A Classification Method for Transmission Line Icing Process Curve Based on Hierarchical K-Means Clustering

Hao, Yanpeng; Yao, Zhaohong; Wang, Junke; Li, Hao; Li, Ruihai; Yang, Lin; Liang, Wei

doi:10.3390/en12244786

Cited by 7 publications

(4 citation statements)

References 25 publications

(29 reference statements)

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“…Huang et al (2017) applied a genetic algorithm for hyper-parameter optimization in the icing prediction model, in order to improve model accuracy. However, these basic statistical methods typically use linear models for icing prediction, without considering nonlinear conditions (Hao et al, 2019). With the advent of the era of big data and artificial intelligence (AI), more and more machine learning methods have been applied to various fields.…”

Section: Figurementioning

confidence: 99%

Prediction model for transmission line icing based on data assimilation and model integration

Wang,

Shen,

Jin

et al. 2024

Front. Environ. Sci.

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With the increase of extreme weather events such as cold waves, power transmission line icing has become more and more severe, affecting the safe and stable operation of power systems. Thus, icing prediction has become crucial for power grids. In this study, we collect multi-source data including the historical observations of meteorological elements and transmission line icing in Sichuan during 2017–2019, and develop an artificial intelligence (artificial intelligence)-based integrated model to achieve icing thickness prediction according to meteorological elements. Using the Weather Research and Forecasting model and the three-dimensional variational data assimilation method, we analyze the weather conditions in Sichuan of China during the 2020 winter, and obtain the high-precision meteorological element fields that are related to icing prediction. The forecasted meteorological elements are then combined with the AI-based integrated model to predict icing conditions, assisting in the warning of transmission line icing. The results indicate that the AI-based integrated model displays superior performance on the accurate prediction of icing thickness in the test set, with only two samples having prediction errors of more than 3 mm. Data assimilation can effectively improve the forecast accuracy of meteorological elements near icing observation stations and thus enhance the accuracy of icing thickness prediction. In particular, icing thickness prediction is remarkably improved at Gaoqiao, Laolinkou and Erlangshan stations.

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Section: Figurementioning

confidence: 99%

Prediction model for transmission line icing based on data assimilation and model integration

Wang,

Shen,

Jin

et al. 2024

Front. Environ. Sci.

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“…In the electric lines case study, K-means algorithms are primarily used in cascade fault prevention, allowing the decision maker to have an early warning [103]. Meteorological conditions, such as ice, can influence electric line performances, so K-means algorithms are utilized to perform an anti-ice prediction strategy [104].…”

Section: B Power Transmission and Dispatching 1) Electric Linesmentioning

confidence: 99%

K-Means and Alternative Clustering Methods in Modern Power Systems

Miraftabzadeh,

Colombo,

Longo

et al. 2023

IEEE Access

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As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in computational capabilities, clustering algorithms, including K-means, are becoming essential tools for researchers in analyzing, optimizing, and modernizing power systems. This paper presents a comprehensive review of over 440 articles published through 2022, emphasizing the application of K-means clustering, a widely recognized and frequently used algorithm, along with its alternative clustering methods within modern power systems. The main contributions of this study include a bibliometric analysis to understand the historical development and wide-ranging applications of K-means clustering in power systems. This research also thoroughly examines K-means, its various variants, potential limitations, and advantages. Furthermore, the study explores alternative clustering algorithms that can complete or substitute K-means. Some prominent examples include K-medoids, Time-series K-means, BIRCH, Bayesian clustering, HDBSCAN, CLIQUE, SPECTRAL, SOMs, TICC, and swarm-based methods, broadening the understanding and applications of clustering methodologies in modern power systems. The paper highlights the wide-ranging applications of these techniques, from load forecasting and fault detection to power quality analysis and system security assessment. Throughout the examination, it has been observed that the number of publications employing clustering algorithms within modern power systems is following an exponential upward trend. This emphasizes the necessity for professionals to understand various clustering methods, including their benefits and potential challenges, to incorporate the most suitable ones into their studies.INDEX TERMS Clustering algorithms, K-means clustering, power systems. FIGURE 3. K-means clustering and power system bibliometric trend per country.

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“…Serious accidents are easily caused by the icing of 10 kV transmission lines, which brings considerable challenges to the safe operation of the power grid [1][2][3][4]. In 2008, normal activities in southern China were severely disrupted due to largescale line failures caused by continuous ice and snow [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…In the operation and maintenance of transmission lines, the comparison of the equivalent ice thickness (EIT) and the designed ice thickness is usually used to select the ice melting strategy. Equivalent ice thickness refers to the thickness that converts different densities and shapes of ice into uniform annular ice with a density of 0.9 g/cm 3 . The measured sag and temperature calculate the EIT in the sag measurement method for 110 kV and above transmission lines [13].…”

Section: Introductionmentioning

confidence: 99%

Experimental study on ice monitoring method for 10 kV transmission line with tangent tower in alpine landform

Yang,

Chen,

Hao

et al. 2023

High Voltage

Self Cite

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Ice monitoring methods were applied for 110 kV and above transmission lines with tangent towers. However, the change in the vertical span is not considered, and a significant difference lies in the tower‐conductor structure of 10 kV transmission lines. For this reason, a proposal is made about the ice monitoring method for the 10 kV transmission line with tangent tower in alpine landform, which includes the ice monitoring system based on pressure measurement and corresponding equivalent ice thickness calculating methods. Different methods calculate the vertical span under different height difference coefficients. A finite element simulation model and a simulated ice load experiment system are established based on real conductors and insulators. Experiments and simulations under four simulated terrains are conducted within 2.5–20 mm ice thickness range. The comparison is made between this method and the method without considering the change in vertical span. The results show that the two methods are consistent and the relative errors are lower than ±4% in simulation and ±10% in experiment when the height difference coefficient is 0. When it is not 0, the relative errors of this method fall between +0.38% and +6.78% in simulation and −6.40% to +6.60% in experiment, while the relative errors of the method without considering the change in vertical span ranges between −11.13% and −20.23% in simulation and −11.65% to −23.20% in experiment.

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A Classification Method for Transmission Line Icing Process Curve Based on Hierarchical K-Means Clustering

Cited by 7 publications

References 25 publications

Prediction model for transmission line icing based on data assimilation and model integration

Prediction model for transmission line icing based on data assimilation and model integration

K-Means and Alternative Clustering Methods in Modern Power Systems

Experimental study on ice monitoring method for 10 kV transmission line with tangent tower in alpine landform

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