The large-scale integration of wind power into grid makes it difficult to sustain the peak regulation resources of the existing system

and the wind power consumption is hindered. Therefore

considering the uncertainty of wind power output and electricity price

it proposes a distribution robust optimization method for deep peak regulation of electrolytic aluminum load cooperating with thermal power and energy storage system based on Wasserstein distance. Firstly

combined with the load characteristics of electrolytic aluminum

considering the optimization of deep peak regulation capacity of the energy storage auxiliary thermal power units

an electric power system optimization framework for deep peak shaving of the electrolytic aluminum load and thermal power-energy storage system is established. Secondly

drawing on the idea of the robust model of Wasserstein distance distribution

the Wasserstein fuzzy set constraint of the purchase and sale price of the upper power grid and the output of renewable energy is constructed

and the distribution robust optimization model for deep peak regulation of the electrolytic aluminum load and thermal power-energy storage system is designed.Finally

simulation is performed to verify that the proposed method can effectively improve the peak regulation pressure

reduce the operating cost of the system

and promote the consumption of wind power. The economics and robustness of the method are verified by comparative analysis.