Wind turbine micro-siting device and method based on binary coded genetic algorithm

A binary coding and micro-site selection technology, which is applied in computing, special data processing applications, instruments, etc., can solve the problems of large calculation errors, heavy workload, and limitations in complex terrain

Active Publication Date: 2013-02-27
STATE GRID LIAONING ELECTRIC POWER RES INST +3
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Problems solved by technology

[0004] In the existing micro-site selection, software such as WasP and WindFarmer are mainly used for site selection. However, the software can calculate the maximum power generation of the wind farm only after the micro-site selection of each wind turbine needs to be manually arranged. , in order to obtain the optimal result, it is necessary to manually determine the micro-site selection many times, so the workload will be relatively large; in addition, these commercial software are relatively limited to the wind turbine site selection on flat terrain, and the calculation error for complex terrain will be relatively large

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  • Wind turbine micro-siting device and method based on binary coded genetic algorithm
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  • Wind turbine micro-siting device and method based on binary coded genetic algorithm

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Embodiment 1

[0047] The invention is a microscopic site selection device and method for a fan based on a binary coding genetic algorithm. Such as figure 1 As shown, different wind turbine wake models can be selected according to different terrains to calculate the output power and noise impact of the wind farm, and the investment and maintenance costs of the wind farm can be calculated to maximize the economic benefits of the wind farm. The wind speed data of the wind farm is obtained through the measurement of the anemometer; the obstacles, ground roughness and other data can be obtained through the hardware device camera to collect images and then identify and process the data. The image acquisition is to collect the surrounding environment image of the alternative wind farm by the camera device, which is transmitted to the image processing chip SPCA563A for processing through the image CMOS sensor SPCA561A, and then processed by the 16-bit single-chip microcomputer SPCE061A to judge the...

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Abstract

The invention relates to the technical field of wind turbine siting in a wind power plant, in particular to a wind turbine micro-siting device and a wind turbine micro-siting method based on binary coded genetic algorithm. The wind turbine micro-siting device has the structure that a camera device is connected with a CMOS (Complementary Metal Oxide Semiconductor) image sensor which is connected with an image processing chip, and the image processing chip is connected with an SPCE (Screen Printed Carbon Electrode) 0161A singlechip microcomputer; and an air velocity transducer is connected with an A/D (Analog to Digital) converter which is connected with a 89C51 singlechip microcomputer. The wind turbine micro-siting device and the method are suitable for wind turbine siting in both places with flat terrains and places with complex terrains. The wind turbine micro-siting device and the method have the advantages that target optimization is diversified, the investment cost of the wind power plant is small and the economic benefit is high; and the annual electric power output of the wind power plant is remarkably improved.

Description

technical field [0001] The invention relates to the technical field of location selection of wind turbines in wind farms, in particular to a device and method for microscopic location selection of wind turbines based on a binary coded genetic algorithm. Through the measurement of the wind speed and direction of the alternative wind field, the monitoring of the surrounding environment through the camera device, the image data is transmitted to the image processing chip SPCA563A for processing, and then transmitted to the microcontroller for processing to obtain the judgment of the ground roughness; after the anemometer measures The wind speed signal is sent to the microprocessor after A / D conversion. The optimal position of each fan is obtained by using the wake influence model, noise model, fan construction and maintenance cost model as the objective optimization function and binary-based genetic algorithm. Background technique [0002] Wind energy is a new type of clean an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 黄旭张化光朱钰杨珺刘劲松孙秋野王刚吴彦高凯葛延峰
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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