Real-coded genetic algorithm-based optimizing method for micrositing of wind power station

The invention discloses a real-coded genetic algorithm-based optimizing method for the micrositing of a wind power station. In the method, the measured wind speed in the wind farm is corrected by an index model in the direction of relative height; a power characteristic curve of a wind machine is discretized by a linearized method; for the wake flow of the wind machine, a linearized wake flow model is adopted; the wind speed of the wind machines at the wake flow of a plurality of wind machines is solved by a method of the summation of squared differences, when part of the wind machines are positioned in the wake flow, the wind speed is revised by a method of area coefficients; based on an optimizing target function of the micrositing in the design of the wind power station, when the total number of the wind machines in the wind power station is determined, the total generated energy is used as the target function, and when the total number of the wind machines in the wind power station is not determined, the kilowatt-hour cost is used as the target function; and the microcosmic arrangement site of each wind machine in the wind power station is obtained by the real-coded genetic algorithm-based optimizing method. By the method, the reliability of forecast is high, the optimizing efficiency is high and results are accurate.