摘要
针对35 kV电力变压器运行故障高精度预警的需求,开展基于油中溶解气体分析的自动预警方法研究。通过建立变压器内部故障与油中溶解气体之间的复杂关系函数,实现对变压器内部故障类型的准确识别。进一步从变压器运行数据中提取关键特征,包括气体含量比值、温度变化趋势等,为预测模型提供输入。引入LSTM网络预测气体含量,并结合设定的预警阈值实现故障的自动预警。通过实例应用证明,该方法能够准确预测变压器油中溶解气体的含量,并及时发出预警信号,有效避免变压器故障导致的电力中断和安全事故,提高电力系统的稳定性和可靠性。该方法为35 kV电力变压器的运行维护提供了有力的技术支持。
In order to meet the demand of high-precision fault early warning for 35 kV power transformers,an automatic early warning method based on dissolved gas analysis in oil was developed.By establishing the complex relationship function between the internal fault of transformer and the dissolved gas in oil,the accurate identification of the internal fault type of transformer is realized.Further,key features,including gas content ratio and temperature trend,are extracted from transformer operation data to provide input to the prediction model.The LSTM network is used to predict the transformer gas content,and the alarm threshold is set to realize the automatic fault warning.The practical application shows that the method can accurately predict the content of dissolved gas in transformer oil,send early warning signal in time,effectively avoid power interruption and safety accident caused by transformer fault,and improve the stability and reliability of power system.This method provides powerful technical support for the operation and maintenance of 35 kV power transformers.
作者
张昊
张晓宇
蒋法兵
ZHANG Hao;ZHANG Xiaoyu;JIANG Fabing(Electrical Center of Shandong Yulong Petrochemical Co.,Ltd.,Yantai 265700,China)
出处
《电工技术》
2025年第14期226-228,231,共4页
Electric Engineering
关键词
电力变压器
自动预警
运行故障
electricity transformer
automatic early warning
operation failure
