Xiaoping Tu

Modeling and Real-Time Simulation of Internal Faults in Synchronous Generators With Parallel-Connected Windings

In large synchronous generators, the stator windings are usually parallel-connected in order to increase the machine current capacity. In analysis and modeling, the parallel windings are usually lumped into one equivalent stator winding since equal currents flow in these windings. However, when an internal fault occurs in the windings, the symmetry between the parallel windings is broken and different currents will flow in the parallel windings since unsymmetrical magnetic linkage may exist between the stator windings. The aim of this paper is to present a simulation model to investigate the internal fault currents of large synchronous generators with parallel-connected windings. This model is based on a modified winding function theory that takes into account all space harmonics. Moreover, the calculation of the machine inductances is made easier by the use of the machine electrical parameters instead of the geometrical ones. The simulation results illustrate the existence of different currents in parallel windings in the case of internal faults. Results are given for an implementation of the internal fault model in a real-time simulator of large power networks

A New Model of Synchronous Machine Internal Faults Based on Winding Distribution

A synchronous machine internal faults model based on the actual winding arrangement is described in this paper. Based on the winding function approach, the machine inductances are calculated directly from the machine winding distribution, thereby the space harmonics produced by the machine windings are readily taken into account. Moreover, the calculation of the machine inductances is made easier by the use of the machine electrical parameters instead of the geometrical ones. Simulation results for internal faults on a laboratory generator are compared with experimental results to verify the accuracy of the proposed model

Transient Modeling of Squirrel-Cage Induction Machine Considering Air-Gap Flux Saturation Harmonics

A transient model of a squirrel-cage induction machine, including air-gap flux saturation harmonics, is presented in this paper. The machine model is based on a flux model, where the winding magnetizing fluxes are directly calculated from the resultant air-gap magnetomotive force, avoiding the use of complicated inductance harmonics. The effects of the fundamental and third harmonic components of the air-gap flux are incorporated in the model by two saturation factors. Moreover, the saturation effects are incorporated in the machines torque equation, allowing the model to investigate the machines performance under any load condition. The machine parameters, including saturation data, are obtained via the conventional no-load and locked-rotor tests, with access to the stator neutral connection. The proposed model is validated by experimental results for a squirrel-cage machine and can be used to predict machine transient states.

Modeling and experimental validation of internal faults in salient pole synchronous machines including space harmonics

Considering the space harmonics caused by the faulted windings, a simulation model of internal faults in salient pole synchronous machines is proposed in this paper. The model is based on the winding function approach, which makes no assumption for sinusoidal symmetrical distribution of the machine windings. A new method of calculation of synchronous machine inductances is presented, in which the space harmonics produced by the windings are readily taken into account. Simulation results for internal faults on the stator windings of a generator at no load and at load are compared with experimental results to verify the accuracy of the proposed model.

A global approach to transient stability constrained optimal power flow using a machine detailed model

Transient stability constrained optimal power flow (TSC-OPF) is originally a nonlinear optimization problem with variables and constraints in time domain, which is not easy to deal with because of its huge dimension, especially for systems with detailed machine models. This paper presents an efficient approach to realize TSC-OPF by introducing an independent dynamics simulation algorithm into the optimization procedure. In the new approach, the simulation algorithm is used to realize the dynamic constraints and to deduce the transient stability constraint, while the optimization algorithm verifies the steady state and the transient stability constraints together. The new TSC-OPF has just one more constraint than that of a conventional OPF and can be solved by a conventional OPF algorithm with small modification. In the new approach, there is no limitation for the machine model and the simulation method. The nonlinearity of the power system is taken fully into account. In the paper, the proposed approach is verified with a small three-machines system. The simulation results show the machine model influences greatly the system transient stability and the TSC-OPF results. The widely used machine classical model in the TSC-OPF over-estimates the system transient stability and under-estimates the TSC-OPF costs.

