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Estimation and forecast accuracy of regional photovoltaic power generation with upscaling method using the large monitoring data in Kyushu, Japan

机译:利用九州,日本九州大型监测数据估计和预测精度。

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In order to optimize photovoltaic (PV) output curtailment control, forecasting a regional PV power generation are an important issue. Its estimation is also important as a basic step prior to forecasts. Upscaling algorithm is general approach for evaluating and forecasting a regional PV power generation because the number of monitored plants is usually limited. However, the method leads to large error when the characteristics of monitored plants differ from those of unknown plants in a region. In this paper, we analysed the errors on estimation and forecast of regional PV power generation with upscaling method by using monitoring data obtained from 2219 small PV plants in Kyushu, Japan. As the results, random sampling method has sufficient accuracy for day-ahead and short-term forecasts in case of the large number of reference plants, and unlike forecasts the minimum estimation error does not remain flat and continued to decrease as the number of power plants increased.
机译:为了优化光伏(PV)输出缩减控制,预测区域光伏发电是一个重要问题。它的估计也是预测之前的基本步骤。升级算法是用于评估和预测区域光伏发电的一般方法,因为受监控植物的数量通常是有限的。然而,当监测植物的特性与区域中的未知植物不同时,该方法导致误差。在本文中,我们通过使用日本九州的2219个小型光伏工厂获得的监测数据分析了具有升高方法的区域光伏发电的估计和预测差异。作为结果,随机采样方法在大量参考厂的情况下对日前前方和短期预测具有足够的准确性,并且与预测不同,最小估计误差不会保持平坦,并且随着发电厂的数量而继续降低增加。

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