A new optimized extreme learning machine-(ELM-) based method for power system transient stability prediction (TSP) using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO) algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.
AC contactor state evaluation is a challenging problem. This paper proposes an AC contactor state assessment method based on variable weight coefficient. Firstly, the characteristic indicators that have a great influence on the state of the AC contactor are selected, and the state evaluation index system is established. Secondly, using the subjective and objective combination weighting method combined with the analytic hierarchy process and the grey relational analysis method, the constant weight coefficient is obtained, and the variable weight coefficient method with the equalization function is introduced to obtain the variable weight coefficient of each characteristic parameter. Finally, the fuzzy comprehensive evaluation method is used to evaluate the running state of the AC contactor. The experimental results show that the state evaluation method proposed in this paper can accurately reflect the real state of the AC contactor operation and effectively improve the reliability of the power system.
The virtual synchronous generator (VSG) technique is used to simulate the external characteristics of a synchronous generator (SG) to provide certain damping and inertia to power systems. However, it may easily cause low-frequency oscillation of the power system. We studied the small-signal stability of a grid-connected virtual synchronous generator. Firstly, the small-signal models of single-VSG and multi-VSG grid-connected systems were established. Subsequently, the system eigenvalues were obtained by solving the state matrix, and the system oscillation modes were analyzed. The eigenvalue analysis method was used to analyze the impacts of parameter changes, such as virtual moment of inertia, virtual damping coefficient, line resistance, and line inductance, on system stability. Finally, our conclusions were verified by numerous simulation models.
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