Accounting for and optimizing efficient consumption of large-scale new energy sources on the grid with multitimescale uncertainties

Conventional new energy grid-connection and consumption methods are mainly based on global optimization, which do not take into account the uncertainty characteristics under different load levels, thus affecting the grid-connection and consumption effects. Therefore, an efficient optimization method for large-scale new energy grid integration taking into account the uncertainties of multiple time scales is designed. The dynamic voltage fluctuation characteristics of large-scale new energy grid connection are extracted, and the operating conditions such as grid strength and transient voltage offset overrun are analyzed to determine the factors affecting the efficient consumption of grid connection. Based on the multi-timescale uncertainty, a new energy grid-connected consumption optimization model is constructed, with the maximum capacity of new energy consumption as the objective function and the safe and stable operation of the grid as the constraint to ensure the efficient consumption of large-scale new energy grid-connected. The maximum capacity of new energy consumption is taken as the objective function, and the safe and stable operation of the grid is taken as the constraint condition to ensure the efficient consumption of large-scale new energy grid-connected. Taking the new energy output, the power load, and the residual capacity of the energy storage into consideration, the model optimizes the storage capacity of the new energy grid-connected to meet the economic demand of new energy grid-connected. Using simulation experiments, it is verified that the optimization effect of this method is better and can be applied in real life.