World is facing a big problems for fossil fuel as it deals with the issues like availability, environmental effect like global warming etc, which forces us to explore new renewable sources of energy like solar, tidal, geothermal, wind etc. Among all the energies wind energy is the effective form of energy. As evaluated from the research, main cause for reduction of energy output in wind farm is the positioning of the wind turbine, as it is a function of wake loss. Present paper investigates an effective meta-heuristics optimization method known as Teaching–Learning-Based Optimization (TLBO), to optimize the positioning of the wind turbine in a wind farm. Two different scenarios of wind speed and its direction distribution across the wind site is considered like, (a) uniform wind speed of 12 m/s with uniform direction and (b) uniform wind speed of 12 m/s with variable wind direction. The results show that the implementation of TLBO is effective then other existing strategy, in terms of maximized expected power output and minimum wake effect of turbines by each other.

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