With the rise of digital twin technology, the application of digital twin technology to industrial automation provides a new direction for the digital transformation of the global smart manufacturing industry. In order to further improve production efficiency, as well as realize enterprise digital empowerment, this paper takes a welding robot arm as the research object and constructs a welding robot arm digital twin system. Using three-dimensional modeling technology and model rendering, the welding robot arm digital twin simulation environment was built. Parent–child hierarchy and particle effects were used to truly restore the movement characteristics of the robot arm and the welding effect, with the help of TCP communication and Bluetooth communication to realize data transmission between the virtual segment and the physical end. A variety of UI components were used to design the human–machine interaction interface of the digital twin system, ultimately realizing the data-driven digital twin system. Finally, according to the digital twin maturity model constructed by Prof. Tao Fei’s team, the system was scored using five dimensions and 19 evaluation factors. After testing the system, we found that the combination of digital twin technology and automation is feasible and achieves the expected results.

This paper proposes an improved state-of-charge (SOC)-based adaptive droop control strategy for photovoltaic DC microgrids with distributed energy storage units (DESUs). To overcome the slow SOC equalization and limited adaptability of conventional droop control methods, a nonlinear arctangent-based droop coefficient adjustment mechanism is introduced to enhance regulation sensitivity under small SOC deviations. In addition, a capacity compensation factor and an acceleration term are incorporated to improve proportional power sharing and SOC convergence speed among heterogeneous storage units. To further evaluate the engineering significance of SOC balancing performance, a time-integrated SOC deviation index is introduced to analyze the cumulative imbalance effect on battery degradation and lifecycle operation. By reducing the SOC imbalance duration, the proposed strategy contributes to mitigating uneven battery aging and may potentially reduce long-term battery replacement costs. Simulation results under discharging, charging, and irradiance-variation scenarios demonstrate that the proposed strategy significantly improves SOC-balancing performance compared with conventional SOC-based droop control. Across the three operating modes, the average SOC balancing time has been reduced by 52.6%. The proposed method provides an effective and economically sustainable control framework for distributed energy storage coordination in DC microgrids.