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Case study of outlier event of solar irradiance forecasts from a numerical prediction model

机译:来自数值预测模型的太阳辐照度预测的异常值案例研究

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A significant number of photovoltaic (PV) power systems have been installed in Japan since the introduction of a feed-in-tariff program in 2012. PV power generations are directly affected by solar irradiance and have also large variations in spatial and time scales. For stability control of power grids with system operation in energy management systems (EMS), one day ahead forecasts of solar irradiance with numerical weather prediction model (NWP) are important. However, solar irradiance forecasts by the NWP have often yield errors. In particular, large forecast errors of PV power or solar irradiance forecasts are undesirable in the operation of EMS. In this study, we investigate, as a case study, outliers events of solar irradiance forecasts (i.e, cases when relatively large forecast errors occurred). The forecasts are based on the NWP from the Japan Meteorological Agency, and they were performed for a spatially large area (the operation area of a power utility) around Tokyo in Japan. From validation results, we found that, in some cases of one day ahead forecasts, it was difficult to forecast cold front locations with moving synoptic-scale low pressure zone. However, forecasts in early morning (06 LST initialization time in Japan) were able to detect the location of cold front and/or cloud fields associated with low pressure zones. It is seems that the improvement of solar irradiance happened due to data assimilation using latest observation data. These results indicated that updated forecast data of solar irradiance proved to be useful to comprehend large errors in one day ahead forecasts.
机译:自2012年引入送入关税计划以来,日本安装了大量的光伏(PV)电力系统。光伏电站直接受太阳辐照度的影响,并且在空间和时间尺度也具有大的变化。对于在能量管理系统(EMS)中具有系统运行的电网的稳定性控制,有一天的太阳辐照程序预测与数值天气预报模型(NWP)很重要。然而,NWP的太阳辐照度预测通常会产生错误。特别地,在EMS的操作中,PV功率或太阳辐照度预测的大型预测误差是不希望的。在这项研究中,我们调查,作为案例研究,太阳辐照度预测的异常事件(即,当发生相对较大的预测错误时)。预测基于日本气象局的NWP,在日本东京围绕东京进行空间大面积(电力效用的运营区)。从验证结果来看,我们发现,在某些情况下,在某些情况下预测,难以预测具有移动概要低压区的冷前部门。然而,清晨预测(日本的06 LST初始化时间)能够检测与低压区域相关的冷前部和/或云场的位置。似乎,由于使用最新观察数据的数据同化,因此发生了太阳辐照的改善。这些结果表明,更新的太阳辐照预测数据证明是在预测的一天内理解大错误。

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