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

A genetic algorithm and micro-site selection technology, applied in wind power generation, wind turbine combination, genetic model, etc., can solve the problems of wind turbines' annual utilization hours not meeting the design requirements, low return on investment, and large workload.

Inactive Publication Date: 2011-08-03
HOHAI UNIV
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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

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

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Embodiment Construction

[0049] The wind farm optimization micro-site selection method based on genetic algorithm adopts the exponential method to correct the measured wind speed of the wind farm to the height direction, adopts the linearized discrete for the power characteristics of the wind turbine, and adopts the linearized wake model for the wake of a single wind turbine. The difference-square accumulation method is used for the wind speed of the wind turbine in the wake of multiple wind turbines, and the situation that the wind turbine is partially in the wake is considered. At this time, the area coefficient correction is used to determine the optimization goal of micro-site selection in the design of wind farms. When the total number of wind turbines is determined, the total power generation is selected as the objective function. When the total number of wind turbines in the wind farm is not determined, it is necessary to determine the number of wind turbines and the micro-address of the arrangem...

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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 optimization design method for optimizing the specific position of each wind turbine in a wind farm area using the wake model of the wind turbine and a genetic algorithm based on real number coding in a given wind farm area, and belongs to energy power engineering and electrical engineering. issues in the field. Background technique [0002] As one of the most promising energy sources to replace fossil energy, wind power has been vigorously developed in countries around 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 thing that should be considered is the location of wind farms. The quality of site selection plays a very important role in the economy of wind power generation. Wind farm site selection is divided into macro site selection and micro site selection. The...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12F03D9/00F03D9/25
CPCY04S10/545Y02E40/76Y02E10/72Y02E40/70Y04S10/50
Inventor 许昌严彦刘德有郑源
Owner HOHAI UNIV
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