Matukio ya Kupungua Uwezo na Matumizi ya Miaka ya Kondensa ya Nishati kwa Mazingira ya Joto Kikuu
Matukio ya Kupungua Uwezo na Matumizi ya Mipaka ya Umri wa Capacitors za Umeme kwa Masharti ya Joto Kikuu
Kutokana na ukuaji wa miundo ya umeme na maombi ya ongezeko la mizigo, mazingira ya kutumia vyombo vya umeme imekuwa zifuatazo. Ongezeko la joto lenye mazingira limekuwa kama chanzo muhimu cha kuathiri utaratibu mzuri wa capacitors za umeme. Kama sehemu muhimu katika miundo ya kutuma na kukabiliana na umeme, kupungua uwezo wa capacitors za umeme huathiri usalama na utaratibu wa grid. Kwenye masharti ya joto kikuu, vifaa vya dielectric vichache kwenye capacitors hujafanya kwa upinde, kusababisha kupungua kidogo cha uwezo wa umeme, mipaka ya umri imeshinda, na inaweza kusababisha matatizo ya mfumo.
1. Utafiti wa Matukio ya Kupungua Uwezo
1.1 Usambazaji wa Tofauti za Tafiti
Capacitors za umeme zenye ukali wa umeme wa 10 kV na uwekezaji wa 100 kvar zilichaguliwa kama sampuli za tafiti, kufanana na mahitaji ya GB/T 11024.1—2019, Shunt capacitors for a.c. power systems with a rated voltage above 1000 V – Part 1: General. Mfumo wa tafiti ulikuwa una OMICRON CP TD1 capacitance tester na ME632 dielectric loss analyzer, na joto kilikuwa kimewekwa kwa KSP-015 high-temperature aging chamber. Viwango vitatu vya joto—70 °C, 85 °C, na 100 °C—vilivyowekezwa, na sampuli tano vilivyotathmini kila viwango. Msimulizi wa tafiti ulielekea IEC 60871-2, kutumia ukali wa umeme wa kutosha kwa muda wa kupungua ili kutafsiri masharti halisi za kutumia.
1.2 Matumizi ya Kupungua Dielectric Loss
Kwenye joto kikuu, dielectric loss (tanδ) iliepuka kwa wingi kulingana na joto. Kwenye 70 °C, tanδ iliongeza polepole kwa muda, ikabaki ndani ya vipimo vya kutumia, kunainamisha ustawi wa insulation. Kwenye 85 °C, kiwango cha ongezeko kilivivutishwa, na mwendo wa kuratibu kuwa wa upinde; baadhi ya sampuli ziliteleza vipimo vya kawaida kwenye hatua za mwisho. Kwenye 100 °C, tanδ iliruka kwa nguvu na kuratibu wa upinde, kunainamisha sifa sahihi za thermal aging.
1.3 Matumizi ya Kupungua Capacitance
Ongezeko la joto lilikuwa limetathmini ustawi wa capacitance, na kubainisha tabia tofauti. Kwenye joto chache, sarafu ya capacitance ilibaki ndani ya vipimo vya kukubaliwa, kunainamisha ustawi mzuri. Katika eneo la joto wa kati, capacitance ilianza kupungua kwa wingi, na sarafu yake ikarudi karibu na vipimo vya kutumia. Kwenye joto kikuu, capacitance ilipungua kwa haraka, ikateleza vipimo vya kukubaliwa, kunainamisha kupungua kwa haraka.
2. Unda Modeli ya Matumizi ya Mipaka ya Umri
2.1 Tathmini ya Data ya Kupungua Uwezo
Kwa kulinganisha kiwango cha kupungua kwenye viwango mbalimbali vya joto, uhusiano kati ya joto na factor wa kupunguza ulitathmini. Kikomo cha kuharibika kiliundwa kwa kutumia viwango muhimu kama vile dielectric loss, sarafu ya capacitance, na resistance ya insulation. Matokeo yalitoea kwamba kupungua uwezo kilikuwa kinapongezeka kwa wingi kwenye joto kikuu, na factor wa kupunguza ulikuwa na uhusiano wa exponential na joto. Kutumia data fitting iliyopatikana correlation coefficient wa juu, kunainamisha umuhimu wa tatizo la hisabati. Equation ya Arrhenius ilikutumika kutathmini factor wa kupunguza, kuchakata energy ya activation na Boltzmann’s constant kutoka kwa majaribio, kwa hivyo kuunda uhusiano wa quantitative temperature-acceleration.
