With the establishment of dual carbon goals, a new connotation is attributed to energy consumption control, demanding further clarification. In the process of picking operations, energy consumption is closely related to picking paths and the distribution of goods. Therefore, achieving efficient and rational allocation of storage locations, optimization of picking paths, and minimizing total energy consumption have become focal points for enterprises. Addressing these challenges, this paper, based on MATLAB programming, comprehensively considers factors including storage location coordinates, cargo weight, frequency of inbound and outbound operations, warehouse physical constraints, and practical constraints of picking tools. It constructs a location table and establishes an optimization model involving multiple types of goods and orders, considering energy consumption, within the context of real logistics warehouse picking operations. Utilizing the simulated annealing algorithm, we achieve the optimal picking paths for both conventional S-type picking and S-M-type picking, as well as optimize energy consumption through ABC classification of goods distribution.