Supplementary Files
Keywords
Dissolved Gas Analysis
Condition Monitoring
TDCG Method
Key Gas Ratio Method
How to Cite
Abstract
Distribution transformer is a unique asset in a solar farm. While solar panels capture sunlight, the inverter converts it into usable electricity, and the distribution transformer is the key component that enables the seamless delivery of this energy. Fault-free operation of this transformer ensures a proper power supply to the grid. Condition monitoring of transformers is critical for ensuring reliability and extending the operational lifespan at solar farms. Data-driven condition monitoring is one of the most effective approaches for enhancing the operational lifetime of this transformer. This research presents a comprehensive analysis of Dissolved Gas Analysis (DGA) data to predict potential faults in distribution transformers. Utilizing IEEE standards as a validation framework, the Key gas ratio method, Total Dissolved Combustible Gas (TDCG), and Principal gas concentration approaches were employed to identify faults and assess transformers health. The results were analysed using MATLAB software with an M-code algorithm. In this paper, the exceedance level of TDCG (2324 ppm) in transformer 2 is highlighted. Additionally, the CO?/CO ratios for station transformers 1 to 6 were 7.5, 5.5, 7.6, 7.3, 7.5, and 7.9, respectively. However, in transformer 4, the CH?/H? ratio was also noted to be 0.09. This concentration exceeded the IEEE standard thresholds and was indicative of overheated cellulose and partial discharge faults respectively. The proposed scheme is designed to assist in reducing suspected faults in transformers by enabling timely action based on validated data. This monitoring process can make a significant contribution to reducing the maintenance cost of a solar farm.
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