Coordinating Wind Farms and Battery Management Systems for Inter-Area Oscillation Damping: A Frequency-Domain Approach

Chandra, Souvik; Gayme, Dennice F.; Chakrabortty, Aranya

doi:10.1109/tpwrs.2013.2282367

Cited by 41 publications

(26 citation statements)

References 19 publications

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“…Since the frequency is generally smoother than voltage dynamics, due to the existing inertia of the system, frequency returns back to a value close to its nominal value. Meanwhile, some minor local or inter-area oscillation modes are also observable in frequency curve [18], [19].…”

Section: Simulation Resultsmentioning

confidence: 99%

Centralized load shedding based on thermal limit of transmission lines against cascading events

Hoseinzadeh

Amini

Bak

2017

2017 IEEE Power &Amp; Energy Society General Meeting

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Load shedding is the last and most expensive control action against system collapse and blackout. Achievement of an efficient emergency control to stabilize the power system following severe disturbances, requires two key objectives. First, preventing of further cascading outages, i.e. saving the available and determinant power system elements and second, issuing proper control actions to stabilize the power system inside the permissible time frame. In this paper online contingency analysis is performed to monitor secure and reliable operation of transmission lines. Load shedding locations are continuously updated based on loading rate/thermal limit of lines to prevent their outage. Simulation of severe contingencies carried out on 39 bus IEEE standard test system in DIgSILENT PowerFactory validates the efficiency of proposed method.

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Section: Simulation Resultsmentioning

confidence: 99%

Centralized load shedding based on thermal limit of transmission lines against cascading events

Hoseinzadeh

Amini

Bak

2017

2017 IEEE Power &Amp; Energy Society General Meeting

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“…Compared with FSIG, DFIG is comparatively new and has a more flexible control in active and reactive power, and thus most of research efforts are devoted to the grid connection study of DFIG in recent decade. Various case studies have been implemented to address different aspects of DFIG in affecting the oscillation stability such as integration method [4]- [9], inertia or other sensitivity based approach [10] [12], reactive power/voltage control [13]- [17], operating condition [18], virtual inertia control [19]- [21], additional damping control [22]- [32] and external energy storage system [33] [34].…”

Section: B Literature Reviewmentioning

confidence: 99%

Comparison analysis on damping mechanisms of power systems with induction generator based wind power generation

Zhang

Zhu

et al. 2018

International Journal of Electrical Power & Energy Systems

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The rotor structure varies with different types of wind power induction generator (WPIG), which leads to their different dynamic behaviors during power system disturbances. This paper proposes a generic implementation framework of explicit damping torque analysis to investigate the damping mechanisms of power system integrated with induction generator based wind power generation, so that the essential difference and inner connection between two main types of WPIG (i.e., DFIG and FSIG) in damping power system oscillation can be revealed. The linearized models which can represent DFIG and FSIG as well as three transitional wound rotor generators are established to facilitate the analytical comparison analysis. Phillips-Heffron system linearized model is employed to derive an explicit expression of damping torque contribution from main dynamic components of WPIGs. In the paper, 16-machine 5-area NYPS-NETS example system is used for the demonstration of proposed framework and comparison analysis. Both damping effectiveness and robustness of different WPIGs are extensively examined under multiple operating status, in order to provide useful guidance to system planner for the real-time operation of induction generator based wind generation.

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“…Applying (9) On the other hand, we can choose α 4 = 4117.8σ 2 so that the Inequality (5) holds. Since the eigenvalues of P are 1.2 and 4117.8, α 1 and α 2 are chosen as α 1 = 1.2(x 1 2 + x 2 2 ) and α 2 = 4117.8(x 1 2 + x 2 2 ), respectively.…”

Section: A Stochastic Single-machine Infinite-bus Systemmentioning

confidence: 99%

“…On the other hand, power system stabilizers (PSSs) are applied for enhancing stochastic small-signal stability via eigenvalue sensitivity analyses [6]. Furthermore, the adaptive control based strategies [7,8], frequency-domain approach [9], and particle swarm optimization-based methods [10] are adopted to enhance power system stability with stochastic disturbances. In [11], uncertainties are characterized by a compact set, then robust optimization is carried out for the worst-case scenario, or the random factors are measured in real time in the context of the adaptive control.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Small Signal Stability of a Power System with Uncertainties

Wen

Zhao

et al. 2018

Energies

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The ever-increasing penetration of wind power generation and plug-in electric vehicles introduces stochastic continuous disturbances to the power system. This paper proposes an analytical approach to analyze the influence of stochastic continuous disturbances on power system small signal stability. The noise-to-state stability (NSS) and NSS Lyapunov function (NSS-LF) are adopted for stability analysis with respect to the magnitude of uncertainties in a power system. The power system is modeled as a set of stochastic differential equations (SDEs). The supremum of the norm of the covariance is employed to characterize the influence of magnitudes of uncertainties on the power system. Then the relationship between the magnitudes of stochastic variations and probabilistic stability is explicitly identified by NSS. The proposed method can assess the stochastic stability of the power system by checking some algebraic expressions. Hence, it has high computation efficiency compared with the well-established Monte Carlo based method. Besides, since the magnitudes of the stochastic variations are integrated into the definition of the stochastic stability, the proposed method provides theoretical explanations for the impacts of uncertainties.

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Coordinating Wind Farms and Battery Management Systems for Inter-Area Oscillation Damping: A Frequency-Domain Approach

Cited by 41 publications

References 19 publications

Centralized load shedding based on thermal limit of transmission lines against cascading events

Centralized load shedding based on thermal limit of transmission lines against cascading events

Comparison analysis on damping mechanisms of power systems with induction generator based wind power generation

Stochastic Small Signal Stability of a Power System with Uncertainties

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