为提高风电机组系统的运行效率和稳定性,提出一种基于数据驱动的风电机组能效状态分析方法,实现对机组异常状态的高效检测与预警。首先从损耗与效率的角度出发,开展各因素对机组能效的影响分析,考虑到系统各部件能量损失主要体现在热量...为提高风电机组系统的运行效率和稳定性,提出一种基于数据驱动的风电机组能效状态分析方法,实现对机组异常状态的高效检测与预警。首先从损耗与效率的角度出发,开展各因素对机组能效的影响分析,考虑到系统各部件能量损失主要体现在热量方面,因此以温度参数为依据,建立基于能量流的能效状态指标体系。然后利用风电机组数据采集与监视控制(supervisory control and data acquisition,SCADA)系统采集数据,确定各参数基准区间,构建指标偏离度矩阵,利用改进的鲸鱼算法(improved whale optimization algorithm,IWOA)优化支持向量机,实现对能效异常状态的检测。同时引入能效异常指数来表征机组能效变化情况,利用自回归滑动平均模型-支持向量机(autoregressive moving average model-support vector machines,ARMA-SVM)组合模型实现能效的时间序列预测。最后以1.5 MW双馈异步风电机组为研究对象开展算例分析。结果表明该方法能够实现对能效异常状态的有效检测和预警,为风电机组的性能优化与故障分析提供了必要的决策参考。展开更多
The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking th...The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslid展开更多
文摘为提高风电机组系统的运行效率和稳定性,提出一种基于数据驱动的风电机组能效状态分析方法,实现对机组异常状态的高效检测与预警。首先从损耗与效率的角度出发,开展各因素对机组能效的影响分析,考虑到系统各部件能量损失主要体现在热量方面,因此以温度参数为依据,建立基于能量流的能效状态指标体系。然后利用风电机组数据采集与监视控制(supervisory control and data acquisition,SCADA)系统采集数据,确定各参数基准区间,构建指标偏离度矩阵,利用改进的鲸鱼算法(improved whale optimization algorithm,IWOA)优化支持向量机,实现对能效异常状态的检测。同时引入能效异常指数来表征机组能效变化情况,利用自回归滑动平均模型-支持向量机(autoregressive moving average model-support vector machines,ARMA-SVM)组合模型实现能效的时间序列预测。最后以1.5 MW双馈异步风电机组为研究对象开展算例分析。结果表明该方法能够实现对能效异常状态的有效检测和预警,为风电机组的性能优化与故障分析提供了必要的决策参考。
基金The authors would like thank LI Renjiang and HU Bin from the China Three Gorges Corporation for providing many valuable suggestions for the establishment of the physical models.This work was supported by the National Natural Science Foundation of China(No.U23A2045)the China Three Gorges Corporation(YM(BHT)/(22)022)the Scientific Research Project of Chongqing Municipal Bureau of Planning and Natural Resources(Evaluation and Reinforcement Technology of Surge Disaster Caused by High and Steep Dangerous Rocks in Chongqing Reservoir Area of the Three Gorges Project,KJ-2023046).
文摘The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslid
