Energy management strategy for a renewable-based residential microgrid with generation and demand forecasting

This paper proposes an energy management strategy for a residential microgrid comprising photovoltaic (PV) panels and a small wind turbine. The microgrid is connected to the main grid, allowing for a controlled power exchange through a battery system and its control strategy. As input data, the proposed control strategy uses the battery state of charge (SOC), the power at each microgrid node as well as the load and renewable generation forecasts. By using forecasted data and correcting any forecasting errors according to the SOC of the battery, the strategy manages to make a better use of the battery resulting in a better grid power profile. The simulation of the system using a one-year data period shows that the proposed energy management strategy results in a better grid power profile for a given storage system when compared with other state-of-the-art strategies. Finally, the proposed strategy was experimentally validated in the microgrid built in the Renewable Energy Laboratory at the UPNa.