Optimal configuration of multi-microgrid energy system based on historical data

Aiming at the problems of low utilization rate of distributed energy in China, weak interaction between energy microgrids, and unreasonable equipment configuration, a multi-microgrid integrated energy scheduling optimization configuration model based on historical data is established in this paper. The mathematical modeling is carried out for the cogeneration, photovoltaic (PV) and other equipment in the micro-grid. It collects the historical annual wind and solar output data of the region, and uses the BP neural network to predict the photovoltaic output of the next year based on the historical data to ensure the reasonableness of capacity configuration of the micro-grid equipment, as well as considers the influence of photovoltaic prediction error on the accuracy of the results. Taking the installation cost, maintenance cost, etc. as the objective function to carry out the optimization analysis, it sets up the independent operation and joint operation of the micro-grid for comparative analysis. The case analysis shows that the proposed multi-microgrid integrated energy scheduling optimization configuration model based on historical data can effectively reduce the total operating cost of the micro-grid, rationalize the micro-grid equipment configuration, and improve the utilization rate of distributed energy.