group; Be specially, the equipment sample preprocessing be to equipment life test figure screen, choose design/manufacture is identical, running environment is similar 10 SF6 isolating switchs as a sample group, between the life-span Statistical Area, take and be one section in 5 years; The testing data of life-span of the present embodiment sample group is 15.6,16.2,16.8,17.3,17.9,18.1,18.7,19.5,19.7,20.1;
S103, carry out parameter estimation to obtain the crash rate function according to equipment sample group after pretreatment to failure-rate models; Be specially, parameter estimation is to utilize through pretreated one group of sample data the form parameter in three parameters of Weibull, scale parameter, location parameter are estimated, thereby obtains the crash rate function.When estimation, in sample data, i accumulative total failure probability corresponding to equipment can utilize the meta rank technique
Approximate trying to achieve, wherein N is sample size; N=10 in the present embodiment, corresponding accumulative total failure probability is 0.07,0.16,0.26,0.36,0.45,0.55,0.64,0.74,0.84,0.93; Form parameter m and scale parameter η return and obtain by least square method; Location parameter γ obtains with the maximum correlation coefficient optimization; Particularly, least square method returns and calculates is to get natural logarithm twice to accumulative total failure probability F (t) both sides are same, the equation obtained is converted into to linear equation y=mx-B, wherein
X=ln (t-γ), B=ln η
mX in the present embodiment, the value of y is as shown in the table:
Suppose known location parameter γ, can utilize least square method to return and obtain form parameter m, scale parameter η; In the present embodiment, form parameter and scale parameter are respectively 2.81,4.47;
Particularly, the maximum correlation coefficient optimization be by the related coefficient between independent variable x in linear equation y=mx-B and dependent variable y to location parameter γ first derivation, make that derivative is zero, the γ value obtained is required; In the present embodiment, γ=13.65.Therefore with selected sample group, designing/manufacture the SF6 purpose of breaker failure rate function identical, that running environment is similar is
S104, determine the best retired time of equipment according to the crash rate function; Be specially, suppose that the equipment O&M cost is directly proportional to the crash rate function, scale-up factor is equipment initial investment expense.In the present embodiment, the cost of investment of SF6 isolating switch is 270000 yuan, obtains the O&M cost curve as shown in Fig. 2 solid line with the product of above-mentioned crash rate, increases in time the rule that presents non-linear increasing; Suppose that the retired disposal costs of this isolating switch (comprising artificial, cost of equipment and traffic expense while carrying out retired dispose) is 110000 yuan, remanent value of equipment (equipment is in the surplus value at computation period end) is 2800 yuan, and retired cost of disposal final value is 110000 – 2800=107200 units; Interest rate is 8% if suppose, retired cost of disposal is discounted curve as shown in Fig. 2 dotted line, increases and presents non-linear rule of successively decreasing in time.Article two, the intersection point of curve was the retired time of the best with the SF6 isolating switch that meets this sample group accumulative total failure probability distributions in---approximately 16.9---.
As can be seen from the above description, method of the present invention has the following advantages:
1. historical experience shows, the life distribution type Exponential distribution of grid equipment, Weibull distribution, normal distribution ratio account for more than 80%, and exponential distribution and normal distribution are the special cases of Weibull distribution, so the present invention with Weibull distribution rule apparatus for establishing failure-rate models, finally determines the best retired time of equipment and has universality;
2. for two parameters of Weibull, three parameters of Weibull are stronger for various types of experimental data capability of fitting, especially those be take to loss failure as the grid equipment fitting precision of feature is higher, more can reflect the actual conditions of equipment failure;
3. utilize least square method and maximum correlation coefficient optimization to determine the Weibull distribution coefficient, calculated amount is little, and can guarantee certain precision;
4. a best retired time of relatively accurate equipment can be provided, thereby science, quantitative defining standard are provided for formulating assets life cycle management operating strategies (especially O&M strategy and retired strategy), give full play to the equipment self-value, reduced energy dissipation and economic loss.
Above invention has been described in conjunction with most preferred embodiment, but the present invention is not limited to the embodiment of above announcement, and should contain various modification, equivalent combinations of carrying out according to essence of the present invention.
Claims (7)
1. based on three parameters of Weibull, determine the grid equipment method of best retired time for one kind, it is characterized in that, comprising:
Based on Weibull distribution rule apparatus for establishing failure-rate models;
Described failure-rate models is carried out to parameter estimation to obtain the crash rate function;
According to described crash rate function, determine the best retired time of equipment.
2. the method for claim 1, is characterized in that, " based on Weibull distribution rule apparatus for establishing failure-rate models " also comprises afterwards:
Equipment sample group is carried out to pre-service.
3. method as claimed in claim 2, is characterized in that, " the equipment sample is carried out to pre-service " specifically comprises:
Choose design/manufacture is identical, running environment is similar a plurality of equipment as a described equipment sample group;
A plurality of testing data of life-span between the default life-span Statistical Area of statistics in described equipment sample group.
