The solar spectrum covers a broad wavelength range, which requires that antireflection coating (ARC) is effective over a relatively wide wavelength range for more incident light coming into the cell. In this paper, ...The solar spectrum covers a broad wavelength range, which requires that antireflection coating (ARC) is effective over a relatively wide wavelength range for more incident light coming into the cell. In this paper, we present two methods to measure the composite reflection of SiO2/ZnS double-layer ARC in the wavelength ranges of 300-870 nm (duaI- junction) and 300-1850 nm (triple-junction), under the solar spectrum AM0. In order to give sufficient consideration to the ARC coupled with the window layer and the dispersion effect of the refractive index of each layer, we use multidimensional matrix data for reliable simulation. A comparison between the results obtained from the weighted-average reflectance (WAR) method commonly used and that from the effective-average reflectance (EAR) method introduced here shows that the optimized ARC through minimizing the effective-average reflectance is convenient and available.展开更多
利用电池储能系统平滑风电功率波动可以提高风力发电站功率输出的稳定性。针对风电出力的随机性特别是骤变情况,提出一种基于加权移动平均滤波算法的储能系统平滑控制策略。该方法根据风电功率的波动程度与当前储能系统的荷电状态(state...利用电池储能系统平滑风电功率波动可以提高风力发电站功率输出的稳定性。针对风电出力的随机性特别是骤变情况,提出一种基于加权移动平均滤波算法的储能系统平滑控制策略。该方法根据风电功率的波动程度与当前储能系统的荷电状态(state of charge,SOC),通过实时调整权重系数和滤波带宽有效平滑风电功率的骤变。为了维持SOC在合理水平,在综合考虑各种约束条件后,该文采用模糊控制法设计了能够根据实时情况自动调节储能电池SOC的控制策略。算例结果表明,该文提出的控制策略在维持SOC合理水平前提下能有效平滑功率波动;同时,该文方法基于的在线信息使其具有实时应用前景。展开更多
主元分析(principal component analysis,PCA)是一种有效的数据分析方法,在故障诊断与状态监测方面已得到广泛应用.多元指数加权移动平均–主元分析(multivariate exponentially weighted moving average principal component analysis,...主元分析(principal component analysis,PCA)是一种有效的数据分析方法,在故障诊断与状态监测方面已得到广泛应用.多元指数加权移动平均–主元分析(multivariate exponentially weighted moving average principal component analysis,MEWMA–PCA)方法用于解决PCA不能有效检出微小故障的问题.本文深入研究了MEWMA–PCA中EWMA影响主元分析进行故障检测的机制,导出了MEWMA–PCA可检出微小故障的原因.本文确定了MEWMA–PCA中遗忘因子λ、单传感器故障幅值和迟延时间三者的关系,并进行了数值仿真和火电厂磨煤机组运行状态的仿真实验.实验结果验证了MEWMA–PCA中EWMA提高PCA的监测性能的机制,并给出了根据系统实际要求来选取合适的遗忘因子值,从而在规定的时间内检出微小故障的实例.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61176012 and 90921015)the National Basic Research Program of China (Grant Nos. 2010CB327601 and 2012CB932701)the National Science Foundation for Post-doctoral Scientists of China (Grant No. 20080440507)
文摘The solar spectrum covers a broad wavelength range, which requires that antireflection coating (ARC) is effective over a relatively wide wavelength range for more incident light coming into the cell. In this paper, we present two methods to measure the composite reflection of SiO2/ZnS double-layer ARC in the wavelength ranges of 300-870 nm (duaI- junction) and 300-1850 nm (triple-junction), under the solar spectrum AM0. In order to give sufficient consideration to the ARC coupled with the window layer and the dispersion effect of the refractive index of each layer, we use multidimensional matrix data for reliable simulation. A comparison between the results obtained from the weighted-average reflectance (WAR) method commonly used and that from the effective-average reflectance (EAR) method introduced here shows that the optimized ARC through minimizing the effective-average reflectance is convenient and available.
文摘利用电池储能系统平滑风电功率波动可以提高风力发电站功率输出的稳定性。针对风电出力的随机性特别是骤变情况,提出一种基于加权移动平均滤波算法的储能系统平滑控制策略。该方法根据风电功率的波动程度与当前储能系统的荷电状态(state of charge,SOC),通过实时调整权重系数和滤波带宽有效平滑风电功率的骤变。为了维持SOC在合理水平,在综合考虑各种约束条件后,该文采用模糊控制法设计了能够根据实时情况自动调节储能电池SOC的控制策略。算例结果表明,该文提出的控制策略在维持SOC合理水平前提下能有效平滑功率波动;同时,该文方法基于的在线信息使其具有实时应用前景。
文摘主元分析(principal component analysis,PCA)是一种有效的数据分析方法,在故障诊断与状态监测方面已得到广泛应用.多元指数加权移动平均–主元分析(multivariate exponentially weighted moving average principal component analysis,MEWMA–PCA)方法用于解决PCA不能有效检出微小故障的问题.本文深入研究了MEWMA–PCA中EWMA影响主元分析进行故障检测的机制,导出了MEWMA–PCA可检出微小故障的原因.本文确定了MEWMA–PCA中遗忘因子λ、单传感器故障幅值和迟延时间三者的关系,并进行了数值仿真和火电厂磨煤机组运行状态的仿真实验.实验结果验证了MEWMA–PCA中EWMA提高PCA的监测性能的机制,并给出了根据系统实际要求来选取合适的遗忘因子值,从而在规定的时间内检出微小故障的实例.