随着新能源并网进程的推进,风电装机规模逐年扩大。受区域内天气变化影响,风机出力的间歇性和波动性特征对电网的威胁亦越发显著。极端天气所引发的风电出力异常爬坡事件,易导致电网功率失衡,对电力系统机组调度、源荷平衡造成了极大压...随着新能源并网进程的推进,风电装机规模逐年扩大。受区域内天气变化影响,风机出力的间歇性和波动性特征对电网的威胁亦越发显著。极端天气所引发的风电出力异常爬坡事件,易导致电网功率失衡,对电力系统机组调度、源荷平衡造成了极大压力。合理的风电爬坡事件检测以及精准的风电功率预测能为风电场运维及电力系统调度提供先验指导,有力缓解风电不确定性带来的危害。首先讨论了目前主流风电爬坡事件定义的盲点,分类并分析了3种风电爬坡场景的功率变化特性,据此提出基于滑动窗双边累计和(cumulative sum, CUSUM)算法的风电爬坡事件检测方法,提取时序耦合信息,捕捉短时间窗口内风电功率数据的异常波动,提高风电爬坡事件检测精度。其次,采用贝叶斯优化的长短期记忆(long short term memory, LSTM)神经网络,最优化模型超参数,提高模型对于爬坡事件发生时风机出力的预测性能。进一步应用所提风电爬坡事件检测方法,对模型预测区间内的风电爬坡事件进行检测实验,验证了所提方法的有效性。展开更多
Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part...Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part at the right time will result in damage and in some cases,loss of that part.An anti-pinch mechanism is an excellent choice to solve this problem,which detects the obstacle in the glass path immediately and moves it down.In this paper,an optimal solution H_/H_(∞)is presented for fault detection of the anti-pinch window system.The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption,the speed and the position of DC motors.In this research,a speed-based method is used to detect the obstacles.In order to secure the anti-pinch window,an optimal algorithm based on a fault detection observer is suggested.In the residual design,the proposed fault detection algorithm uses theDCmotor angular velocity rate.Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm.Finally,an optimal filter for solving the fault problem is designed using the H_/H_(∞)method.The results show that the simulated anti-pinch window is pretty sensitive to the fault,in the sense that it can detect the obstacle in 50 ms after the fault occurrence.展开更多
文摘随着新能源并网进程的推进,风电装机规模逐年扩大。受区域内天气变化影响,风机出力的间歇性和波动性特征对电网的威胁亦越发显著。极端天气所引发的风电出力异常爬坡事件,易导致电网功率失衡,对电力系统机组调度、源荷平衡造成了极大压力。合理的风电爬坡事件检测以及精准的风电功率预测能为风电场运维及电力系统调度提供先验指导,有力缓解风电不确定性带来的危害。首先讨论了目前主流风电爬坡事件定义的盲点,分类并分析了3种风电爬坡场景的功率变化特性,据此提出基于滑动窗双边累计和(cumulative sum, CUSUM)算法的风电爬坡事件检测方法,提取时序耦合信息,捕捉短时间窗口内风电功率数据的异常波动,提高风电爬坡事件检测精度。其次,采用贝叶斯优化的长短期记忆(long short term memory, LSTM)神经网络,最优化模型超参数,提高模型对于爬坡事件发生时风机出力的预测性能。进一步应用所提风电爬坡事件检测方法,对模型预测区间内的风电爬坡事件进行检测实验,验证了所提方法的有效性。
基金supported by DP-FTSM-2021,Dana Lonjakan Penerbitan FTSM,UKM.
文摘Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part at the right time will result in damage and in some cases,loss of that part.An anti-pinch mechanism is an excellent choice to solve this problem,which detects the obstacle in the glass path immediately and moves it down.In this paper,an optimal solution H_/H_(∞)is presented for fault detection of the anti-pinch window system.The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption,the speed and the position of DC motors.In this research,a speed-based method is used to detect the obstacles.In order to secure the anti-pinch window,an optimal algorithm based on a fault detection observer is suggested.In the residual design,the proposed fault detection algorithm uses theDCmotor angular velocity rate.Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm.Finally,an optimal filter for solving the fault problem is designed using the H_/H_(∞)method.The results show that the simulated anti-pinch window is pretty sensitive to the fault,in the sense that it can detect the obstacle in 50 ms after the fault occurrence.
