An online optimization control method for flexible DC distribution networks based on visual programming and its engineering applications

With the large-scale integration of high-throughput renewable energy into the power system, the architecture of alternating and direct current interconnection of the distribution network has become increasingly complex and critical. This paper conducts an in-depth analysis of the popular AC/DC hybrid topology according to the scenario of high penetration of renewable energy and clarifies its structural features and operating mechanism. On this basis, an innovative virtual impedance management strategy is introduced, which integrates the mechanism of influence and dynamic characteristics of several variables. An online optimization control method of a flexible DC distribution network based on visual programming is proposed. This method uses the intuitiveness and accessibility of visual programming to achieve fast and efficient online optimization and parameter configuration in network debugging and real engineering applications, greatly improving debugging efficiency and ease of operation. To verify the effectiveness of this method, an advanced hardware-in-the-loop (HIL) testing platform was built using RT-LAB. Strict experimental results show that this method realizes fast online adjustment of DC voltage parameters and active power settings, and has excellent dynamic response performance. In addition, this method is also implemented in the electrical network of Guangshui District of Hubei province. Long-term operation monitoring and data analysis show that the DC voltage fluctuation is kept below 2%, and the active power adjustment error is always controlled within 1.5% to ensure the stability of the electrical network. In addition, this method facilitates trouble-free switching operations in field applications and effectively mitigates the transitions of the electrical network. Compared with traditional methods, the visual programming-based method improves parameter tuning efficiency—measured in terms of commissioning time, trial-and-error iterations—by 40%, and the degree of voltage distortion during the conversion of the system is kept below 3%, which significantly improves the quality of power. This method provides strong technical support for the stable and efficient operation of distribution networks with high throughput of renewable energy and has theoretical significance and practical technical value. It has great potential for widespread adoption in future power grid upgrades and smart grid development.