Smoothing power fluctuation from variable renewable energy (VRE) sources is one of the critical issues to increase their interconnection capacity to the power grids. Especially, in relatively small balancing areas, such as small islands and remote districts with a small tie-line capacity, the frequency control becomes difficult, and grid operators require countermeasures for VRE sources to reduce their power fluctuation amplitude. In this paper, we deal with a photovoltaic system with a battery energy storage and a camera to meet a grid code limiting its maximum power fluctuation. We propose a battery smoothing control using short-term forecast of photovoltaic system (PV) power output by deep learning techniques with historical PV power output data and total sky images taken by the camera. A numerical simulation is conducted for an actual system to verify that the proposed method contributes to the reduction of the battery capacity necessary for meeting the grid code.
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