Typical Modes of the Wind Speed Diurnal Variation in Beijing Based on the Clustering Method

Yan, Pengcheng; Zuo, Depeng; Yang, Ping; Li, Suosuo

doi:10.3389/fphy.2021.675922

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…Notably, in this manuscript, the number (K value) of typical terrain patterns, which is set according to the number of terrains related to ice cover in the past, is confirmed artificially due to the limitations of the K-means method itself. For research in other regions where typical terrain is uncertain, we can also use the elbow method [21,22] to determine the number of typical terrain patterns when we are unsure how many typical terrains we need to choose.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Research on the Identification of Typical Terrain Patterns in Yunnan Province Based on the K-Means Technology

Zhou,

Huai,

Yan

et al. 2024

Atmosphere

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Wire icing is a prevalent challenge in both industrial and scientific domains, and it is widely acknowledged that terrain and water vapor are significant contributing factors in the formation of wire icing. Consequently, the identification of terrains that are prone to inducing water vapor uplift serves as the scientific foundation for predicting ice accumulation on power lines. Yunnan Province, a mountainous province in China, features a large elevation difference. In winter, this region is prone to wire, pole and tower icing, which can affect power transmission and cause economic and property losses. Therefore, it is necessary to conduct research on the identification of typical terrain patterns in this region. In previous terrain studies, more attention has been focused on slope and aspect, watershed analysis and terrain profile analysis. When the purpose of the terrain identification is to analyze which terrains are more prone to collecting water vapor, we hope to obtain slightly larger terrain blocks and analyze the water vapor sources for different terrains in order to identify typical terrains that are conducive to icing formation. A new technology for identifying terrain patterns based on the K-means clustering method is proposed in this study to explore the typical terrain in Yunnan province. Additionally, the influences of different terrain patterns on water vapor movement are also analyzed. The results indicate that the typical terrains in Yunnan are “Valley-Air Channel”, “Topographic Uplifting”, “Ravine”, “Mountain Pass” and “Alpine Divide” patterns. The results show that the identified typical terrain is consistent with observations from satellite images, which verifies the effectiveness of this identification method. Among these five typical terrains, the “Valley-Air Channel”, the “Topographic Uplifting” and the “Mountain Pass” terrains are prone to collecting water vapor and forming ice cover. The “Alpine Divide” terrain is also prone to accumulating water vapor on both sides to form ice cover. The identified typical terrain demonstrates that typical terrain patterns near water bodies are more prone to the occurrence of wire, pole and tower icing because these areas are abundant in water vapor, and the extensive water vapor is easily condensed under the effects of terrain uplifting and cooling. In these key areas, existing wires and towers, as well as those to be constructed in the future, deserve our special attention.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Research on the Identification of Typical Terrain Patterns in Yunnan Province Based on the K-Means Technology

Zhou,

Huai,

Yan

et al. 2024

Atmosphere

Self Cite

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Comparison of deterministic wind speed generation models for wind erosion modeling

Han

Chang

Guo

et al. 2023

Agricultural and Forest Meteorology

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Wind and Sea Breeze Characteristics for the Offshore Wind Farms in the Central Coastal Area of Taiwan

Cheng

Teng³

2022

Energies

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Renewable energy is crucial for achieving net zero emissions. Taiwan has abundant wind resources and most major wind farms are offshore over the Taiwan Strait due to a lack of space on land. A thorough study that includes time series modeling of wind speed and sea breeze identification and evaluation for Taiwan’s offshore wind farms was conducted. The time series modeling identified two periodic (annual and diurnal) components and an autoregressive model for multiple-year wind speed time series. A new method for sea breeze type identification and magnitude evaluation is proposed. The method (named as EACH) utilizes a vector and an ellipse to represent the wind condition of a day. Verification of the type identification determined by the new method in two cases of different seasons has been conducted by using surface weather charts and wind data measured by lidar. It is a concise, effective, and programmable way to filter a number of dates for type identification and speed change precursor of sea breeze. We found that the typical daily wind power production of corkscrew sea breeze in Central Taiwan is more than 33 times that of pure sea breeze and more than 9 times that of backdoor sea breeze, which highlights the impact of sea breeze types on wind power.

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Typical Modes of the Wind Speed Diurnal Variation in Beijing Based on the Clustering Method

Cited by 3 publications

References 25 publications

Research on the Identification of Typical Terrain Patterns in Yunnan Province Based on the K-Means Technology

Research on the Identification of Typical Terrain Patterns in Yunnan Province Based on the K-Means Technology

Comparison of deterministic wind speed generation models for wind erosion modeling

Wind and Sea Breeze Characteristics for the Offshore Wind Farms in the Central Coastal Area of Taiwan

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