Investigation of Transformer Maintenance Scheduling Based on Dissolved Gas Analysis of Insulating Oil

Transformers are essential components in power systems, and their reliability must be ensured through timely maintenance. Conventional inspection and maintenance practices often follow fixed schedules regardless of the transformer’s actual condition, which may result in unnecessary costs or delayed detection of potential failures. To address this issue, this study proposes an optimized maintenance strategy based on dissolved gas analysis (DGA) of transformer insulating oil, focusing on carbon monoxide (CO) and carbon dioxide (CO₂) concentrations as key indicators of insulation degradation. By analyzing inspection records and statistical data, four condition-based inspection cases are developed and compared with the existing periodic maintenance standards adopted by utilities such as KEPCO. The analysis evaluates inspection intervals, labor costs, and cost-saving potential while considering the effectiveness of detecting insulation deterioration. Results show that condition-based inspection using CO and CO₂ thresholds can reduce unnecessary inspections and achieve significant cost savings, while also contributing to transformer life extension and improved system reliability. This study demonstrates that incorporating DGA into inspection scheduling provides a more efficient and economical maintenance framework compared to conventional time-based approaches. The findings highlight the importance of adaptive maintenance strategies for enhancing asset management and ensuring stable power supply.