مدل ترکیبی تعمیر‏و‏نگهداری پیشگیرانه و پیشبینانه ترانسفورماتور قدرت (مطالعه موردی: شرکت برق منطقه ‏ای خراسان)

نوع مقاله : مقاله برق

نویسندگان

1 دانشگاه آزاد اسلامی، واحد نیشابور

2 دانشگاه حکیم سبزواری

3 دفتر فنی انتقال، معاونت بهره برداری، شرکت برق منطقه خراسان

4 دانشگاه آزاد اسلامی، واحد نیشابور، نیشابور، ایران

چکیده

با نصب سنسور هوشمند و تشخیص زود هنگام خرابی‏های جزئی، می‏توان تعمیر‏و‏نگهداری پیشبینانه را به تعمیر‏و‏نگهداری دوره‏ای تجهیز اضافه کرد. هدف از این مقاله ارائه مدل جدید تعمیر‏و‏نگهداری پیشگیرانه و پیشبینانه ترکیبی مارکوف تجهیز می‏باشد. برای رسیدن به این هدف سه گام برداشته شده است. گام اول به بررسی تحلیلی انواع خرابی‏های تجهیز پرداخته شده است. بدین منظور مدل ریاضی جهت محاسبه نرخ‏های سطوح مختلف خرابی ارائه شده است. بعلاوه اثر نصب سنسور هوشمند بر نرخ‏های خرابی مدل‏سازی شده است. در این مدل‏سازی احتمال خرابی سنسورها نیز لحاظ شده است.‏ با توجه به تجربه بهره‏برداران شبکه، خرابی‏های تجهیز به 4 سطح خرابی دسته‏بندی شده است، که مهمترین آن‏ها نرخ خروج ناخواسته و نرخ خروج اضطرای است. در گام دوم مدل جدید تعمیر‏و‏نگهداری پیشگیرانه و پیشبینانه ترکیبی مارکوف جهت آنالیز نصب سنسور هوشمند بر روی تجهیز ارائه شده است. با نصب سنسور هوشمند تعدادی از خرابی‏هایی که نیاز مبرم به تعمیر دارند شناسایی و با خروج اضطراری اصلاح می‏شوند. بنابراین فرکانس رفتن به تعمیر‏و‏نگهداری، عمر تجهیز و هزینه‏های تعمیر‏و‏نگهداری در مدل جدید ارائه شده مارکوف نسبت به مدل تعمیر‏و‏نگهداری پیشگیرانه بهبود پیدا می‏کند. در گام سوم خرابی‏های ترانسفورماتورهای قدرت شرکت برق منطقه‏ای خراسان با سطح ولتاژ 400 کیلو‏ولت و 132 کیلو‏ولت مطالعه شده اند. نتایج شبیه سازی نشان می‏دهد که با مدل جدید مارکوف ارائه شده، نرخ خروج ترانسفورماتورهای 400 و 132 کیلو‏ولت به ترتیب به مقدار %12/74 و %51/54 کاهش پیدا می‏کند و متوسط عمر جایگزینی به ترتیب به مقدار 4/28 و 4/20 سال افزایش پیدا می‏کند

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Combined preventive and predictive maintenance model of power transformers (Case study: Khorasan Regional Electricity Company)

نویسندگان [English]

  • Ali Karimabadi 1
  • Mohammad Ebrahim Hajiabadi 2
  • ebadollah Kamyab 3
  • Aliasghar shojaei 4
1 Islamic Azad University of Neyshabur
2 Hakim Sabzevari University
3 Khorasan Regional Electricity Company (KREC), Mashhad, Iran
4 Islamic Azad University of Neyshabur, Neyshabur, Iran
چکیده [English]

By installing the smart sensor and early detection of minor failures, the predictive maintenance can be added to the periodic maintenance. The purpose of this paper is to present a new preventive and predictive maintenance Markov model. For this at the first step, the various types of equipment failures are analysed. Therefore, a mathematical model is presented to calculate the rates of failures at various levels. In addition, the effect of smart sensor instalation on these failure rates has been modelled. In this modelling, the failure probability of the sensor is also considered.The equipment failures are classified into four levels of failure. The most importants failures rates are the outage failure rate and emergency failure rate. In the second step, a new Integrated preventive and predictive maintenance Markov model to consider the effect of smart sensor installation on equipments in maintenance process is presented. By installing the smart sensor, a number of high severity failures are early identified and corrected by emergency outages. So the frequency of going to major maintenance, the lifetime and maintenance costs in the new Markov model is improved with respect to the preventive maintenance model. At the third step, the failures of 400 kv and 132 kv power transformers of Khorasan Regional Electricity Company (KREC) were studied. The simulation results show that with new Markov model, the outage rates of 400 kv and 132 kv transformers are reduced by 74.12% and 54.51%, respectively, and the lifetimes are increased 28.4 and 20.4, respectively

کلیدواژه‌ها [English]

  • Reliability
  • preventive maintenance
  • predictive maintenance
  • smart sensors
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