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Non-availability of reliable and sustainable electric power is a majorproblem in the developing world. Renewable energy sources like solar are notvery lucrative in the current stage due to various uncertainties like weather,storage, land use among others. There also exists various other issues likemis-commitment of power, absence of intelligent fault analysis, congestion,etc. In this paper, we propose a novel deep learning-based system forpredicting faults and selecting power generators optimally so as to reducecosts and ensure higher reliability in solar power systems. The results arehighly encouraging and they suggest that the approaches proposed in this paperhave the potential to be applied successfully in the developing world.

Deep Fault Analysis and Subset Selection in Solar Power Grids