AUTHOR=Liang Liang , Bai Xiaoyang TITLE=A Data Driven Based Ultra Short PV Forecasting Method With Sky Images JOURNAL=Frontiers in Energy Research VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.903998 DOI=10.3389/fenrg.2022.903998 ISSN=2296-598X ABSTRACT=

With increasing levels of renewable energy in power systems, the coordination of different types of dispatchable resources, such as coal-fired power plants, hydropower plants, energy storage systems, and electric vehicles, has become more important than before. To optimally dispatch these operating units, the quality of the forecasting results becomes increasingly important for the operation of power systems. In this study, an ultra-short forecasting method was proposed for photovoltaic (PV) systems. It provided a forecast of the power output for the following 5 min using sky images obtained photographically in real time. The brightness of the key area was an important factor in determining the output power of the PV system. The output power was calculated using several different features extracted from the sky images. The brightness and other key features were then processed by a bidirectional long short-term memory network. The accuracy of the proposed PV forecasting method improved the accuracy of the forecast for the total power system. A testbed system was established to capture sky images in real time and verify the effectiveness of the proposed method.