Condition Assessment of Oil-Immersed Transformers Based on Fuzzy Theory and Combination Weighting of Least Squares

Abstract

Oil-immersed power transformer is the key equipment to maintain the safe and stable operation of the whole power system, it is very important to improve the accuracy of the condition assessment results to keep the power system running safely and stably. Aiming at the problems that the traditional condition evaluation model of oil immersed transformer is difficult to evaluate and the evaluation result is inaccurate. A condition assessment model of oil immersed power transformer based on fuzzy theory and combination weighting of least squares is proposed in this paper. The model combines subjective weightings with objective weightings, and uses the least square method to determine the subjective and objective weight coefficients, which reduces the error impact caused by artificial subjective determination. The final transformer condition assessment results are determined by the fuzzy theory method. Using the oil-immersed transformer test data provided by a power supply company as a sample for experimental verification and analysis. The results show that the method proposed in this paper can accurately evaluate the state of oil-immersed power transformers, which has certain practical significance in engineering.