Energy Storage System Controller Design for Suppressing Electromechanical Oscillation of Power Systems

Yang, Bo; Li, Guanjun; Tang, Wencheng; Hu, Ailian; Zhang, Donghui; Wu, Yongbin

doi:10.3390/app9071329

Cited by 2 publications

(3 citation statements)

References 22 publications

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“…Reference [15] studies the oscillations of wind farms' synchronous generators. Reference [16] describes the implementation of an energy storage system for the damping of electromechanical oscillations of synchronous generators. References [17][18][19] describe the effects of control appliances on the power grid frequency, power system blackouts, and cascading failures.…”

Section: Existing Solutions and Literature Reviewmentioning

confidence: 99%

Analysis of Synchronous Generators’ Local Mode Eigenvalues in Modern Power Systems

Ritonja

Polajžer

2021

Applied Sciences

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New energy sources, storage facilities, power electronics devices, advanced and complex control concepts, economic operating doctrines, and cost-optimized construction and production of machines and equipment in power systems adversely affect small-signal stability associated with local oscillations. The objective of the article is to analyze local oscillations and the causes that affect them in order to reduce their negative impact. There are no recognized analyses of the oscillations of modern operating synchronous generators exposed to new conditions in power systems. The basic idea is to perform a numerical analysis of local oscillations of a large number of synchronous generators in the power system. The paper represents the local mode data obtained from a systematic analysis of synchronous generators in the Slovenian power system. Analyzed were 74 synchronous generators of the Slovenian power system, plus many additional synchronous generators for which data were accessible in references. The mathematical models convenient for the study of local oscillations are described first in the paper. Next, the influences of transmission lines, size of the synchronous generators, operating conditions, and control systems were investigated. The paper’s merit is the applicable rules that have been defined to help power plant operators avoid stability-problematic situations. Consequently, boundaries were estimated of the eigenvalues of local modes. Finally, experiments were performed with a laboratory-size synchronous generator to assess the regularity of the numerically obtained conclusions. The obtained results enable the prediction of local oscillations’ frequencies and dampings and will be useful in PSS planning.

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Section: Existing Solutions and Literature Reviewmentioning

confidence: 99%

Analysis of Synchronous Generators’ Local Mode Eigenvalues in Modern Power Systems

Ritonja

Polajžer

2021

Applied Sciences

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“…Guyuan Wind Farm is located in North China. The main model of the wind farm is 1.5 MW Double fed induction generator (DFIG), supplemented by a small number of PMSG and constant speed induction generators 6 . The wind farm is distributed in an area of thousands of square kilometers.…”

Section: Introductionmentioning

confidence: 99%

“…In the current project, the oscillation evaluation is mainly based on the method of disturbance power statistics 6 , 8 . The core of this method is to screen out the values with high disturbance intensity and count the number of times by setting a threshold.…”

Section: Introductionmentioning

confidence: 99%

Research on high proportion of clean energy grid-connected oscillation risk prediction technology based on CNN and trend feature analysis

Pu,

Yingnan,

Chongjuan

et al. 2023

Sci Rep

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Oscillations, commonly known as a universal, propagative, and intricate event in the new power system, often give rise to generator tripping and load shedding, not only adversely affecting the power flow limit and the power angle stability but also posing threats to the lines of defense for stability and protection. Traditionally, emphasis has been laid on post-fault oscillation management, an emergency measure to deal with the impact and damage that have already affected the power grid. As such, this paper focuses on an oscillation prediction technique to detect oscillation energy early and intervene proactively to prevent further faults. This technique effectively lessens the damage caused by impacts and disconnects to the power grid. Firstly, this paper proposes the concept of disturbance power density and establishes the correlation between disturbance energy and the time domain, thereby exploring a method for evaluating the pattern of electrical quantities before power system oscillation. Secondly, it speeds up the time it takes to detect faults by catching nuances of voltage-current phase angle and impedance. Lastly, it puts forward a technique to cope with the intricacy and variety of power grid equipment using the convolutional neural network (CNN). This technique incorporates an integrated attention mechanism within a one-dimensional CNN model to capture the implicit mapping between voltage, active power, and reactive power at any time in the power system. This enables the model to self-learn multi-device characteristics and enhances the possibility of using theory in practical ways. Moreover, practical case studies also show that the prediction technique proposed in this paper can effectively issue warnings eight minutes before the occurrence of oscillation.

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Energy Storage System Controller Design for Suppressing Electromechanical Oscillation of Power Systems

Cited by 2 publications

References 22 publications

Analysis of Synchronous Generators’ Local Mode Eigenvalues in Modern Power Systems

Analysis of Synchronous Generators’ Local Mode Eigenvalues in Modern Power Systems

Research on high proportion of clean energy grid-connected oscillation risk prediction technology based on CNN and trend feature analysis

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