Deep Learning Model on Energy Management in Grid-Connected Solar Systems

Because of increased electricity consumption and the inherent limitations fossil fuel ability to replenish themselves in future, a shift renewable energy sources is unavoidable. Although are afflicted by intermittency, this problem can be alleviated combining them with other electricity. As result above situation, secondary source will take over if primary unable match load demand. In paper, we develop hybrid that connected grids an optimal way for prediction using management system (EMS). The study aimed at handling production, grid interaction, storage system, all which must accomplished simultaneously. current state information from battery, as well control objectives, used design actions maximise amount injected into grid. During window, it assumed inputs received start window remain consistent throughout duration window. results RMSE show errors lesser than 0.3% shows improved rate accuracy EMS.