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Multivariable time series prediction for the icing process on overhead power transmission line.

Li P, Zhao N, Zhou D, Cao M, Li J, Shi X - ScientificWorldJournal (2014)

Bottom Line: In this model, the time effects of micrometeorology parameters for the icing process have been analyzed.Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness.According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering, Yunnan University, Kunming 650091, China ; Department of Automation, Tsinghua University, Beijing 100084, China ; Yunnan Electric Power Research Institute, China Southern Power Grid Corp., Kunming 650217, China.

ABSTRACT
The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

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Related in: MedlinePlus

Meteorology data and icing load curves I (2009.12.14–2010.1.25).
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig2: Meteorology data and icing load curves I (2009.12.14–2010.1.25).

Mentions: Due to the huge damage of freezes disaster in January 2008, CSPGC has built the icing monitoring systems in some important overhead transmission lines in the northeast area of Yunnan Province. The micrometeorology and force data are collected by field sensors and synchronously transmitted to monitoring center through GSM (global system for mobile) communication system. Figure 2 shows three icing processes, two of which are serious, in the Tao-Luo-Xiong Transmission Line from December 14th of 2009 to January 25th of 2010. There is an obvious relationship between the icing load (weight) and influence factors, such as the environment temperature, humidity, wind speed, wind direction, air pressure, and sunlight intensity.


Multivariable time series prediction for the icing process on overhead power transmission line.

Li P, Zhao N, Zhou D, Cao M, Li J, Shi X - ScientificWorldJournal (2014)

Meteorology data and icing load curves I (2009.12.14–2010.1.25).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4127214&req=5

fig2: Meteorology data and icing load curves I (2009.12.14–2010.1.25).
Mentions: Due to the huge damage of freezes disaster in January 2008, CSPGC has built the icing monitoring systems in some important overhead transmission lines in the northeast area of Yunnan Province. The micrometeorology and force data are collected by field sensors and synchronously transmitted to monitoring center through GSM (global system for mobile) communication system. Figure 2 shows three icing processes, two of which are serious, in the Tao-Luo-Xiong Transmission Line from December 14th of 2009 to January 25th of 2010. There is an obvious relationship between the icing load (weight) and influence factors, such as the environment temperature, humidity, wind speed, wind direction, air pressure, and sunlight intensity.

Bottom Line: In this model, the time effects of micrometeorology parameters for the icing process have been analyzed.Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness.According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering, Yunnan University, Kunming 650091, China ; Department of Automation, Tsinghua University, Beijing 100084, China ; Yunnan Electric Power Research Institute, China Southern Power Grid Corp., Kunming 650217, China.

ABSTRACT
The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

Show MeSH
Related in: MedlinePlus