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

Abstract

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.

Description

technical field [0001] The invention relates to an optimal design method for optimally selecting a specific position of each wind turbine in a wind farm by using a wake model of a wind turbine and a genetic algorithm based on real number coding in a given wind farm area, belonging to energy power engineering and electrical engineering field problems. Background technique [0002] As one of the most promising energy sources to replace fossil energy, wind power has been vigorously developed in countries all over the world including China in recent years. Among them, China's annual installed capacity growth rate has exceeded 100% in the past five years. [0003] In the practical application of wind energy, the first consideration is the site selection of wind farms. The quality of site selection plays a very important role in the economy of wind power generation. The site selection of wind farms is divided into macro site selection and micro site selection. The principle of ma...

AI Technical Summary

Problems solved by technology

[0006] Technical issues: At present, the micro-site selection of wind farms has been carried out using imported commercial software. Commercial software also requires designers to arrange the specific addresses of each wind turbine based on experience and manual experience, and compare them according to objective functions such as economy or wind energy utilization efficiency. The final micro-address, the workload is heavy, and it can not achieve the optimal layout of wind turbines with the best power generation or economic benefits. Sometimes the annual utilization hours of individual wind turbines are far from meeting the design requirements. The lower power generation efficiency reduces the advantages of wind power generation compared with other power sources

Images