Evaluation and Adjustment Based on Broad Learning System for Small Signal Stability Analysis of Power System Integrated with Wind Farms

Yang, Yude; Yao, Wen-Jing; Yang, Lizhen

doi:10.1007/s42835-022-01111-5

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…In [24], using the state-space method, the average model of the converter in a DC MG is constructed to analyze its stability, and the trajectory of the system's eigenvalue is determined. It was determined that the greater the control coefficient, the greater the stability.…”

Section: Research On Stability Of DC Mgsmentioning

confidence: 99%

Review of Voltage Control Strategies for DC Microgrids

Lu,

Wang,

Wang

2023

Energies

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With the continuous development of the global economic level, global energy consumption is also on the rise, and the global power industry is faced with a number of formidable challenges including load growth, low energy efficiency, high power quality, and environmental protection. Despite the fact that distributed energy cannot be directly connected to the power grid, the concept of the microgrid (MG) is proposed to make better use of distributed energy and reduce its effect on the power grid. The low cost and high controllability of DC MGs have piqued the interest of academicians both at home and abroad. If DC MGs are to be implemented in real-world engineering, a stability control strategy is required; therefore, research on voltage stability and coordinated control of DC MGs is extremely important and promising. This paper summarizes the current research on the voltage control strategy of the DC MG from the perspective of the voltage control strategy of the DC MG. Lastly, it is proposed that the future development of DC MGs will be more focused on intelligence and control precision and that the consistency algorithm combined with the benefits of centralized control and distributed control can effectively aid the future development of DC MGs, taking into account the grid’s dependability and control precision.

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Section: Research On Stability Of DC Mgsmentioning

confidence: 99%

Review of Voltage Control Strategies for DC Microgrids

Lu,

Wang,

Wang

2023

Energies

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“…Deep learning updates weights and adjusts hyperparameters based on back propagation. BLS uses pseudo-inverse methods to calculate weights; this avoids problems such as local optimization and gradient explosion, which are issues faced by the deep learning methods [34,36].…”

mentioning

confidence: 99%

“…Compared with RVFLNN, BLS first maps the inputs to build a set of mapped features. These features are used as the input layer of the original RVFLNN [36]. The process of the BLS training model is as follows:…”

mentioning

confidence: 99%

Predictive Analysis and Correction Control of CCT for a Power System Based on a Broad Learning System

2023

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Transient stability is an important factor for the stability of a power system. With improvements in voltage levels, and the expansion of power network scales, the problem of transient stability is particularly prominent. When a power system circuit fails, if the operation time of the relay protection device is higher than the critical clearing time (CCT), the relay protection device cannot cut the fault line in a timely manner. It is essential to forecast and adjust the CCT to improve the stability of the system; therefore, a method is proposed in this paper to predict and evaluate the critical clearing time using the broad learning system (BLS). The sensitivity of the critical clearing time can be easily calculated based on the prediction results of the critical clearing time using BLS. Moreover, the critical clearing time can be modified using the BLS correction control model. The proposed method was verified using a 4-machine 11-node system and a 10-machine 39-node system. According to the experimental results, the proposed model can predict, evaluate, and correct the CCT very well.

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