Due to its clean and renewable nature, wind energy is becoming one of the important renewable sources of energy in the world. Through its collaboration with other renewable sources of energy, such as solar energy, the world energy crises can be solved in the future. Comparatively with the past and due to the progressive integration of the nonlinear loads in the grid, the principal role of a Wind Energy Conversion System (WECS) is not only to capture the maximum power from the wind, but also to improve the quality of power. Consequently, with the development of the wind farms which are integrated into the grid, power quality could be better improved in the future. Variable speed wind generators are frequently used and are more attractive than fixedspeed systems because of their efficient energy production, improved power quality and dynamic performance during grid faults. Recently, the most of the wind energy conversion systems are equipped with a variable speed Doubly Fed Induction Generator. Many works are done about power generation and power quality improvement using a WECS. In this paper, Bacterial foraging optimization algorithm (BFOA) is used which has been widely accepted as a global optimization. BFOA is inspired by the foraging behaviour of Escherichia coli. BFOA has drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. It is used to obtain tuned proportional gain and integral gain, so that the power quality can be improved..
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