In contrast to the Pacific and Atlantic Oceans,the Indian Ocean has lacked in-situ observations of wind profiles over open sea areas for decades.In 2021,a shipborne coherent Doppler lidar(CDL)was used to observe in-si...In contrast to the Pacific and Atlantic Oceans,the Indian Ocean has lacked in-situ observations of wind profiles over open sea areas for decades.In 2021,a shipborne coherent Doppler lidar(CDL)was used to observe in-situ wind profiles in the eastern tropical Indian Ocean.This equipment successfully captured low-level jets(LLJs)in the region,and their characteristics were thoroughly analyzed.Results reveal that the observed wind speed of LLJs in the eastern Indian Ocean ranges from 6 m s^(-1) to 10 m s^(-1) during the boreal winter and spring seasons,showing a height range of 0.6 to 1 km and two peak times at 0800 and 2000 UTC.This wind shear is weaker than that in land or offshore areas,ranging from 0 s^(-1) to 0.006 s^(-1).Moreover,the accuracy of the CDL data is compared to that of ERA5 data in the study area.The results indicate that the zonal wind from ERA5 data significantly deviated from the CDL measurement data,and the overall ERA5 data are substantially weaker than the in-situ observations.Notably,ERA5 underestimates northwestward LLJs.展开更多
由于可再生能源的广泛接入,智能配电网面临电压波动挑战,直接导致了电压裕度增加。因此,设计了基于态势感知的智能配电网精细化日前优化调度方法。该方法构建了一个由数据捕获层、数据分析层、未来预测层构成的3层态势感知架构。基于电...由于可再生能源的广泛接入,智能配电网面临电压波动挑战,直接导致了电压裕度增加。因此,设计了基于态势感知的智能配电网精细化日前优化调度方法。该方法构建了一个由数据捕获层、数据分析层、未来预测层构成的3层态势感知架构。基于电网数据,设定约束与目标函数,建立日前调度模型。模型通过识别储能系统荷电状态(State of Charge,SoC)极值点,估算虚拟电量消耗,并线性化资本回收系数,实现精细化调度。实验显示,该方法将总电压裕度降至54.26 V,远低于同类研究,有效降低了电压裕度,提高了配电网运行效率。展开更多
基金supported by the Taishan Scholars Programs of Shandong Province(No.tsqn201909165)the Global Change and Air-Sea Interaction Program(Nos.GASI-04-QYQH-03,GASI-01-WIND-STwin)the National Natural Science Foundation of China(Nos.41876028,42349910).
文摘In contrast to the Pacific and Atlantic Oceans,the Indian Ocean has lacked in-situ observations of wind profiles over open sea areas for decades.In 2021,a shipborne coherent Doppler lidar(CDL)was used to observe in-situ wind profiles in the eastern tropical Indian Ocean.This equipment successfully captured low-level jets(LLJs)in the region,and their characteristics were thoroughly analyzed.Results reveal that the observed wind speed of LLJs in the eastern Indian Ocean ranges from 6 m s^(-1) to 10 m s^(-1) during the boreal winter and spring seasons,showing a height range of 0.6 to 1 km and two peak times at 0800 and 2000 UTC.This wind shear is weaker than that in land or offshore areas,ranging from 0 s^(-1) to 0.006 s^(-1).Moreover,the accuracy of the CDL data is compared to that of ERA5 data in the study area.The results indicate that the zonal wind from ERA5 data significantly deviated from the CDL measurement data,and the overall ERA5 data are substantially weaker than the in-situ observations.Notably,ERA5 underestimates northwestward LLJs.
文摘由于可再生能源的广泛接入,智能配电网面临电压波动挑战,直接导致了电压裕度增加。因此,设计了基于态势感知的智能配电网精细化日前优化调度方法。该方法构建了一个由数据捕获层、数据分析层、未来预测层构成的3层态势感知架构。基于电网数据,设定约束与目标函数,建立日前调度模型。模型通过识别储能系统荷电状态(State of Charge,SoC)极值点,估算虚拟电量消耗,并线性化资本回收系数,实现精细化调度。实验显示,该方法将总电压裕度降至54.26 V,远低于同类研究,有效降低了电压裕度,提高了配电网运行效率。
