考虑风速波动的风电机组状态评估
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摘要
风速的随机性影响了机组的运行状态,降低了机组的可靠性。为了准确、及时地在线评估风电机组的运行状态,提出了一种基于波动率的风电机组在线状态评估方法。首先,根据风速与监测参数的相关性分析和监测参数的方差、偏度、峰度和均值分析,确定了机组状态评估指标参数体系。然后,提出了对数波动率的定义,采用波动率分析机组运行指标参数的波动。通过分析正常状态机组的历史数据指标参数的波动率轨迹,确定了机组运行状态等级的划分。最后,采用双滑动窗口,实现了对机组运行状态的在线评估。将该方法用于贵州某风电场两台2 MW机组,其在线状态评估结果符合实际情况。该方法考虑了风速的随机性对机组造成的影响,为风电机组的动态研究奠定了基础。
The randomness of wind speed affects the operation status of the unit and reduces the reliability of the unit.In order to accurately and timely evaluate the operation status of wind turbines on-line,an on-line state evaluation method of wind turbines based on volatility is proposed.Firstly,according to the correlation analysis between wind speed and monitoring parameters and the analysis of variance,skewness,kurtosis and mean of monitoring parameters,the parameter system of unit status evaluation indexes are determined.Then the definition of logarithmic volatility is put forward,and the fluctuation of unit operation index parameters is analyzed by using volatility.By analyzing the fluctuation rate trajectory of historical data index parameters of normal state units,the division of operation status level of units is determined.Finally,double sliding windows are used to realize on-line evaluation of unit operation status.The method is applied in two of 2 MW units of a wind farm in Guizhou,and the on-line status evaluation results are in line with the actual situation.This method takes into account the influence of the randomness of wind speed on the unit,and lays a foundation for the dynamic research of wind turbine.
The randomness of wind speed affects the operation status of the unit and reduces the reliability of the unit.In order to accurately and timely evaluate the operation status of wind turbines on-line,an on-line state evaluation method of wind turbines based on volatility is proposed.Firstly,according to the correlation analysis between wind speed and monitoring parameters and the analysis of variance,skewness,kurtosis and mean of monitoring parameters,the parameter system of unit status evaluation indexes are determined.Then the definition of logarithmic volatility is put forward,and the fluctuation of unit operation index parameters is analyzed by using volatility.By analyzing the fluctuation rate trajectory of historical data index parameters of normal state units,the division of operation status level of units is determined.Finally,double sliding windows are used to realize on-line evaluation of unit operation status.The method is applied in two of 2 MW units of a wind farm in Guizhou,and the on-line status evaluation results are in line with the actual situation.This method takes into account the influence of the randomness of wind speed on the unit,and lays a foundation for the dynamic research of wind turbine.
引文
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[2] 贾子文,顾煜炯,邢月,等.改进专家群决策方法的风电机组故障风险评价研究[J].可再生能源,2018,36(3):453- 460.
[3] 周湶,徐清鹏,李剑,等.融合集对分析和证据理论的风电机组运行状态评估[J].电力自动化设备,2017,37(7):38- 45.
[4] 李大中,许炳坤,常城.基于熵值法的大型风电机组运行状态综合评价[J].热能动力工程,2016,31(4):1- 5.
[5] 王春梅.基于深度置信网络的风电机组主轴承故障诊断方法研究[J].自动化仪表,2018,39(10):33- 37.
[6] 徐创学,刘鲁清,谢云明,等.基于实时数据的风力发电机组性能在线评价[J].热力发电,2015,44(4):88- 91.
[7] 王小航,张妍,钟振林.基于IPSO- TSFNN的风电机组综合评价[J].计算机仿真,2016,33(1):420- 424.
[8] 王洋,孙伟,魏静,等.随机风速下风力发电机组载荷传递特性研究[J].中国机械工程,2015,26(2):152- 156.
[9] 马静,高翔,李益楠,等.考虑风速随机特征的多工况电力系统稳定性分析[J].电力自动化设备,2016,36(8):26- 32.
[10]阎洁,许成志,刘永前,等.基于风速云模型相似日的短期风电功率预测方法[J].电力系统自动化,2018,42(6):53- 59.
[11]刘旭,陈广.合成氨装置引风机组保护及控制系统浅析[J].石油化工自动化,2018,54(5):33- 35.