A Method for Fans’ Potential Malfunction Detection of ONAF Transformer Using Top-Oil Temperature Monitoring

Abstract

The fan is one of the key components of the power transformer cooling system. The operating condition of fans determines transformers' internal temperature rise and long-term reliability. However, at present, the fans' condition monitoring only includes switch status (online) and regular maintenance (offline), online direct monitoring of the fans' operating condition is lacking due to economic costs. In view of the above-mentioned problem, this paper proposes a transformer fan early fault detection method based on the oil exponent, which is monitored by the existing transformer top oil temperature data, thereby detecting the abnormality of the fans. In this method, the oil exponent was chosen as the characteristic criterion. First, to obtain the range of oil exponent in different cooling modes, a set of physical models describing global oil flow and its interaction with air was established based on fluid dynamics and heat transfer principle. Then, regarding the constantly changing top-oil temperature, ambient temperature and load current, an oil exponent tracking algorithm using particle swarm optimization (PSO) was proposed within an improved IEC dynamic thermal model. The operation data from an oil-immersed transformer with a rated capacity of 120-MVA and rated voltage of 220-kV was selected to verify the above methods under two different scenarios.INDEX TERMS Power transformer, cooling system, fan, top-oil temperature, condition monitoring, oil exponent This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

Acoustic-Based Online Monitoring of Cooling Fan Malfunction in Air-Forced Transformers Using Learning Techniques

“…Most utilities only have access to online information on whether the cooling fans are working or not. However, this method cannot detect cooling systems malfunctioning [11]. Despite their limitations, online methods have the potential for malfunctioning detection allowing for the timely detection of faults and early alerts [12].…”

“…In the existing literature, malfunction detection of cooling fans, which serve as critical components in AF transformers and auxiliary equipment in oil-type transformers, has not received much attention. A novel approach to early fault detection in oil-immersed transformer fans was proposed in [17]. Based on existing top-oil temperature data, the oil exponent concept was utilized as a parameter of fan operation.…”

“…Based on existing top-oil temperature data, the oil exponent concept was utilized as a parameter of fan operation. A physical model for malfunction detection in cooling fans of ONAF power transformers was presented in [18] by monitoring top-oil temperature and using an oil exponent as the critical criterion. In [19] an improved online presented method was proposed for estimating the hot-spot temperature of ONAN transformers when auxiliary cooling fans are employed.…”

Thermal evaluation optimization analysis for non‐rated load oil‐natural air‐natural transformer with auxiliary cooling equipment

“…But the above investigations mainly aimed at the improvements of transformer design, which means that a new transformer needs to be replaced. In addition, for the ONAN transformers in operation, adding the cooling fan is an effective auxiliary heat dissipation measure [15]. The influence of the blowing direction, offset, and mounting arrangement of the cooling fan on the heat dissipation performance of panel-type radiator was investigated in [16][17][18].…”