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This paper proposes Extended Kalman Filter (EKF) based dynamic state estimator for power systems using phasor measurement unit (PMU) data. Dynamic state estimation in power systems provides synchronized wide area system history of the dynamic events which is key in the analysis and understanding of the system performance, behavior, and the types of control decisions to be made for large scale power system contingencies. In this paper, 2-axis-fourth-order state space modeling and validation of the synchronous machine is explained in detail. The model is then used for dynamic state estimation using EKF in IEEE 3-Generator-9-Bus Test System. The simulation results show that the model and estimation approach are capable to provide accurate information about the states of the machine and eliminate the noise effects on the measurement signal. The main challenges of dynamic estimation in large power systems are also addressed in this paper. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a scheme for online voltage stability monitoring for multiple contingencies using an enhanced radial basis function network (RBFN). A single RBFN is used to estimate MW margins for different contingencies. A sequential learning strategy is used along with a regularization technique to design the RBFN and the weights in the output layer are determined by using linear optimization. The proposed network can be adapted with changing operating scenario of the power system. A network pruning strategy is used to limit the growth of the network size due to adaptive training. The proposed scheme is applied on the New England 39-bus power system and the IEEE 118-bus power system. [Copyright &y& Elsevier]

Abstract: This paper proposes a scheme for online voltage stability monitoring using an enhanced Radial Basis Function Network (RBFN). A single RBFN is used to predict MW margins for different contingencies. A sequential learning strategy is used along with a regularization technique to design the RBFN and the weights in the output layer are determined by using linear optimization. The proposed network can be adapted with changing operating scenario of the power system. A network pruning strategy is used to limit the growth of the network size due to adaptive training. The proposed scheme is applied on the New England 39-bus power system model. [Copyright &y& Elsevier]

This paper presents the development of a Class-D full-bridge zero-voltage switching (ZVS) inverter, applicable to wireless power transfer (WPT) systems, operating at 13.56 MHz switching frequency with dynamic dead-time control (DDTC). Resonant-coupled WPT systems are being designed at ultrahigh switching frequencies to reduce the size of the wireless link and the passive components. Maintaining ZVS while controlling the output power delivered to a fixed or variable load is one of the major challenges of designing inverters at multi-MHz switching frequencies. DDTC is the approach deployed in this paper to sustain soft switching of a Class-D full-bridge inverter over the full range of output power while regulating the input dc bus voltage. Simulation results are presented to show that dynamically controlling the dead-time during input dc bus voltage variations reduces switch-node voltage overshoot, prevents large current spikes in the switching devices, and reduces associated high switching loss. Practical results obtained show that DDTC reduces switch-node voltage overshoot, increases the inverter efficiency, and reduces the steady-state temperature of the inverter during output power regulation. [ABSTRACT FROM AUTHOR]