Fire Status Sensing of Oil-immersed Power Transformers Based on TOPSIS Method and Combination Weighting of Game Theory
Xinyu Pi, Tao Feng, Xunjian Xu, Yi Ouyang, Yahui Wang, Xingren Su · 2024
The oil-immersed power transformer plays a crucial role in ensuring the safe and stable operation of the entire power system, highlighting the significance of enhancing the precision of its fire detection Aiming at the problems of difficulty in status sensing and inaccurate sensing results of traditional oil-immersed transformer status sensing models, a fire status sensing model for oil-immersed power transformers based on TOPSIS (Technique for order preference by similarity to an ideal solution) method and combination weighting of game theory is proposed in this paper. The model combines subjective weighting with objective weighting, while using game theory to determine the subjective and objective weight coefficients, eliminating human influence, and the TOPSIS method determines the final status sensing results. The test data of oil-imm supplied by a power company serves as the verification and analysis sample. This paper focuses on the oil-immersed power transformer, a key equipment in the power system, and carries out research on fire state sensing, which promotes the progress of state sensing technology and is of great significance to ensure the safe and stable operation of the power system and the normal life of residents, and providing early warning of potential fires, which holds significant practical implications in engineering.