State Prediction Method of Power Transformer Based on Grey Differential Threshold

The power transformer is one of the core equipment of the power system. Transformer faults will directly affect the stability of the power system and cause irreversible losses to the transformer itself. Predicting the operating status of power transformers and timely withdrawing transformers that have deteriorated is of great significance to the power system. Currently, most of the work of state prediction is mainly based on the relationship between the actual state value and the predicted state value based on the oil chromatographic data, and the existing methods have poor prediction accuracy for large fluctuation faults and have no practical application value. This paper proposes a method for predicting the state of equipment by predicting transformer differential thresholds to determine equipment operating trends. This method judges the state of the system by predicting the difference threshold. It realizes the early warning of the state of the equipment and prevents the system from oscillating due to the faults of the transformer. In practical applications. The fault conditions in accordance with actual conditions were obtained by this method. The method proposed in this paper focuses on the impact of historical data on predictions, overcomes the problem of prediction accuracy caused by sudden changes in the external environment, and has more practical application value than existing state prediction methods.