Joint wind and ice hazard for transmission lines in mountainous terrain. Issue 232 (January 2023)
- Record Type:
- Journal Article
- Title:
- Joint wind and ice hazard for transmission lines in mountainous terrain. Issue 232 (January 2023)
- Main Title:
- Joint wind and ice hazard for transmission lines in mountainous terrain
- Authors:
- Davalos, Daniel
Chowdhury, Jubayer
Hangan, Horia - Abstract:
- Abstract: This paper focuses on analyzing the ice and wind conditions for a high voltage transmission line system going over mountainous terrain in British Columbia, Canada. After analyzing sixteen surrounding weather stations, an Artificial Neural Network (ANN) is performed for wind speed predictions, the Inverse Distance Weighted Interpolation method (IDW) is used for temperature estimations, and the K Nearest Neighbor Imputation (KNNI) is performed for precipitation rate on the unsampled site of interest. In-cloud icing is estimated using a simple empirical equation proposed by Makkonen & Ahti (1995), in addition to the ice accretion model proposed by Makkonen (2000). The weather data from the described procedure is compared with data from a Weather Research and Forecast model (WRF) reported in previous studies. The wind speed and ice accretion data are fitted to the Weibull and Generalized Pareto distributions, respectively, and five hundred years of data pairs are simulated in addition to the historical data based on those distributions. Finally, hazard contours are drawn, and the results are compared with the combined wind and ice values proposed in the National Standard of Canada (CSA-C22.3) for different reliability levels. Highlights: Provides weather analysis of 16 weather stations for a specific site of interest located in mountainous terrain. Analyzes ice accretion on transmission lines. Characterizes joint wind and ice hazard. Provides a comparison with theAbstract: This paper focuses on analyzing the ice and wind conditions for a high voltage transmission line system going over mountainous terrain in British Columbia, Canada. After analyzing sixteen surrounding weather stations, an Artificial Neural Network (ANN) is performed for wind speed predictions, the Inverse Distance Weighted Interpolation method (IDW) is used for temperature estimations, and the K Nearest Neighbor Imputation (KNNI) is performed for precipitation rate on the unsampled site of interest. In-cloud icing is estimated using a simple empirical equation proposed by Makkonen & Ahti (1995), in addition to the ice accretion model proposed by Makkonen (2000). The weather data from the described procedure is compared with data from a Weather Research and Forecast model (WRF) reported in previous studies. The wind speed and ice accretion data are fitted to the Weibull and Generalized Pareto distributions, respectively, and five hundred years of data pairs are simulated in addition to the historical data based on those distributions. Finally, hazard contours are drawn, and the results are compared with the combined wind and ice values proposed in the National Standard of Canada (CSA-C22.3) for different reliability levels. Highlights: Provides weather analysis of 16 weather stations for a specific site of interest located in mountainous terrain. Analyzes ice accretion on transmission lines. Characterizes joint wind and ice hazard. Provides a comparison with the standard CSA-C22.3 for three different hazard levels. … (more)
- Is Part Of:
- Journal of wind engineering and industrial aerodynamics. Issue 232(2022)
- Journal:
- Journal of wind engineering and industrial aerodynamics
- Issue:
- Issue 232(2022)
- Issue Display:
- Volume 232, Issue 232 (2022)
- Year:
- 2022
- Volume:
- 232
- Issue:
- 232
- Issue Sort Value:
- 2022-0232-0232-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-01
- Subjects:
- Wind and ice hazard -- Ice accretion modelling -- Transmission lines -- Reliability-based design
Wind-pressure -- Periodicals
Buildings -- Aerodynamics -- Periodicals
Pression du vent -- Périodiques
Constructions -- Aérodynamique -- Périodiques
Buildings -- Aerodynamics
Wind-pressure
Periodicals - Journal URLs:
- http://www.sciencedirect.com/science/journal/01676105 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jweia.2022.105276 ↗
- Languages:
- English
- ISSNs:
- 0167-6105
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5072.632000
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