4. method as described as the claims 1 to 3 any one, is characterized in that, " utilizing described equipment sample group after pretreatment to carry out parameter estimation to described failure-rate models " specifically comprises:
Accumulative total failure probability F (t) both sides, with getting natural logarithm twice, are converted into to linear equation y=mx-B by the equation obtained, wherein
X=ln (t-γ), B=ln η
m, x is independent variable, and y is dependent variable, and ln means to take from right logarithm, and m is that form parameter, η are that scale parameter, γ are location parameter,
T is the time, and exp means expectation;
Suppose known location parameter γ, adopt the described form parameter of least square method calculated and scale parameter;
Adopt the maximum correlation coefficient method to calculate described location parameter.
5. method as claimed in claim 4, is characterized in that, described " adopting the maximum correlation coefficient method to calculate described location parameter " specifically comprises:
By the described parameter γ first derivation of putting of the related coefficient contraposition between independent variable x in linear equation y=mx-B and dependent variable y, make that derivative is zero to obtain the described parameter γ that puts.
6. method as claimed in claim 4, is characterized in that, " determining the best retired time of equipment according to described crash rate function " specifically comprises:
According to equipment initial investment expense and described crash rate function, draw the O&M cost curve;
According to the retired cost of disposal of equipment and remanent value of equipment, draw the retired cost of disposal curve of discounting;
According to described O&M cost curve and the retired cost of disposal curve of discounting, determine the best retired time of described equipment.
7. the method for claim 1, is characterized in that, described parameter comprises form parameter, scale parameter and location parameter.
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| CN104483192A (en) * | 2014-11-27 | 2015-04-01 | 福达合金材料股份有限公司 | Method for processing static fusion welding force data of electrical contact material based on Weibull distribution |
| CN105891645A (en) * | 2016-05-31 | 2016-08-24 | 西安航空制动科技有限公司 | Method for determining vibration fault distribution of anti-skid brake control device |
| CN105930632A (en) * | 2016-03-02 | 2016-09-07 | 航天科工防御技术研究试验中心 | Electromechanical whole machine product shelf-life modeling method |
| CN106054105A (en) * | 2016-05-20 | 2016-10-26 | 国网新疆电力公司电力科学研究院 | Intelligent ammeter reliability prediction correction model building method |
| CN106647273A (en) * | 2016-12-26 | 2017-05-10 | 北京天源科创风电技术有限责任公司 | Method and device for preventability replacing time of prediction part |
| CN108108542A (en) * | 2017-12-14 | 2018-06-01 | 河北工业大学 | The life-span prediction method of low-voltage complete switch equipment |
| CN109101466A (en) * | 2018-11-22 | 2018-12-28 | 中国人民解放军国防科技大学 | Weibull distribution parameter estimation method based on distribution function logarithm transformation |
| CN113168597A (en) * | 2018-11-08 | 2021-07-23 | 施乐百有限公司 | Method and system for predicting failure of a fan group and corresponding fan group |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104483192B (en) * | 2014-11-27 | 2017-01-25 | 福达合金材料股份有限公司 | Method for processing static fusion welding force data of electrical contact material based on Weibull distribution |
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| CN105930632B (en) * | 2016-03-02 | 2018-10-02 | 航天科工防御技术研究试验中心 | Electromechanical machine product storage life modeling method |
| CN106054105B (en) * | 2016-05-20 | 2019-01-15 | 国网新疆电力公司电力科学研究院 | A kind of reliability prediction correction model method for building up of intelligent electric meter |
| CN106054105A (en) * | 2016-05-20 | 2016-10-26 | 国网新疆电力公司电力科学研究院 | Intelligent ammeter reliability prediction correction model building method |
| CN105891645A (en) * | 2016-05-31 | 2016-08-24 | 西安航空制动科技有限公司 | Method for determining vibration fault distribution of anti-skid brake control device |
| CN105891645B (en) * | 2016-05-31 | 2018-10-09 | 西安航空制动科技有限公司 | The method for determining the distribution of antiskid brake control device vibration fault |
| CN106647273A (en) * | 2016-12-26 | 2017-05-10 | 北京天源科创风电技术有限责任公司 | Method and device for preventability replacing time of prediction part |
| CN108108542A (en) * | 2017-12-14 | 2018-06-01 | 河北工业大学 | The life-span prediction method of low-voltage complete switch equipment |
| CN113168597A (en) * | 2018-11-08 | 2021-07-23 | 施乐百有限公司 | Method and system for predicting failure of a fan group and corresponding fan group |
| CN109101466A (en) * | 2018-11-22 | 2018-12-28 | 中国人民解放军国防科技大学 | Weibull distribution parameter estimation method based on distribution function logarithm transformation |
| CN109101466B (en) * | 2018-11-22 | 2019-03-22 | 中国人民解放军国防科技大学 | Weibull distribution parameter estimation method based on distribution function logarithm transformation |
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