Title :
Genetic algorithm technique on wind turbine and sensitive equipment placement against lightning
Author :
Kazazi, S. ; Raahemifar, Kaamran
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
Abstract :
Lightning as a natural phenomenon represents directly and indirectly a risk for wind turbines and other objects as the transient voltages may reach dangerous levels for people, equipment, and transmission lines. It is important to consider lightning and its consequences on the placement of wind turbines, buildings, and other sensitive electrical installations. The objective of this study is to optimize the placement of a wind farm for minimum lightning occurrence on the turbines. The method is also applied to optimize the location of any other sensitive installation for minimum electromagnetic interference from lightning current in any geographic area. The process involves gathering accurate lightning data information for the interested area from North American Lightning Detection Network (NALDN) over a period of time and using the genetic algorithm optimization technique using MATLAB to determine the wind farm location and other sensitive equipment placement. It is found that genetic algorithm optimization technique produced results which are very consistent considering different scenarios. The findings in this study could help wind farm designers in addition to other criteria for energy collecting efficiency of wind turbines in order to determine the best location of wind farms.
Keywords :
electromagnetic interference; genetic algorithms; lightning protection; transients; wind power plants; wind turbines; NALDN; North American Lightning Detection Network; energy collecting efficiency; genetic algorithm optimization technique; lightning current; lightning data information; minimum electromagnetic interference; sensitive electrical installation; sensitive equipment placement; transient voltage; transmission line; wind farm location; wind turbine; Genetic algorithms; Lightning; Linear programming; Optimization; Transient analysis; Wind farms; Wind turbines; Electromagnetic transient; genetic algorithm; induced voltage; lightning protection; wind turbine placement;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2013 26th Annual IEEE Canadian Conference on
Conference_Location :
Regina, SK
Print_ISBN :
978-1-4799-0031-2
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2013.6567692