Least squares based estimation of synchronous generator states and parameters with phasor measurement units

Wehbe, Yasser; Fan, Lingling; Miao, Zhixin

doi:10.1109/naps.2012.6336346

Cited by 28 publications

(21 citation statements)

References 11 publications

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“…Rojas-Dueñas, J.-R. Riba, Member, IEEE and M. Moreno-Eguilaz S systems involving different SMPCs, design engineers often do not to know most of the parameters in advance [20]. A feasible possibility for parameter identification is to acquire the instantaneous values of the input and output currents and voltages [21] at the input/output terminals of the power converter. This approach is appealing since it is compatible with a non-invasive on-line monitoring of the input/output signals, so there is no need to disconnect or remove the converter from its location when already installed.…”

Section: Non-linear Least Squares Optimization For Parametric Identifmentioning

confidence: 99%

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Rojas-Dueñas

Riba

Moreno-Eguilaz

2021

IEEE Trans. Power Electron.

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Switching mode power converters are being extensively applied in different power conversion systems. Parameter identification comprises a set of techniques focused on extracting the relevant parameters of the converters in order to generate accurate discrete simulation models or to design enhanced condition diagnosis schemes. This paper applies a noninvasive optimization approach based on the non-linear least squares algorithm to determine the model parameters of different commercially available DC-DC power converters (buck, boost and buck-boost) from experimental data, including the parameters related to passive, parasitic and control loop elements. The proposed approach is based on a non-invasive on-line acquisition of the input/output voltages and currents under both steady state and transient conditions. The proposed method can also be applied to many other applications requiring precise and efficient parameter identification, including rectifiers, filters, or power supplies among others.

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Section: Non-linear Least Squares Optimization For Parametric Identifmentioning

confidence: 99%

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Rojas-Dueñas

Riba

Moreno-Eguilaz

2021

IEEE Trans. Power Electron.

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“…Figure 2 shows that the transient response changes in every iteration, but the voltage ripple is almost not affected. The most suitable values of R C2 and C 2 are those minimizing the error between simulated and experimental results, which is calculated as in (15).…”

Section: Buck Converter Parameter Identificationmentioning

confidence: 99%

“…Parameter identification has been applied to identify parameters of electrical machines and circuits operating under dynamic conditions by analyzing electrical signals such as current and voltage [15]. Parameter identification can be performed online or offline, either in the time or frequency domains.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of DC-DC Converters under Steady-State and Transient Conditions Based on White-Box Models

et al. 2018

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This paper proposes a white-box approach for identifying the parameters of DC-DC buck and boost switch mode power converters. It is based on discretizing the differential equations that describe the dynamic behavior of the converters. From the discretized equations and experimental data, the parameters of the converters are identified, thus obtaining both the values of the passive components and the transfer function coefficients of the controller. To this end, steady state and transient experimental signals are analyzed, including the input and output voltages and the inductor and output currents. To determine the accuracy of the proposed method, once the parameters are identified, a simulation with the identified parameters of the converter is run and compared with experimental signals. Such results show the accuracy and feasibility of the approach proposed in this work, which can be extended to other converters and electrical and electronic devices.

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“…Parameter identification and estimation under dynamic conditions have been effectively applied to identify circuit and machine parameters based on the measurement of electrical magnitudes such as instantaneous voltages and currents, even from real-time operating data [7]. However, it is known that model parameters can depend on the operating conditions.…”

Section: Black-box Modelmentioning

confidence: 99%

“…It is noted that from (1), (7) and (11) the values of the parameters Rc, C, L and RL are calculated at every time step Ti.…”

Section: A Open Loop Parameter Estimationmentioning

confidence: 99%

DC-DC Buck Converter Parameter Identification Based on a White-Box Approach

Balakrishnan

Moreno-Ezuilaz

Riba

et al. 2018

2018 IEEE 18th International Power Electronics and Motion Control Conference (PEMC)

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This paper proposes to use a white-box approach to identify the parameters of an electronic DC-DC buck converter. It discretizes the differential equations governing the dynamic of such system, which are used to identify the parameters of the electronic components of the converter and the control loop. The proposed method is used to calculate the system parameters from the open loop and closed loop outputs, that is, the steady state and transient state stages of the output signals. The approach is validated by comparing simulation results from PSIM models of the converter with experimental data obtained from a commercial non-synchronous buck converter. Both simulation and experimental results show the feasibility and accuracy of the proposed approach in identifying the parameters of the converter, thus being feasible to obtain a full representation of such power converter. I.

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Least squares based estimation of synchronous generator states and parameters with phasor measurement units

Cited by 28 publications

References 11 publications

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Parameter Identification of DC-DC Converters under Steady-State and Transient Conditions Based on White-Box Models

DC-DC Buck Converter Parameter Identification Based on a White-Box Approach

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