摘要
随着海上风电机组在电力系统中所占比例的不断提高,电力系统运行的经济性、安全性和稳定性将会受到海上风机故障的影响。准确预测海上风电场故障,并及时故障预警,对海上风电大规模并网运行安全至关重要。文章基于海上风机各部件的运行特性及故障情况,结合海上风电场的实际SCADA数据,利用人工神经网络对海上风机故障进行建模仿真,并提出一种海上风机故障预测方法。结果表明基于人工神经网络的海上风机故障预测方法效果良好,能有效预警海上风机故障。文章提出的故障预测方法对海上风电场的安全稳定运行具有较好的应用价值。
With the increasing proportion of offshore wind power in the power system,the economy,safety and stability of the power system operation will be affected by the failure of the offshore wind turbines.Accurate prediction of offshore wind farm faults and timely fault warning is crucial to the safe operation of large-scale grid connection of offshore wind power.Based on the operation characteristics and fault situation of each component of offshore fan,combined with the actual SCADA data of offshore wind farm,the artificial neural network is used to model and simulate offshore fan faults,and a method of offshore fan fault prediction is proposed.The results show that the offshore fan fault prediction method based on artificial neural network is effective and can effectively warn it.The fault prediction method proposed here has a good application value for the safe and stable operation of offshore wind farms.
出处
《电力系统装备》
2023年第2期113-115,共3页
Electric Power System Equipment
关键词
海上风机
机器学习
故障预测
人工神经网络
offshore fan
machine learning
fault prediction
artificial neural network
