Elmer P. T. Cari

A new methodology for parameter estimation of synchronous generator from disturbance measurements

A new framework to estimate dynamic parameters of synchronous generator is proposed in this paper. The methodology does not require special tests but uses disturbance data collected from the system without disconnecting the generator from the grid. It requires measurements that are easily available, more precisely, the 3-phi currents and voltages, the field voltage and the mechanical rotor speed. The estimation of mechanical and electrical parameters are decoupled offering more robustness to the estimation algorithm. In order to achieve robustness with respect to the initial parameter guesses, the DAEpsilas (Differential-Algebraic Equations) which model the generator are replaced by a constrained minimization problem that overcomes singular problems of the algebraic equations. Finally, the rotor angle is not measured but calculated as a byproduct of the proposed methodology.

A methodology for parameter estimation of synchronous generators based on trajectory sensitivity and synchronization technique

In this paper, a new approach combining synchronization techniques and trajectory sensitivity analysis is proposed to estimate the parameters of electrical synchronous generator models. The main contribution of this combination is the improvement on the numerical robustness of the estimation algorithm. The synchronization technique consists of coupling the real system with the mathematical model. The coupling is of unilateral type, that is, some outputs of the real system are considered inputs of the mathematical model. With a convenient choice of coupling, parameters that would have difficulties to be estimated by the traditional approach (due in general to very low sensitivity) can be more easily estimated. The proposed methodology is appropriate for on-line applications and does not require special operating conditions. Indeed, it can naturally deal with generator model nonlinearities. The methodology was successfully applied to estimate the parameters of a two-axis synchronous generator model. Synchronization improved the numerical robustness of the estimation algorithm allowing the simultaneous estimation of the d and q axis parameters even for bad initial guesses of parameters

A novel methodology for power angle estimation of synchronous generator based on trajectory sensitivity analysis

This paper proposes a new indirect approach to estimate the power angle of synchronous generators from three-phase currents and voltages, and field voltage measurements. An auxiliary algebraic equation, which relates the power angle with generator parameters and measurements, is included in the generator model. Therefore, the generator is modeled by a set of differential-algebraic equations (DAEs). The procedure is split into two steps. In the first step, uncertain parameters and the power angle are estimated simultaneously using an estimation methodology based on trajectory sensitivity analysis. In the second step, the load angle is estimated directly from the DAEs of the generator model by an implicit integration method. The power angle was correctly estimated even with noise in all the measurements and uncertainties in all the generator parameters.

A methodology for the estimation of synchronous generator and excitation system parameters

In this paper, a methodology to estimate parameters of synchronous generator and its excitation system, based on the trajectory sensitivity technique, is proposed. Some alternatives are proposed for this technique regarding a future on-line application. The parameters of classical and two-axis models of generator are estimated. An alternative is also proposed to overcome problems related to differential equations with variables that can not be measurable in the real system. The methodology developed is also used to estimate the parameters of the excitation system (STR1 and DC1 type) in a successful way.

A methodology for parameter estimation of equivalent wind power plant

A methodology for parameter estimation of equivalent wind power plant is proposed in this paper. The parameter algorithm is formulated as an optimization problem which miminize the output between the real system and the mathematical model. The parameters are updated using Newton-Raphson method which depends on the information of trajectory sensitivity functions. A generic equivalent of wind power plant was used as a structure of the model, which is valid for Double-Fed Induction Generator (DFIG) and full Converter Based Wind Turbine. In addition, the procedure to obtain of the trajectory sensitivity functions of the model is presented in this paper. A discussion of the estimated results is also analysed. In general, the convergence happened in a few seconds for most of the cases studied.

Online parameter estimation of synchronous generators from accessible measurements

This paper describes an approach for the estimation of parameters of a synchronous generator with measurements easily acquired. The generator two-axis model has been rewritten to include field current as an input. The model consists of a set of differential-algebraic equations (DAEs) containing an algebraic equation for the balance of currents. The measured data used are three-phase terminal voltages and currents and field current, which are easily obtained in real applications. Furthermore, to avoid singularities during the solution of the model equation, a special approach based on trajectory sensitivity method is performed due to uncertainties in the parameter. The algorithm was tested with simulation data and provided satisfactory results.

Trajectory sensitivity and genetic algorithm based-method for load identification

Load identification is an important issue in power system representations to ensure that simulations will reproduce the dynamic response of a system during a disturbance. For a load model to be accurate, its parameter must be appropriately estimated by a parameter fitness algorithm. The success of the estimation depends mainly on the availability of a good initial parameter guess. If it is not available, the estimation process takes plenty of time to converge or to diverge. This paper proposes a hybrid algorithm based on trajectory sensitivity and generic algorithm. The advantages of the fitness algorithms of Trajectory Sensitivity and Generic Algorithm are combined so as to provide a robust algorithm regarding the initial parameter guess that guarantees the convergence even in the case of unavailability of a good initial parameter set. The combined algorithm was tested in one hundred simulations, in which the initial parameter guesses were randomly generated between limits (parameter uncertainties) for the assessment of the robustness of the algorithm. The results show that in 99 cases, the proposed methodology converged to the true values in a short time.

Metodologia prática para estimação de parâmetros de geradores síncronos a partir de medidas de perturbações

A new practical and robust methodology to estimate parameters of synchronous generators is proposed in this paper. The proposed methodology is based on trajectory sensitivity analysis combined with a new approach termed minimization approach to estimate parameters of nonlinear dynamical systems modeled by a set of differential-algebraic equations. A suitable choice of inputs and outputs allows the division of the estimation of generator parameters into the independent estimation of mechanical and electrical parameters. The methodology is robust with respect to initial parameter guesses and it does not require special tests, but uses disturbance data (3-ϕ currents and voltages, field voltage and mechanical rotor speed measurements) collected from the electric power system without disconnecting the generator from the grid.

Trajectory Sensitivity Method and Master-Slave Synchronization to Estimate Parameters of Nonlinear Systems

A combination of trajectory sensitivity method and master-slave synchronization was proposed nto parameter estimation of nonlinear systems. It was shown that master-slave coupling increases the robustness nof the trajectory sensitivity algorithm with respect to the initial guess of parameters. Since synchronization is nnot a guarantee that the estimation process converges to the correct parameters, a conditional test that guarantees n that the new combined methodology estimates the true values of parameters was proposed. This conditional test was nsuccessfully applied to Lorenzs and Chuas systems, and the proposed parameter estimation algorithm has shown to be very robust with respect to parameter initial guesses and measurement noise for these examples.

Assessment of model parameters to identify an equivalent wind power plant

An assessment of parameter observability to identify an equivalent wind power plant model is proposed in this paper. The trajectory sensitivity method is used as an updating rule to iteratively improve the estimation of the model parameters. The difficulties for obtaining the correct estimation are analyzed and a strategy to overcome those problems are highlighted. In general those problems are related to parameter divergence during the estimation process, specially when the initial parameter guesses are far away from the true values and when the sensitivities of the parameters with relation to the model output are low. Those problems become more evident as the number of parameter to be simultaneously estimated increases. The proposed strategy splits the estimation procedure into different stages of different window time, facilitating the estimation of parameters. The robustness of the proposed method with relation to initial parameter guesses is verified by estimating parameters in different scenarios and with the addition of noise in the measurements.