Small Signal Stability Analysis of Multi-Infeed Power Electronic Systems Based on Grid Strength Assessment

Dong, Wei; Xin, Huanhai; Wu, Di; Huang, Linbin

doi:10.1109/tpwrs.2018.2875305

Cited by 124 publications

(115 citation statements)

References 25 publications

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“…As it is seen, the voltage and currents are given in DQ axes which is the common reference frame [45]. Equation (27) gives the relationship between the two reference frames for a sample variable F , where T is the transfer function.…”

Section: Network Equationsmentioning

confidence: 99%

A General Mathematical Model for LVRT Capability Assessment of DER-Penetrated Distribution Networks

et al. 2020

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Low voltage ride through (LVRT) is one of the indispensable issues of recent decade in the context of grid codes. LVRT stands for the ability of a generation facility to stay connected during the voltage dip. Despite the numerous discussions in recent works, but they mostly concentrate on the LVRTbased control of distributed energy resources (DERs) integrated into a microgrid and its improvement. However, what has been hidden and not addressed any more yet is an index to measure the LVRT capability of a DER-penetrated distribution network (DPDN) under different voltage sags. This takes precedence when we want to evaluate the LVRT capability of DPDNs with consideration of various LVRT categories of DERs mandated in IEEE 1547 standard. This paper introduces a general framework for LVRT assessment of a DPDN by solving a system of differential algebraic equations (DAEs). Then expected LVRT capability of a DPDN is evaluated by a proposed LVRT index through the implementation of Monte Carlo simulation technique. INDEX TERMS Differential algebraic equation (DAE), Distributed energy resource (DER), Penetrated distribution network (DPDN), Low voltage ride through (LVRT), Monte Carlo

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Section: Network Equationsmentioning

confidence: 99%

A General Mathematical Model for LVRT Capability Assessment of DER-Penetrated Distribution Networks

et al. 2020

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“…4-5. A 3-phase fault was applied to bus 4 and cleared in 0.184 s. This clearing time is almost the critical clearing time 1 and was chosen to ensure a very severe condition where there should be significant difference in the methods. Then a 3rd order NF model was built using the conventional Hessian and the proposed methods.…”

Section: Fig 3 Ieee 3-machine Systemmentioning

confidence: 99%

“…T HE emergence of new power electronic-based (PE) devices onto the power scene and the increasing number of distributed generation power systems in electrical grids contribute to changing the characteristic behaviour of the grid. This outburst seems to be the fastest growing trend in power system with proliferation of DC/AC inverters, switch mode power supplies, high-voltage DC (HVDC) links, distributed renewable energy systems and many more [1]- [3]. The consequence is a complex nonlinear behaviour and failure of conventional small-signal (modal) analysis (SSA) tools [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

A New Fast Track to Nonlinear Modal Analysis of Power System Using Normal Form

Ugwuanyi

Kestelyn

Thomas

et al. 2020

IEEE Trans. Power Syst.

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The inclusion of higher-order terms in small-signal (modal) analysis augments the information provided by linear analysis and enables better dynamic characteristic studies on the power system. This can be done by applying Normal Form theory to simplify the higher order terms. However, it requires the preliminary expansion of the nonlinear system on the normal mode basis, which is impracticable with standard methods when considering large scale systems. In this paper, we present an efficient numerical method for accelerating those computations, by avoiding the usual Taylor expansion. Our computations are based on prescribing the linear eigenvectors as unknown field in the initial nonlinear system, which leads to solving linear-only equations to obtain the coefficients of the nonlinear modal model. In this way, actual Taylor expansion and associated higher order Hessian matrices are avoided, making the computation of the nonlinear model up to third order and nonlinear modal analysis fast and achievable in a convenient computational time. The proposed method is demonstrated on a single-machine-infinitebus (SMIB) system and applied to IEEE 3-Machine, IEEE 16-Machine and IEEE 50-Machine systems.

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“…An adaptive ANN was applied to predict rotor angle stability of generator for dynamic security assessment in [25]. In order to control frequency of loads for stochastic power systems, a deep reinforced learning method is proposed in [26]. Although these studies were done to obtain robust systems and better operating performance, they still have some difficulties for achieving stability in some operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning

Nazlibilek

Ali²,

Askir

2021

Teh. vjesn.

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Electrical power systems usually suffer from instabilities because of some disturbances occurring due to environmental conditions, system failures, and loading conditions. The most frequently encountered problem is the loss of synchronization between the rotor angle and the stator magnetic angle for synchronous generators. The contribution of this study is that a nonlinear adaptive control approach called feedback error learning (FEL) is utilized to improve the small-signal stabilities of an electric power system. The power system under study is composed of a synchronous machine connected to infinite bus. Many advantages of FEL control approach makes it capable to robustly adapting with all possible operating conditions rather than using optimization algorithms for tuning the conventional power system stabilizer (CPSS) that is still unsatisfactory especially at some critical operating points. The performances of two controllers, namely the proposed FEL scheme and the conventional controller CPSS, are tested by Matlab simulations. It is found that the FEL controller can be effectively used as an alternative stabilizer for improving small-signal stabilities of the power system.

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Small Signal Stability Analysis of Multi-Infeed Power Electronic Systems Based on Grid Strength Assessment

Cited by 124 publications

References 25 publications

A General Mathematical Model for LVRT Capability Assessment of DER-Penetrated Distribution Networks

A General Mathematical Model for LVRT Capability Assessment of DER-Penetrated Distribution Networks

A New Fast Track to Nonlinear Modal Analysis of Power System Using Normal Form

Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning

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