Critical Loading Characterization for MTDC Converters Using Trajectory Sensitivity Analysis

Moawwad, Ahmed; El-Saadany, Ehab F.; Moursi, Mohamed Shawky El; Albadi, Mohammed

doi:10.1109/tpwrd.2018.2809565

Cited by 10 publications

(5 citation statements)

References 22 publications

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“…The dynamical evolution of a generic electr(on)ic circuit or system in the time domain can be typically modeled by a set of non-linear DAEs [39], [40]. In principle, if these DAEs are of index-1 [41], a state-space form with a minimal set of variables leading to a system of ordinary differential equations (ODEs) can be identified.…”

Section: Periodic Small-signal Analysismentioning

confidence: 99%

See 1 more Smart Citation

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Giudice

Brambilla

Linaro

et al. 2022

IEEE Trans. Circuits Syst. I

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Instability and oscillation issues originating in highvoltage direct current (HVDC) systems comprising modular multilevel converters (MMCs) are gaining increasing interest in the research community. To detect such phenomena in advance, considerable effort has been devoted recently to developing MMC models for small-signal analysis. The derivation of such models is a challenging task due to the topology and complex control structure of MMCs, which results in them having a multi-frequency response. To address this issue, scholars developed methods based on dynamic phasors and harmonic state-space modelling, which, however, require extensive pen-and-paper computations. In this paper, the periodic small-signal analysis (PAC) is adopted to determine numerically several MMCs transfer functions. Such functions can be computed between any electrical circuit node or input/output port, without the need to recast the three-phase average MMC model to derive a linear equivalent one, possibly in the DQ-frame. We show how vector fitting allows converting these functions to equivalent algebraic representations, which can be profitably used to design MMCs and study their stability following some parameter changes. To showcase this feature, we exploit one of these transfer functions to detect DC-side instability in a point-to-point HVDC system.

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Section: Periodic Small-signal Analysismentioning

confidence: 99%

“…In this paper, we resort to the shooting method (SHM), which is formulated in the time-domain [43] 1 . For space reasons, we do not recall SHM (which was recently used also in [40]) but we provide in Appendix A some specific hints about the small-signal time-domain solution, which is a key aspect of PAC.…”

Section: Periodic Small-signal Analysismentioning

confidence: 99%

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Giudice

Brambilla

Linaro

et al. 2022

IEEE Trans. Circuits Syst. I

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“…The WMLS Algorithm Different to the OMLS that treats all data samples with equal weights, to distinguish the different importance of different data samples, the WMLS is developed by minimizing the weighted quadratic sum of elements in e as follows: (8) where jk w is the element of the weighting matrix W with the coordinate of (j,k).…”

Section: A the Omls Algorithmmentioning

confidence: 99%

“…Power system sensitivity, which is defined as the coefficients in the linear function of multiple system state variables with respect to multiple control variables, is widely applied for power system operation and control [1][2][3][4][5][6][7][8]. Specially, voltage sensitivity is used for reactive power planning and voltage stability control [1][2], power loss sensitivity is for economic operations [3], eigenvalue sensitivity is for small signal stability analysis [4][5], and various kinds of sensitivities are widely employed for control design and system security assessment [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Power System Sensitivity Matrix Estimation by Multivariable Least Squares Considering Mitigating Data Saturation

Liang¹,

Zhang²,

Srinivasan³

2020

Preprint

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<div>To data-driven estimate power system sensitivity matrix considering mitigating data saturation, a series of multivariable least squares (MLS) algorithms are proposed and compared, including the ordinary MLS (OMLS), the weighted MLS (WMLS), the memory-limited OMLS (ML-ORMLS), the memory-limited WRMLS (ML-WRMLS), and the memoryfading ML-WRMLS (MF-ML-WRMLS). Considering enhancing computational efficiency and accuracy by mitigating data saturation, the last three of them are specifically derived for sensitivity matrix estimation based on time-varying online-measured data. The effectiveness of the presented algorithms is verified and compared in the Nordic 32 system for voltage sensitivity matrix estimation. The results illustrate the prime algorithm in practice.</div>

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“…Therefore, the map is often attained by the numerical approach. Alternatively, other analysis methods such as trajectory sensitivity approach, 17,18 Lyapunov-based methods, 19 describing function method 20 and Filippov theory 21,22 have been utilized for the stability analysis of power converters. Note that these methods can also be employed to help the design of the nonlinear control schemes for the power converters.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear analysis of interleaved boost converter with a novel valley V ² control

Sun

Qiu

Liu

et al. 2021

Int Trans Electr Energ Syst

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In this paper, a novel valley V 2 control scheme for interleaved boost converter is presented to improve the transient response performance of system and realize the current sensorless control, and its stability is analyzed by a nonlinear analysis technique. In this proposed methodology, the current sensor is saved by the proposed control signals sharing algorithm, and the nonlinear dynamics is investigated by employing a nonlinear analysis method based on the Monodromy matrix. Meanwhile, the information of the converter parameters' influence on the system stability can be obtained by calculating the Monodromy matrix of switching event. It is worth mentioning that the location of eigenvalues of this matrix can be utilized to analyze the relationship between converter parameters and stability margin. Furthermore, by adopting the knowledge gained from this analysis, an auto-tuning resonant parametric perturbation is proposed to ensure an excellent performance of converter with an extended range of stable operation. Finally, the simulation and experimental results are presented to verify the effectiveness and theoretical analysis of the proposed method.

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Critical Loading Characterization for MTDC Converters Using Trajectory Sensitivity Analysis

Cited by 10 publications

References 22 publications

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Power System Sensitivity Matrix Estimation by Multivariable Least Squares Considering Mitigating Data Saturation

Nonlinear analysis of interleaved boost converter with a novel valley V ² control

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Critical Loading Characterization for MTDC Converters Using Trajectory Sensitivity Analysis

Cited by 10 publications

References 22 publications

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Power System Sensitivity Matrix Estimation by Multivariable Least Squares Considering Mitigating Data Saturation

Nonlinear analysis of interleaved boost converter with a novel valley V 2 control

Contact Info

Product

Resources

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Nonlinear analysis of interleaved boost converter with a novel valley V ² control