CN105717382A - Service life pre-estimate system for transformer - Google Patents

Abstract

The invention discloses a service life pre-estimate system for a transformer. The service life pre-estimate system for a transformer includes a transformer monitoring data acquisition module, a heating aging and accelerated aging calculating module, an electric heating aging and accelerated aging calculating module, and a transformer service life calculating module, wherein the transformer monitoring data acquisition module is used for acquisition of the transformer monitoring data; the heating aging and accelerated aging calculating module is connected with the transformer monitoring data acquisition module, and is used for calculating a heating aging and accelerated aging factor; the electric heating aging and accelerated aging calculating module is connected with the transformer monitoring data acquisition module, and is used for calculating an electric heating aging and accelerated aging factor; and the transformer service life calculating module is connected with the heating aging and accelerated aging calculating module and the electric heating aging and accelerated aging calculating module, and is used for calculating the service life of the transformer. The service life pre-estimate system for a transformer can calculate the expected service life of the transformer according to the data recorded by a transformer on-line monitoring device, and provides a basis for a maintainer to make a maintenance plane, thus having a good application prospect and a high promotional value.

Description

A kind of transformator Prediction System in service life

Technical field

The invention belongs to Condition Maintenance Technology of Transformer field, particularly relate to a kind of transformator Prediction System in service life.

Background technology

Power transformer is the important electrical in power system, wherein improves voltage so that long-distance sand transport electric energy and reduction voltage are to meeting the pivotal roles such as power supply in generating, transmission of electricity, distribution link.Jumbo power transformer itself is also very valuable equipment.In power system, the quantity not only needing transformator is many, and requires that the performance of transformator is good, reliable.But each transformer utilization factor operating also differs, and some transformer utilization factors are higher, and what have is then relatively low.Result in the insulation ag(e)ing rate of transformator inconsistent, the Transformer Insulation Aging speed that utilization rate is higher is fast, the transformator of this running status should be monitored closely, it has been found that defect processes in time.Then can suitably increase monitoring periods for the transformator that utilization rate is relatively low, reduce equipment operating cost, or suitably increase equipment active time.In order to make Repair of Transformer personnel that the service life of transformator is had the foundation of a visual rationing.

At present, jumbo power transformer is all configured with on-line monitoring system, dissolves other in the temperature of transformator, transformer oil, and shelf depreciation is monitored.But existing detection system exists inefficient, it is impossible to calculating transformer heat ageing and thermal-electrical aging life-span.

Summary of the invention

It is an object of the invention to overcome existing detection system to exist inefficient, it is impossible to the problem in calculating transformer heat ageing and thermal-electrical aging life-span, it is provided that a kind of transformator Prediction System in service life.

A kind of transformator Prediction System in service life, this transformator Prediction System in service life includes: transformer monitoring data acquisition module, heat ageing accelerated ageing computing module, thermal-electrical aging accelerated ageing computing module, transformator computing module in service life；For gathering the transformer monitoring data acquisition module of transformer monitoring data；The heat ageing accelerated ageing computing module for calculating the heat ageing accelerated ageing factor it is connected with transformer monitoring data acquisition module；The thermal-electrical aging accelerated ageing computing module for calculating the thermal-electrical aging accelerated ageing factor it is connected with transformer monitoring data acquisition module；The transformator computing module in service life for calculating transformer service life it is connected with heat ageing accelerated ageing computing module and thermal-electrical aging accelerated ageing computing module.

Further, transformer monitoring data acquisition module also includes: transformer load monitoring device, Gases Dissolved in Transformer Oil monitoring device and transformer temperature monitoring device.

Further, the process that realizes of heat ageing accelerated ageing computing module includes:

Calculate upper strata oil temperature liter:

${\mathrm{\θ}}_{\mathrm{tt}}={\mathrm{\θ}}_{\mathrm{ft}}{\left(\frac{K^2+1}{R+1}\right)}^n$

Wherein: θ ft is oil temperature temperature rise in upper strata time at full capacity；

The ratio of K actual load and rated load；

R rated load is to the construction rate of non-rated load；

N load reduces the Intrusion Index to upper strata oil temperature；

${\mathrm{\θ}}_o\left(t\right)={\mathrm{\θ}}_{\mathrm{tt}}(1-e^{-\frac{1}{{\mathrm{\τ}}_0}})+{\mathrm{\θ}}_t{e}^{-\frac{1}{{\mathrm{\τ}}_0}}$

