Project Progress

Development 100%
  • Project Supervisor: Mehdi Bagheri
  • Ending date: May 2018
  • Location: Nazarbayev University, Astana, Republic of Kazakhstan

Description:

The majority of available commercial transformer diagnosis methods are being performed off-line once the transformer is out of service. Utility management and service operators have to disconnect their transformers from main feeders during the diagnostic test. However, transformer isolation from the grid out of predetermined overhaul schedule is quite costly and time-consuming task. Therefore, the majority of the grids are unwilling to disconnect the transformer unless it is become urgent and required. Transformer mechanical defect recognition needs that a real-time method is utilized to assess transformer mechanical integrity. Online Short Circuit Impedance (OSCI) measurement and V-I locus diagram have been introduced years ago to assist and address this problem and recognize transformer mechanical deformation. The latter technique is based on the analysis of the voltage and current signals. Any deviation of the V-I locus with respect to the reference signature can indicate the presence of the deformation in the transformer. On the other hand, application of the Internet of Things (IoT) in all aspects of the industry is becoming popular in this new century. Researchers are now working on predictive maintenance and prognosis methods based on IoT structure. Access to the transformer information from all four corners of the globe is crucial. Hence this study is specifically focused to develop and implement real-time transformer V-I locus diagnosis method over cloud environment and evaluate data through cloud computing. Transformer mechanical fault recognition is discussed and voltage/current method is highlighted. Turn-to-turn short circuit fault is emulated over a distribution transformer and practical study is performed. Data obtained from practical measurement is evaluated over cloud environment and transformer assessment is performed via application over the portable device, which is connected to the cloud. A new protection relay is developed and connected to the transformer that can be activated via cloud outcome.

Project Team

Project team consists of BSc capstone project students from Nazarbayev university.

Team Leader: Nurtas Moldiyar

Nurtas Moldiyar
Nurbolat Bazarbek
Aigerim Borasheva
Altynay Smagulova

Contacts

To contact the project group use one the following contact links:

Phone: +7 (777) 504-94-83

Email: mehdi.bagheri@nu.edu.kz

Address: Kabanbay Batyr 53, Astana, Republic of Kazakhstan

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