基于LSTSVR模型预测STATCOM晶闸管阀组本体温度

LSTSRVR Model Based Prediction of STATCOM Thyristor Valves Temperature

STATCOM晶闸管阀组本体温度过高,会导致其失效。因此及时、准确地预测出STATCOM晶闸管阀组本体温度对提高STATCOM运行的可靠性至关重要。本文利用最小二乘双支持向量回归机(least square twin support vector regression,LSTSVR)算法,将STATCOM进水温度、回水温度、进水流量、IGBT模块散热材料的导热系数、STATCOM输出电压、STATCOM输出电流、晶闸管阀组的集电极电流共7个量作为输入量,构建了STATCOM晶闸管阀组本体温度预测模型。与现场实测数据对比的结果表明,利用LSTSVR模型实现了STATCOM晶闸管阀组本体温度的高精度预测,且模型的预测精度优于最小二乘支持向量回归机(least square support vector regression,LSSVR)模型。应用实例也验证了该方法的准确性和有效性。

The excessive temperature of STATCOM thyristor valves will lead to their cracking and even breakdown.Therefore,timely and accurate prediction of the temperature is essential to improve the safety and reliability of STATCOM thyristor valves operation.Based on the least square twin support vector regression(LSTSVR)and seven input values such as STATCOM water temperature,return water temperature,water supply flow,thermal conductivity of heat dissipating material of IGBT module,STATCOM output voltage,STATCOM output current,and collector current of gate valve set,a monitoring system is constructed to predict the temperature of STATCOM thyristor valves.The comparison with the field measured data shows that the LSTSVR model achieves the accurate prediction of STATCOM thyristor valves temperature,and the prediction accuracy of the model is better than the least square support vector regression(LSSVR)model.The effectiveness and reliability of the method are proved by practical cases.