Modi, Mitul M.
Intelligent approach to interpret incipient faults of power transformer from DGA database - Vol.104(4), Aug - USA Springer 2023 - 869-876p.
Power transformer is most powerful and expensive tool in power system for transmitting and distributing electrical energy to all consumers. High-voltage transformers in power system are oil-immersed type transformer. Use of oil provides much needed cooling, insulation, and reduces vibrations to power transformer. Oil of the power transformer is monitored and diagnosed on a regular basis to preserve its dependability and efficiency. Dissolved gas analysis (DGA) is effective and efficient tools to interpret incipient faults. In DGA method, dissolved gases like H, CH, CH, CH, CH are extracted from oil. Based on the gases threshold values in oil, different faults are identified. The current article focus on three traditional fault diagnostic methods IEC, Roger ratio, and Duval triangle and one artificial neural network-based intelligent method. Result spot light that intelligent methods gives higher accuracy and consistency to identify the incipient faults of power transformer while traditional methods are proved inadequate, inaccurate and inconsistent.
Humanities and Applied Sciences
Intelligent approach to interpret incipient faults of power transformer from DGA database - Vol.104(4), Aug - USA Springer 2023 - 869-876p.
Power transformer is most powerful and expensive tool in power system for transmitting and distributing electrical energy to all consumers. High-voltage transformers in power system are oil-immersed type transformer. Use of oil provides much needed cooling, insulation, and reduces vibrations to power transformer. Oil of the power transformer is monitored and diagnosed on a regular basis to preserve its dependability and efficiency. Dissolved gas analysis (DGA) is effective and efficient tools to interpret incipient faults. In DGA method, dissolved gases like H, CH, CH, CH, CH are extracted from oil. Based on the gases threshold values in oil, different faults are identified. The current article focus on three traditional fault diagnostic methods IEC, Roger ratio, and Duval triangle and one artificial neural network-based intelligent method. Result spot light that intelligent methods gives higher accuracy and consistency to identify the incipient faults of power transformer while traditional methods are proved inadequate, inaccurate and inconsistent.
Humanities and Applied Sciences