Wherein: the thermal time constant of oil during τ 0 rated load；

θ i initial upper layer oil temperature liter；

θ(^gT)=θ^(f)K2m

Wherein: the temperature rise of winding under θ (f) rated load；

M load variations, the variability index of winding temperature；

After t, the hottest spot temperature computational methods of transformator:

θ hst (t)=θ o (t)+θ g (t)+θ a (t)

Wherein: θ a (t) is ambient temperature；

Therefore hottest spot temperature accelerated ageing factor computing formula is:

$F_{\mathrm{AA}}=e^{[\frac{15000}{110+273}-\frac{15000}{{\mathrm{\θ}}_{\mathrm{hst}}\left(t\right)+272}]}.$

Further, thermal-electrical aging accelerated ageing computing module realize method:

$L=L_0{\left(\frac{E}{E_0}\right)}^{-n}$

Wherein: electric stress lower limit during E0 normal aging；

Life-span lower limit during L0 normal aging；

The resistance to electrostrictive coefficient of n；

L=⁰Le-BT

$T=\frac{1}{{\mathrm{\θ}}_0}-\frac{1}{\mathrm{\θ}}$

Wherein: the activation energy of B heat ageing reaction；

θ 0 reference temperature

$L_{\mathrm{res}}=L_0-{\∫}_0^t{\left(\frac{E}{E_t}\right)}^{-(n-\mathrm{bT})}{e}^{-\mathrm{BT}}\mathrm{dt}$

Wherein: the L0 equipment initial expected life-span；

Et electric field intensity is over time；

Life loss rate:

$L\%=1-\frac{L_{\mathrm{res}}}{L_o}$

$F={\∫}_0^t{\left(\frac{b}{\mathrm{kt}+b}\right)}^{-(n-\mathrm{bT})}\·e^{-\mathrm{BT}}\mathrm{dt}$

Wherein: b insulation thickness；

The equivalent burn-in factor:

$F_{\mathrm{EQA}}=\frac{F}{t}.$

Further, the method that transformator computing module in service life realizes:

Life loss according to the heat ageing accelerated factor inputted and thermal-electrical aging accelerated factor technical equivalences, is added up to life loss by following formula calculating transformer；

Ft=α FAA+ (1-α) FEQA

Wherein: α is heat ageing accelerated factor weight.

The present invention data according to transformer online monitoring device record, calculate transformator expected service life, formulate repair schedule for maintainer and provide foundation, owing to not having similar-type products, the present invention to have a good application prospect and promotional value on market.The present invention is by transformer online monitoring device data are analyzed, the method drawing transformator equivalence service life, according to transformator hottest spot temperature, calculates the accelerated factor FAA, the accelerated factor MAAF in thermal-electrical aging life-span in heat ageing service life.By contrasting the two accelerated factor and the service life of transformator under ecotopia, draw the actual life of transformator under different service condition, provide foundation for formulating more reasonably Repair of Transformer plan.

Detailed description of the invention

A kind of transformator Prediction System in service life, this transformator Prediction System in service life includes: transformer monitoring data acquisition module, heat ageing accelerated ageing computing module, thermal-electrical aging accelerated ageing computing module, transformator computing module in service life；For gathering the transformer monitoring data acquisition module of transformer monitoring data；The heat ageing accelerated ageing computing module for calculating the heat ageing accelerated ageing factor it is connected with transformer monitoring data acquisition module；The thermal-electrical aging accelerated ageing computing module for calculating the thermal-electrical aging accelerated ageing factor it is connected with transformer monitoring data acquisition module；The transformator computing module in service life for calculating transformer service life it is connected with heat ageing accelerated ageing computing module and thermal-electrical aging accelerated ageing computing module.

Further, transformer monitoring data acquisition module also includes: transformer load monitoring device, Gases Dissolved in Transformer Oil monitoring device and transformer temperature monitoring device.

Further, the process that realizes of heat ageing accelerated ageing computing module includes:

Calculate upper strata oil temperature liter:

${\mathrm{\θ}}_{\mathrm{tt}}={\mathrm{\θ}}_{\mathrm{ft}}{\left(\frac{K^2+1}{R+1}\right)}^n$

Wherein: θ ft is oil temperature temperature rise in upper strata time at full capacity；

The ratio of K actual load and rated load；

R rated load is to the construction rate of non-rated load；

N load reduces the Intrusion Index to upper strata oil temperature；

${\mathrm{\θ}}_o\left(t\right)={\mathrm{\θ}}_{\mathrm{tt}}(1-e^{-\frac{1}{{\mathrm{\τ}}_0}})+{\mathrm{\θ}}_t{e}^{-\frac{1}{{\mathrm{\τ}}_0}}$

