The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric componen...The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.展开更多
针对电力电子化配电网谐波源随机波动引发的治理效率与成本问题,提出融合谐波源随机表征与多目标粒子群-遗传算法(multi-objective particle swarm optimization-genetic algorithm,MOPSO-GA)的并联有源电力滤波器(shunt active power f...针对电力电子化配电网谐波源随机波动引发的治理效率与成本问题,提出融合谐波源随机表征与多目标粒子群-遗传算法(multi-objective particle swarm optimization-genetic algorithm,MOPSO-GA)的并联有源电力滤波器(shunt active power filter,SAPF)优化配置策略。基于中心极限定理,采用正态分布与均匀分布构建谐波幅值与相位的概率模型,结合MOPSO-GA算法实现多目标优化。仿真结果表明,在IEEE 18节点系统中仅配置3台SAPF即可将总谐波畸变率从19.88%降至3.32%,电压偏差从10.4%控制至4.5%,SAPF较传统MOPSO算法减少1台,总容量更经济,算法收敛速度与帕累托前沿分布性显著提升。并进一步通过RT-Lab半实物实验平台验证,在真实谐波源下将关键节点谐波电压畸变率从25.24%降至2.12%,该策略为复杂配电网谐波治理提供高效经济的解决方案。展开更多
文摘The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.
文摘针对电力电子化配电网谐波源随机波动引发的治理效率与成本问题,提出融合谐波源随机表征与多目标粒子群-遗传算法(multi-objective particle swarm optimization-genetic algorithm,MOPSO-GA)的并联有源电力滤波器(shunt active power filter,SAPF)优化配置策略。基于中心极限定理,采用正态分布与均匀分布构建谐波幅值与相位的概率模型,结合MOPSO-GA算法实现多目标优化。仿真结果表明,在IEEE 18节点系统中仅配置3台SAPF即可将总谐波畸变率从19.88%降至3.32%,电压偏差从10.4%控制至4.5%,SAPF较传统MOPSO算法减少1台,总容量更经济,算法收敛速度与帕累托前沿分布性显著提升。并进一步通过RT-Lab半实物实验平台验证,在真实谐波源下将关键节点谐波电压畸变率从25.24%降至2.12%,该策略为复杂配电网谐波治理提供高效经济的解决方案。
