针对锂离子电池的健康因子提取困难而导致电池健康状况(state of health,SOH)预测精度低的问题,提出一种基于Douglas-Peucker融合闵式距离的锂电池健康因子特征提取算法,并利用该算法对恒流恒压充电恒功率放电策略下的电池数据进行特征...针对锂离子电池的健康因子提取困难而导致电池健康状况(state of health,SOH)预测精度低的问题,提出一种基于Douglas-Peucker融合闵式距离的锂电池健康因子特征提取算法,并利用该算法对恒流恒压充电恒功率放电策略下的电池数据进行特征提取,进而实现对锂电池的SOH预测。首先对测量的实验数据建立特征工程,利用闵式距离建立评价指标,实现基于Douglas-Peucker算法的电池健康因子提取,进而得到34维健康因子。然后,针对所提取的健康因子,利用差分变异头脑风暴(difference-mutation brainstorm optimization,DBSO)算法进行寻优,剔除不相关和冗余的特征,避免模型过拟合,提高模型性能。最后,利用支持向量机(support vector machines,SVM)及其优化模型对所提取的健康因子进行电池SOH预测。实验结果表明,所建立的特征工程提取的健康因子在SVM各模型中拟合优度均超过0.96,其中DBSO-SVM模型的预测精度最高,预测效果最好,平均绝对值误差(mean square error,MSE)值低于3。结合不同充放电策略,将所提出的特征提取算法在NASA数据上验证。结果表明,在SVM模型上,电池B0005、B0006、B0007的拟合优度达到0.99,均方根误差(root mean square error,RMSE)值均低于6%。对比多种优化算法,DBSO-SVM模型的性能最好。展开更多
Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This l...Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness.展开更多
基金supported by the National Natural Sci-ence Foundation of China(No.52077195).
文摘Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness.
