Smart Real-time Transformer Winding Prognosis System using Cloud Service

Project: Research project

Grant Program

Faculty Development Competitive Research Grant Program 2018-2020

Project Description

Intelligent condition monitoring deals with all items of equipment in power system and when it comes to transmission system it pays more attention to those with higher capital and maintenance expenses such as transformers. Transformers are in service in various climates as well as different electrical and mechanical conditions [1]. Based on this fact, transformers are continually facing enormous hazards over the course of operation [2]- [3]. On the other hand, yielding information continuously from insulation system condition and having a reasonable understanding about internal mechanical stability is vitally important for the system operators [4]. In practice, various types of faults are jeopardizing transformers steady state operation and tending to take this expensive equipment out of service. In this regard, one of the main problems in transformers is mechanical defect. Hence, mechanical diagnostic methods have been emerged to recognize transformer active part displacement as well as winding deformation. Various methods such as Low Voltage Impulse (LVI), Frequency Response Analysis (FRA) and Short Circuit Impedance (SCI) have been employed for off-line mechanical defects recognition in transformers [5]- [10]. Since the researchers are showing an increased concern about the energy efficiency in the smart grid context, there are some mixed feelings towards on-line high voltage prognosis/diagnosis solution and how this solution is connected to smart grid later. Transformer tank vibration [11], [12], communication technique using scatter parameters [13], current deformation coefficient [14], ultrasonic method [15], short circuit impedance [16]- [21] and winding stray reactance [22], [23], on-line Transfer Function (TF) using time domain or frequency domain [24], [25] have been introduced as advanced on-line methods in order to real-time recognition of transformer winding deformation or displacement. The method of Frequency Response Analysis (FRA) has been introduced and widely employed in the power industry. This method has been studied for many years, and it has already IEEE, IEC standards [26], [27]; however, FRA implementation is still conducting off-line after many years. To perform FRA technique in current form in industry, the entire connection of transformers should be disconnected from the powerline and transformer is totally isolated. This work is impossible to perform in many places (e.g. arc furnace transformer, gas insulated substation transformers, etc). It is also time consuming and very costly for companies. Industry showing huge interest and demand to address this problem via an online (real-time) technique, but significant research study need to be conducted on this issue to develop a technique, address all the challenges and turn off-line application of FRA method to online (real-time) application. Not only transformer manufacturers are interested to find online FRA technique and obtaining its device for new transformer production, but also transformer owners and operators are interested significantly to install such a system on their used transformers. Therefore, a new technique and system is required to be able to cover and support both new and old used transformers in different voltage level.
StatusActive
Effective start/end date3/20/1812/31/20

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Transformer windings
Frequency response
Short circuit currents
Industry
Electric potential
Transformer substations
Defects
Acoustic impedance
Mechanical stability
Condition monitoring
Transfer functions
Energy efficiency
Insulation
Hazards
Furnaces
Ultrasonics
Communication
Gases