Load — Source analysis and scheduling in hybrid smart grid using multilayer adaptive GNN algorithm

TLDR: The proposed system introduces a method for optimized source additions and effective load scheduling without disturbing the stability of the system using a three-layer metaheuristics multidimensional algorithm, composed of Adaptive Hopfield network and a Genetic Algorithm to identify the optimist load scheduling.

Abstract: The solar and wind power has recently become a potential option in power systems and act significantly to meet the penetration of demands. The present growth of such renewable energy sources has shown an exponential increase in on-grid generation systems. The high penetration of such systems help a grid to effectively meet its load requirements during an irregular demand but also create some disturbances in grid due to frequent addition and detachments of loads/sources. The renewable energy sources that usually works in on-grid mod is to be attached and cut down from the grids without creating disturbances in stable grid. Another important requirement is the effective load management with less transmission losses. The proposed system introduces a method for optimized source additions and effective load scheduling without disturbing the stability of the system. It uses a three-layer metaheuristics multidimensional algorithm, composed of Adaptive Hopfield network which is used to identify the gridand a Genetic Algorithm to identify the optimist load scheduling.