Assessment of the Power Supply Potential of Microgrids Considering Uncertain Energy Output

To address the impact of uncertainty in clean energy output on the power supply potential of microgrids connected to large-scale clean energy, a method for evaluating the power supply potential of microgrids considering uncertain energy output is proposed. Firstly, a long and short term memory neural network is used to predict the wind power and photovoltaic output within the microgrid, and empirical modal decomposition and principal component analysis are used to reduce the data dimensionality of the neural network and improve the prediction accuracy.Based on the prediction results of the uncontrollable energy output, the risky standby power of the microgrid at different confidence levels is calculated based on the internal energy storage and load power consumption of the microgrid, and the external power supply potential of the microgrid at different confidence levels is derived. A microgrid system is selected for simulation to validate the proposed method. The results show that the proposed method can accurately assess the supply potential of the microgrid at different confidence levels.