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Many probabilistic maintenance models developed for maintenance scheduling and optimization are based on state diagrams. Classical maintenance models based on state diagrams provide inaccurate results when inspection rates are nonperiodic. An attempt has been made to rectify some modeling properties through the use of an alternative graph; however, it requires Monte Carlo simulation to accurately calculate reliability. This paper highlights an idealistic property of classical state diagrams and proposes new state diagrams to correct it. The accuracy of Markov models based on proposed state diagrams is verified through a theoretical discussion. Significant differences between the results given by classical and proposed maintenance models are shown through a numerical example for imperfect maintenance. The behavior of mean time between failures is also analyzed to validate the proposed models. With the proposed model, reliability analysis of different maintenance activities can be calculated analytically without the use of Monte Carlo simulation. [ABSTRACT FROM PUBLISHER]

The recently proposed power-synchronization control for grid-connected voltage-source converters (VSCs) has been shown to be a feasible solution for high-voltage direct-current (HVDC) transmission connected to high-impedance weak ac systems. In this paper, power-synchronization control is investigated for VSC-HVDC links connected to another type of weak ac system, i.e., low-inertia or island systems. As an example, a linear model of a typical island system feeding by a VSC-HVDC link, including a synchronous generator, an induction motor, and some passive loads, is developed for tuning the control parameters of the VSC-HVDC link. Time simulations in PSCAD/EMTDC demonstrate that VSC-HVDC systems using power-synchronization control are flexible for various network conditions, such as large-ac-system connection, island systems, or passive networks. The time simulations also show that power-synchronization control can seamlessly handle transitions between operation modes, as well as ride through ac-system faults in all network conditions. [ABSTRACT FROM PUBLISHER]

This paper proposes an optimized transmission line modeling (TLM) method for the real-time transient simulation of systems with multiple nonlinearities. The proposed method allows the simulation to be carried out with larger time-steps while maintaining the accuracy. A detailed case study of a nonlinear bridge circuit is presented to illustrate the advantages of the optimized TLM method in comparison with other methods. The new formulation is then implemented in real-time for the transient simulation of the nonlinear bridge. Real-time simulation results are validated by comparing them with experimental measurements. A second case study includes a power system with several surge arresters which is also simulated in real-time by the aid of the optimized TLM method and verified using offline simulation. [ABSTRACT FROM PUBLISHER]

In this paper, the power system with an excitation controller is represented as a class of large-scale, uncertain, interconnected nonlinear continuous-time system in strict-feedback form. Subsequently, dynamic surface control (DSC)-based adaptive neural network (NN) controller is designed to overcome the repeated differentiation of the control input that is observed in the conventional backstepping approach. The NNs are utilized to approximate the unknown subsystem and the interconnection dynamics. By using novel online NN weight update laws with quadratic error terms, the closed-loop signals are shown to be locally asymptotically stable via Lyapunov stability analysis, even in the presence of NN approximation errors in contrast with other NN techniques where a bounded stability is normally assured. Simulation results on the IEEE 14-bus power system with generator excitation control are provided to show the effectiveness of the approach in damping oscillations that occur after disturbances are removed. The end result is a nonlinear decentralized adaptive state-feedback excitation controller for damping power systems oscillations in the presence of uncertain interconnection terms. [ABSTRACT FROM PUBLISHER]

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V-\theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Québec TransÉnergie network. [ABSTRACT FROM PUBLISHER]