The aim of this paper is to address the current situation where business units in smart grid (SG) environments are decentralized and independent, and there is a conflict between the need for data privacy protection and network security monitoring. To address this issue, we propose a distributed intrusion detection method based on convolutional neural networks–gated recurrent units–federated learning (CNN–GRU–FL). We designed an intrusion detection model and a local training process based on convolutional neural networks–gated recurrent units (CNN–GRU) and enhanced the feature description ability by introducing an attention mechanism. We also propose a new parameter aggregation mechanism to improve the model quality when dealing with differences in data quality and volume. Additionally, a trust-based node selection mechanism was designed to improve the convergence ability of federated learning (FL). Through experiments, it was demonstrated that the proposed method can effectively build a global intrusion detection model among multiple independent entities, and the training accuracy rate, recall rate, and F1 value of CNN–GRU–FL reached 78.79%, 64.15%, and 76.90%, respectively. The improved mechanism improves the performance and efficiency of parameter aggregation when there are differences in data quality.
To improve power system stability in this paper, a method for optimal coordinate control of power system stabilizers (PSSs) and static synchronous compensator (STATCOM) is presented. The optimal coordinated control of multiple PSSs and STATCOM is transformed into an optimization problem in which both rotor angle speed deviation between generators and load voltages deviation after fault are involved. The optimal control parameters of PSS and STATCOM controllers are obtained by employing a paired-bacteria optimizer (PBO) based algorithm. The proposed method is tested on the Western System Coordinating Council (WSCC) 3-generator 9-bus power system. To verify the effectiveness of the proposed method, PSSs and STATCOM optimized in coordinated manner are compared with PSSs optimized independently and no damping controllers. The simulation results have shown that the coordinated PSS and STATCOM controllers optimized by PBO perform efficiently in damping low-frequency oscillations and improving the load bus voltage stability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.