2.2 Tumia Modeli ya Arrhenius
Kama inavyoonyeshwa kwenye Chapa 1, data ya tafiti iliyowekwa kwenye log-lifetime vs. inverse temperature (1/T) coordinate system, iliyopatikana linear correlation ya nguvu. Mteremko wa mstari uliyosambaza unatafsiriwa kama energy ya activation Ea (kwenye kJ/mol), ambayo hutafsiriwa kama barrier ya energy ya process ya kupungua, na inafanana vizuri na expectations za theory. Correlation coefficient wa juu unahusu agreement nzuri kati ya data ya tafiti na modeli ya Arrhenius. Analysis ya 95% confidence interval inaonyesha predictions za kuhesabiwa. Matokeo ya tafiti yanatosha kwamba, kwenye eneo la joto linalotathmini, kiwango cha kupungua uwezo ni exponential kwa wingi kulingana na joto. Kwa kutumia data ya umri kwenye viwango mbalimbali vya joto, modeli ya hesabu kati ya joto na umri wa kutumia iliyoundwa.
2.3 Imelekeza Matumizi ya Mipaka ya Umri
Tumia matumizi ya mipaka ya umri ni kulingana na teoria ya cumulative damage, ambayo husambaza athari za damage kwenye masharti mbalimbali vya joto. The prediction method comprehensively considers factors such as material aging rate, environmental temperature fluctuations, and load variations. The operating cycle is divided into n time intervals, with the damage in each interval determined by the operating temperature and duration. Temperature data are acquired through an online monitoring system with a sampling interval of 1 h to ensure data continuity and accuracy. The measured temperatures are input into the Arrhenius equation to calculate the equivalent operating time for each interval. The accumulated damage across all intervals yields the predicted remaining service life [4]. The prediction accuracy is validated using accelerated aging test results, with the average deviation between model calculations and experimental data maintained within ±8%.
3. Matumizi na Uthibitisho
3.1 Tathmini ya Uwiano wa Matumizi
The prediction model is verified using a combined approach of accelerated aging tests and actual operational data. Multiple batches of power capacitors with different service durations are selected for performance testing, and the results are compared with model predictions. As shown in Table 1, for the 5-year operating group, the measured average life is 4.8 years and the predicted value is 5.2 years, yielding a relative error of 7.7%; for the 8-year group, the measured value is 7.6 years and the predicted value is 8.3 years, with a relative error of 8.4%; for the 10-year group, the measured value is 9.5 years and the predicted value is 10.2 years, resulting in a relative error of 6.9%. Error source analysis shows that environmental temperature fluctuations are the primary factor affecting prediction accuracy. When the daily temperature variation exceeds 20 °C, the model prediction error increases to 12%. Additionally, temperature fluctuations caused by load variations contribute to an increase in prediction error by 4.2%.
3.2 Maendeleo ya Matumizi ya Ujenzi
As shown in Table 2, when the ambient temperature is maintained below 75 °C, the rate of equipment life degradation decreases by 58%. For every 5 °C reduction in installation location temperature, the expected service life increases by 18.5%. By improving ventilation, the ambient temperature at the test site was reduced by an average of 7.2 °C, resulting in a 32% improvement in the stability of capacitor performance parameters. Temperature data from the online monitoring system indicate that after implementing intelligent ventilation, the maximum temperature around the equipment decreased by 11.3 °C and the average temperature by 8.7 °C. The life prediction model was applied in a 500 kV substation for one year, successfully issuing early warnings for six potential failures, increasing preventive maintenance efficiency by 43%. Maintenance data analysis shows that maintenance and replacement decisions based on model predictions achieved an accuracy of 87%, representing a 35% improvement over traditional time-based maintenance. The model-guided equipment management strategy reduced maintenance costs by 27% and increased equipment availability by 15%.
4. Mwisho
Through systematic accelerated aging tests and data analysis, this study reveals the influence of high-temperature environments on the performance degradation of power capacitors and establishes a life prediction model based on the Arrhenius equation. Experimental results show that ambient temperature is a key factor affecting capacitor life: for every 10 °C increase in temperature, service life decreases by 42.5% ± 2.5%. Critical performance parameters such as dielectric loss, capacitance, and insulation resistance exhibit significant degradation trends with rising temperature. The developed life prediction model achieves a prediction accuracy of over 90%, providing a scientific basis for maintenance and replacement decisions of power capacitors.
