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This paper deals with a Dynamic, Distributed Energy Management in a Smart Micro-grid. At present, the energy management is done using a system called SCADA (Supervisory Control and Data Acquisition). This paper advocates the application of Multi Agent System for dynamic energy management. Economic and environment optimization is implemented by choosing the least cost renewable resource available at that time. The outcome of this paper is to show that MAS based control architecture can be used to optimize the energy management in a microgrid. Machine learning has been used for load forecasting and to improve the efficiency of the power grid and create a smooth operating environment.

Energy management System using Multi Agent Systems with IoT and Machine learning