Design technology for virtual circuit automatic generation in intelligent substations based on substation configuration description - Jiesheng, Chen; Feng, Wang; Weibiao, Xiong; Yinhua, Li; Pengyuan, Chen; Jianfeng, Liu (Electric power systems research, 2025)
•Optimization model and algorithm improvement This article proposes an improved simulated annealing algorithm for optimizing the distance weight vector in virtual terminal automatic connection. By constructing an optimization model and obtaining the weight vector that best matches the matching characteristics of intelligent electronic devices (IEDs), the accuracy and applicability of virtual terminal connections have been significantly improved.•Combining k-NN algorithm to achieve efficient matching By combining the optimized distance weight vector with the k-nearest neighbor (k-NN) algorithm and utilizing existing virtual connection data of similar IEDs, high-precision virtual terminal matching has been achieved. This method effectively improves the matching efficiency and applicability of the system, adapting to different manufacturers and models of IED devices.•Experimental verification and actual results Taking the 220 kV main transformer protection device and its related IED equipment as an example, the actual effect of this method was verified. The experimental results show that this method significantly improves the accuracy, compatibility, and efficiency of virtual terminal automatic matching, and is suitable for complex and diverse intelligent substation scenarios.•Future research directions Future work will focus on standardization processes, while introducing intelligent algorithms such as deep learning and adaptive learning to further achieve high-precision matching across devices and manufacturers. In addition, research is being conducted on real-time dynamic adaptation and self-correction functions to meet the connection requirements under different operating scenarios and complex faults, and to improve the efficiency and intelligence level of virtual terminal management in intelligent substations. The intelligent substation project has a high workload, high error rate, and low efficiency in SCD virtual terminal connection. A technique for automatically generating virtual circuits has been proposed to improve the efficiency of SCD virtual terminal connections. Using the virtual circuit design template, this article first uses the K-nearest neighbor learning method to automatically match virtual terminals. On the basis of training data, a weight vector optimization model will be constructed, with weight vectors as optimization parameters and appropriate objective functions set. By using an improved simulated annealing algorithm to solve the weight optimization model, the optimal solution of the distance weight vector is obtained. The verification through examples shows that compared to existing technologies, this method obtains more accurate virtual terminal connection results and higher matching efficiency.