Research on Power System Performance Evaluation Based on Machine Learning Technology

Abstract

Power systems often suffer from various large disturbances during operation, especially grounding and short-circuit faults of operating lines, which may lead to transient instability of the system. In view of the fact that the existing relay protection is difficult to be fully applied to the power system with high permeability distributed energy, the machine learning algorithm is applied to the relay protection of the power system. Enhance the robustness of the model to noise; In the training, more weight is given to the unstable samples to balance the influence caused by the difference in the number of samples. In addition, a regular term is introduced into the loss function to control the complexity of the model and reduce over-fitting, thus adapting to various operating conditions of the power system. By comparing the difference between measured data and estimated data to detect bad data, the machine learning method is more intelligent than the traditional method. The research results show that the transient stability evaluation method based on incremental learning of support vector machine greatly reduces the learning time while maintaining the evaluation performance, and is a promising online learning algorithm for transient stability evaluation.