Transient model of induction machine using rotating magnetic field approach

Most simulation models of electric machines use the coupled circuit approach, where the machine is considered as an electric circuit element with time-varying inductances (abc model) or with constant inductances (dq0 model). On the other hand, the rotating magnetic field approach, which considers the electric machine as two groups of windings producing rotating magnetic fields and can give insight into internal phenomena of the machines, has not yet received much attention in electric machines modeling, especially for machine transient analysis. Based on the rotating magnetic field approach, this paper presents a transient model of the induction machine including main flux saturation effect. Based on the direct computation of the magnetizing fluxes of all machine windings, the model represents instantaneous main flux saturation by simply introducing a main flux saturation factor. No iteration process is involved to incorporate the saturation effects. The model combines the advantages of the dq0 and abc models advantages, such as rapid computation time and nonsymmetrical conditions simulation, respectively. The simulation results and the experimental tests show advantages and verification of the model.

Multi-contingency transient stability-constrained optimal power flow using multilayer feedforward neural networks

Transient stability-constrained optimal power flow (TSC-OPF) aims at optimising the scheduling of generation with stability constraints to ensure a secure system in the event of contingencies. This paper proposes a new approach based on a critical clearing time (CCT) constraint that replaces the dynamic and transient stability constraints of the TSC-OPF problem. The CCT is computed by a multilayer feedforward neural network (MFNN) trained using Gauss-Newton approximation for Bayesian regularization. In order to ensure a uniform distribution of generated points in the input space to train the neural networks, a Sobol quasi-random sequence is adopted for data generation. The proposed method has the merit of removing the computational burden of dynamic simulation during optimisation. Multi-contingency can simply be handled by adding a CCT constraint for each contingency. Simulation results for the New England 10-machine 39-bus system show that TSC-OPF using MFNN has very fast convergence to optimal operating points with the desired CCT.

Independent component analysis for feature reduction in critical clearing time estimation

Critical clearing time (CCT) is an important parameter used in transient stability assessment of power systems. In this paper, only pre-fault generator voltage magnitudes and active powers are used as inputs to a multilayer feedforward neural network (MFNN) trained using Gauss-Newton approximation for Bayesian regularization to estimate the CCT in an optimal power flow framework. Principal component analysis (PCA) and independent component analysis (ICA) are utilized to reduce the dimension of these features. Simulations performed on the New England 10-machine 39-bus system show that ICA outperforms PCA and gives a smooth degradation of MFNN performance as the number of input features are reduced.

Power system losses minimization with transient stability constraints

This paper presents a study of Optimal Power Flow calculation, coupled with additional transient stability constraints (TSC-OPF). Besides, with some modifications to the formulation of the transient stability constraint, a better convergence property can be achieved. The framework is applied to the cases of two standard test power systems, with the objective of minimizing total active power loss. It is shown that the current TSC-OPF framework can be used for loss minimization TSC-OPF.

Non-linear Optimization Approach to Determine Parameters of Small Salient-pole Synchronous Machines from the Short-circuit Test

Abstract The sudden three-phase short-circuit test is commonly used to derive synchronous machine parameters and has been standardized by the IEEE/IEC. However, because they ignore the quadrature axis and use an envelope-tracing technique, the standard methods are inconvenient in determining the parameters of small salient-pole synchronous machines, which have strong second harmonic short-circuit current and short time constants. This article presents an alternative procedure to determine equivalent circuit parameters of small salient-pole synchronous machines from the conventional short-circuit test. The machine steady-state parameters are determined by the standard methods, while the other parameters are estimated from the machine transient short-circuit currents using a non-linear optimization approach. The parameters of the direct- and quadrature-axes are both obtained with a single test. A new state-space linear model and a transient saturation model of synchronous machines in phase quantities are developed to predict the short-circuit test. The method is successfully applied for the parameter estimation of a synchronous motor/generator of 208 V, 1.5 kVA, and 60 Hz. The estimated parameters are validated under load as well as saturation conditions.