Binary-real coding genetic algorithm for wind turbine positioning in wind farm

Abstract

In this paper, the wind turbine positioning problem is discussed. Binary-real coding method that combines binary coding method with real coding method is proposed. Wind turbine layout is optimized based on the linear wake model and genetic algorithm, with the target of minimizing the cost per unit power output or maximizing the profit of wind farm. Turbine power curve model with power control mechanisms is used and Weibull distribution is employed to describe the wind conditions. Two cases with simple models and a case with realistic models are used to test the present method. The results show that the new coding method inherits the advantages of both methods. The positions and the number of turbines are adjusted in the evolution process. The proposed coding method obtains the best number of wind turbines and the optimized layouts. It is an effective solution strategy for wind turbine positioning problem.