A new power swing detection method based on chaos theory

Salehimehr, Sirus; Taheri, Behrooz; Razavi, Farzad; Parpaei, Mohammad; Faghihlou, Milad

doi:10.1007/s00202-019-00898-3

Cited by 17 publications

(20 citation statements)

References 42 publications

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“…The improved version of AOA uses the chaotic theory 29 to model the population diversity in the exploitation phase. It is achieved by introducing the random behavior characteristic of this theory into the algorithm to enhance the performance and identify the global optimal solution with better convergence.…”

Section: Proposed Methodologymentioning

confidence: 99%

Hybrid deep‐Q Elman neural network for crop prediction and recommendation based on environmental changes

Shingade

Mudhalwadkar

2022

Concurrency and Computation

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Crop recommendation is a potential research topic that relies on environmental conditions such as temperature, humidity, rainfall, and soil pH to identify suitable crops for cultivation. There are diverse models available in the literature for crop recommendation. Still, those models are not accurate enough to predict the appropriate crop when there is a sudden change in the environmental factors. The models cannot map the raw data exactly with the prediction values, and the output relies on the quality of the input features used. To resolve these issues, the concept of Q‐learning is hybridized with deep learning to enable exact mapping of the raw data with the prediction values. In this article, Q‐learning is combined with the Elman neural network, trained with the input parameters selected by the improved Archimedes optimization algorithm from the dataset. The model evaluations are carried out with the user dataset constructed using the sensor information collected from the regions of Maharashtra. The overall accuracy provided by the proposed crop recommendation model is 99.44%, and the average inference time of the model is 0.0117 s.

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Section: Proposed Methodologymentioning

confidence: 99%

Hybrid deep‐Q Elman neural network for crop prediction and recommendation based on environmental changes

Shingade

Mudhalwadkar

2022

Concurrency and Computation

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“…Referring to Section 2.3, the proper functioning of the proposed method strongly depends on the choice of the threshold value. This threshold value is determined using the methods described in [45, 46]. In these methods, this threshold value is determined by numerical simulation.…”

Section: Proposed New Methodsmentioning

confidence: 99%

“…The single line diagram of this network is shown in Fig. 6 [46]. This network consists of 39 buses and 10 generators.…”

Section: Software Evaluation Of the Proposed Methodsmentioning

confidence: 99%

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Detection of power swing and prevention of mal‐operation of distance relay using compressed sensing theory

Taheri

Sedighizadeh

2020

IET Generation, Transmission & Distribution

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“…Reference [42] uses Hilbert Transform to reduce fault detection time. This method can detect PS with a phase angle of 180 degrees.…”

Section: Difference Between Three-phase Signalsmentioning

confidence: 99%

An overview of power swing detection methods in distance relays and the factors involved

Taheri

Hosseini

Salehimehr

2022

IET Generation Trans & Dist

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Nowadays, due to the simplicity of operation and proper coordination characteristics, distance relays are being extensively used in the protection of power transmission lines. Despite many advantages, the distance relay is exposed to a maloperation when a power swing phenomenon occurs. Power swings may occur due to major disturbances, such as switching lines, generator interruptions, and connecting or disconnecting a large part of the loads, causing outages in healthy lines. Detecting power swing and preventing distance relay maloperation has always been a challenge. In addition, different parameters can have a great impact on the performance of power swing detection methods. In this paper, these parameters and their effects are examined along with various methods for detecting power swings. Accordingly, this comprehensive review covers all aspects of power swing phenomenon and its detection, including causes of power swings, power swing detection methods, determining threshold values in power swing methods, effecting of compensated lines and wind farms in power swing detection methods, and testing power swing function in the distance relays. It is hoped that this study will be helpful for researchers in power system protection to find relevant references and develop new methods for power swing function.

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A new power swing detection method based on chaos theory

Cited by 17 publications

References 42 publications

Hybrid deep‐Q Elman neural network for crop prediction and recommendation based on environmental changes

Hybrid deep‐Q Elman neural network for crop prediction and recommendation based on environmental changes

Detection of power swing and prevention of mal‐operation of distance relay using compressed sensing theory

An overview of power swing detection methods in distance relays and the factors involved

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