Nonlinear oscillations in power systems

Abed, Eyad H.; Varaiya, Pravin

doi:10.1016/0142-0615(84)90034-6

Cited by 211 publications

(76 citation statements)

References 2 publications

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“…However, the amount of calculation increases accordingly. This paper divided the wind speed of a single wind farm into 11 states according to the operating condition of the wind turbine.The detail is as following [12,25).…”

Section: P2(mw) P1(mw)mentioning

confidence: 99%

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Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Liu

et al. 2015

Sustainability

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Abstract:In the traditional studies on small-signal stability probability of a power system with wind farms, the frequency of wind speed was often assumed to obey to some extent a particular probability distribution. The stability probability that is thus obtained, however, actually only reflects the power system stability characteristics on long time scales. In fact, there is a direct correlation between the change of wind speed and the current state of wind speed, resulting in the system stability characteristics in different time periods having a great difference compared with that of long time scales. However, the dispatchers are more concerned about the probability that the power system remains stable in the next period or after several periods, namely the stability characteristics of the power system in a short period or multi-period. Therefore, research on multi-period small-signal stability probability of a power system with wind farms has important theoretical value and practical significance. Based on the Markov chain, this paper conducted in-depth research on this subject. Firstly, the basic principle of the Markov chain was introduced, based on which we studied the uncertainty of wind power by adopting the transition matrix and the wind speed−power output transformation model and established the probability distribution OPEN ACCESSSustainability 2015, 7 4583 model of multi-period wind power. Then the boundary-based small-signal stability probability evaluation method was used to establish an evaluation model of multi-period small-signal stability probability of power system with wind farms. Finally, taking the power system with two wind farms as an example, we analyzed its small-signal stability probability and studied the influence of the initial states of wind speed and different periods on the probability of stability. This study provides a new method and support for analyzing the small-signal stability probability of a power system with wind farms.

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Section: P2(mw) P1(mw)mentioning

confidence: 99%

“…Among them, Hopf bifurcation [24,25] relates to the oscillatory instability of the power system. This paper mainly focuses on the small-signal stability region boundary formed by this kind of bifurcation.…”

Section: Small-signal Stability Region Boundarymentioning

confidence: 99%

Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Liu

et al. 2015

Sustainability

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“…While, the dynamic bifurcation was linked by Abed and Varaiya [5], Abed et al [6], Rajagopalan et al [7], Dobson et al [8], and Nayfeh et al [9].…”

Section: Introductionmentioning

confidence: 99%

Control of Instable Chaotic Small Power System

Shariff¹,

Harb²

2015

JPEE

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In this paper, we aim to control an instable chaotic oscillation in power system that is considered to be small system by using a linear state feedback controller. First we will analyze the stability of the mentioned power system by means of modern nonlinear theory (Bifurcation and Chaos). Our model is based on a three bus power system that consists of multi generators containing both dynamic and static loads. They are considered to be in the form of an induction motor in parallel with a capacitor, as well as a combination of constant power along with load impedance, PQ. We consider the load reactive power as the control parameter. At this stage, after changing the control parameter, the study showed that the system is experiencing a subcritical Hopf bifurcation point. This leads to a chaos within the system period doubling path. We then discuss the system controllability and present that the all chaotic oscillations fade away through the linear controller that we impose on the system.

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“…Among them, HB [13,14], which physically represents a pair of conjugate eigenvalues crossing the imaginary axis, is related to the system oscillatory instability. This paper mainly focuses on stability region boundary consisting of Hopf bifurcations.…”

Section: Introductionmentioning

confidence: 99%

Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

Liu¹,

Ge²,

Lv³

et al. 2015

Energies

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Abstract:For the interconnected power system with large-scale wind power, the problem of the small signal stability has become the bottleneck of restricting the sending-out of wind power as well as the security and stability of the whole power system. Around this issue, this paper establishes a small signal stability region boundary model of the interconnected power system with large-scale wind power based on catastrophe theory, providing a new method for analyzing the small signal stability. Firstly, we analyzed the typical characteristics and the mathematic model of the interconnected power system with wind power and pointed out that conventional methods can't directly identify the topological properties of small signal stability region boundaries. For this problem, adopting catastrophe theory, we established a small signal stability region boundary model of the interconnected power system with large-scale wind power in two-dimensional power injection space and extended it to multiple dimensions to obtain the boundary model in multidimensional power injection space. Thirdly, we analyzed qualitatively the topological property's changes of the small signal stability region boundary caused by large-scale wind power integration. Finally, we built simulation models by DIgSILENT/PowerFactory software and the final simulation results verified the correctness and effectiveness of the proposed model.

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Nonlinear oscillations in power systems

Cited by 211 publications

References 2 publications

Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Control of Instable Chaotic Small Power System

Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

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