System Optimization Scheduling Considering the Full Process of Electrolytic Aluminum Production and the Integration of Thermal Power and Energy Storage

To address the curtailment phenomenon caused by the high penetration of renewable energy in the system, an optimization scheduling strategy is proposed, considering the full process of electrolytic aluminum production and the integration of thermal power and energy storage. Firstly, to explore the differentiated response capabilities of various devices such as high-energy-consuming electrolytic aluminum units, thermal power units, and energy storage devices to effectively address uncertain variables in the power system, a Variational Mode Decomposition method is introduced to construct differentiated response methods for its low-frequency, medium-frequency, and high-frequency components. Secondly, based on the real production regulation characteristics of the high-energy-consuming electrolytic aluminum load, and considering various influencing factors such as current, temperature, and output, a scheduling model involving electrolytic aluminum load is established. Then, the power generation characteristics in other processes of electrolytic aluminum production are fully exploited to achieve energy storage conversion, replacing the energy storage batteries that respond to high-frequency components. Finally, by combining the deep peak-shaving model of thermal power units, an optimization scheduling model is established for the joint operation of the full electrolytic aluminum production load and thermal-power-storage systems, with the goal of minimizing system operating costs. The case study results show that the proposed model can significantly enhance the system’s renewable energy absorption capacity, reduce energy storage installations, and enhance the economic efficiency of the system’s peak-shaving operation.