Research on the optimal allocation of new energy connected to electrolytic aluminum

In order to solve the problem of high proportion of new energy access to electrolytic aluminum, wind power generation, photovoltaic (PV) power generation and energy storage are combined to maximize the absorption of new energy in the electrolytic aluminum production process by optimizing the configuration. Using the new model of wind, solar and storage complementarity, a bi-level programming model for the high proportion of new energy access is proposed. For the propose of achieving the power required for the electrolytic aluminum production and the new energy power generation as much as possible, minimum energy storage configuration capacity is used as the upper optimization model and the maximum economic benefit is taken as the lower model. Based on the hourly power generation data of wind turbines (WT) and photovoltaics and the hourly power consumption of electrolytic aluminum process in a certain area, the nondominated sorting genetic algorithm (NSGA-II) is used to optimize the configuration of the wind turbines and photovoltaic power generation capacity. The results of research show that the optimal solution of wind-solar storage allocation capacity can maximize the local consumption of new energy on the basis of lower investment cost. At the same time, it can achieve better economy of electrolytic aluminum production, which has practical significance for the high proportion of electrolytic aluminum production and the utilization of new energy.