Wherein: the thermal time constant of oil during τ 0 rated load；

θ i initial upper layer oil temperature liter；

θ(^gT)=θ^(f)K2m

Wherein: the temperature rise of winding under θ (f) rated load；

M load variations, the variability index of winding temperature；

After t, the hottest spot temperature computational methods of transformator:

θ hst (t)=θ o (t)+θ g (t)+θ a (t)

Wherein: θ a (t) is ambient temperature；

Therefore hottest spot temperature accelerated ageing factor computing formula is:

$F_{\mathrm{AA}}=e^{[\frac{15000}{110+273}-\frac{15000}{{\mathrm{\θ}}_{\mathrm{hst}}\left(t\right)+272}]}.$

Further, thermal-electrical aging accelerated ageing computing module realize method:

$L=L_0{\left(\frac{E}{E_0}\right)}^{-n}$

Wherein: electric stress lower limit during E0 normal aging；

Life-span lower limit during L0 normal aging；

The resistance to electrostrictive coefficient of n；

L=⁰Le-BT

$T=\frac{1}{{\mathrm{\θ}}_0}-\frac{1}{\mathrm{\θ}}$

Wherein: the activation energy of B heat ageing reaction；

θ 0 reference temperature

$L_{\mathrm{res}}=L_0-{\∫}_0^t{\left(\frac{E}{E_t}\right)}^{-(n-\mathrm{bT})}{e}^{-\mathrm{BT}}\mathrm{dt}$

Wherein: the L0 equipment initial expected life-span；

Et electric field intensity is over time；

Life loss rate:

$L\%=1-\frac{L_{\mathrm{res}}}{L_o}$

$F={\∫}_0^t{\left(\frac{b}{\mathrm{kt}+b}\right)}^{-(n-\mathrm{bT})}\·e^{-\mathrm{BT}}\mathrm{dt}$

Wherein: b insulation thickness；

The equivalent burn-in factor:

$F_{\mathrm{EQA}}=\frac{F}{t}.$

Further, the method that transformator computing module in service life realizes:

Life loss according to the heat ageing accelerated factor inputted and thermal-electrical aging accelerated factor technical equivalences, is added up to life loss by following formula calculating transformer；

Ft=α FAA+ (1-α) FEQA

Wherein: α is heat ageing accelerated factor weight.

The present invention data according to transformer online monitoring device record, calculate transformator expected service life, formulate repair schedule for maintainer and provide foundation, owing to not having similar-type products, the present invention to have a good application prospect and promotional value on market.The present invention is by transformer online monitoring device data are analyzed, the method drawing transformator equivalence service life, according to transformator hottest spot temperature, calculates the accelerated factor FAA, the accelerated factor MAAF in thermal-electrical aging life-span in heat ageing service life.By contrasting the two accelerated factor and the service life of transformator under ecotopia, draw the actual life of transformator under different service condition, provide foundation for formulating more reasonably Repair of Transformer plan.

Claims (2)

1. a transformator estimating system in service life, it is characterized in that, this transformator Prediction System in service life includes: transformer monitoring data acquisition module, heat ageing accelerated ageing computing module, thermal-electrical aging accelerated ageing computing module, transformator computing module in service life；For gathering the transformer monitoring data acquisition module of transformer monitoring data；The heat ageing accelerated ageing computing module for calculating the heat ageing accelerated ageing factor it is connected with transformer monitoring data acquisition module；The thermal-electrical aging accelerated ageing computing module for calculating the thermal-electrical aging accelerated ageing factor it is connected with transformer monitoring data acquisition module；The transformator computing module in service life for calculating transformer service life it is connected with heat ageing accelerated ageing computing module and thermal-electrical aging accelerated ageing computing module.

2. transformator Prediction System in service life according to claim 1, it is characterised in that transformer monitoring data acquisition module also includes: transformer load monitoring device, Gases Dissolved in Transformer Oil monitoring device and transformer temperature monitoring device；Transformer load monitoring modular is by the current/voltage value of bushing shell for transformer current transformer and high-voltage side bus PT, the load of monitoring transformator；Gases Dissolved in Transformer Oil monitoring device passes through the gas sensor being arranged in transformer oil, the gas dissolved in measuring transformer oil；Transformer temperature measurement apparatus is by each measuring point temperature in being arranged on Transformer Winding, in the temperature sensor measurement transformator in oil meter face.