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Improved versatile distribution and versatile mixture distribution models characterizing wind power probability distribution

A mixed distribution and general distribution technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as inability to handle random power flow problems

Active Publication Date: 2016-09-07
武汉龙德控制科技有限公司
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, this method has obvious defects, that is, it cannot deal with the random power flow problem caused by multiple wind farms connected to the system at different points

Method used

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  • Improved versatile distribution and versatile mixture distribution models characterizing wind power probability distribution
  • Improved versatile distribution and versatile mixture distribution models characterizing wind power probability distribution
  • Improved versatile distribution and versatile mixture distribution models characterizing wind power probability distribution

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specific Embodiment approach

[0083] The specific implementation method is: observe the distribution of the predicted value and the measured negative error data. Taking the Irish wind farm with more small data as an example, because the small data is large and the data is small, it can be analyzed from 1p.u. to 0p.u. box. Determine the lower boundary of the box where the predicted value 1p.u. is located, so that the number of data groups contained in this box reaches the amount A that can meet the fitting requirements (see later); after determining the lower boundary of the last box, it is used as the next box The upper bound of , repeat the method just now, until 0p.u. Renumber the predicted values ​​of the obtained M1 prediction boxes from small to large, and record them as 1...i...M1 boxes.

[0084] The following uses an actual wind farm data binning example to illustrate the improved general distribution and the binning method and advantages and disadvantages of the general distribution. For the conv...

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Abstract

The present invention discloses improved versatile distribution and versatile mixture distribution models characterizing wind power probability distribution. By selecting an appropriate shape parameter and order, a versatile mixture distribution model is capable of fitting wind power distribution or error distribution in any shape under a precision requirement. A CDF of a distribution function of the model has a closed analytic expression, and an inverse function of the CDF is an implicit function expression, which is applicable to economic dispatch in a wind power integrated system. Compared with fitting performed on actual wind power distribution of an actual wind farm by a Gaussian mixture distribution model, an advantage of a probability distribution model is verified. The method has great promotion value and an excellent application prospect.

Description

technical field [0001] The invention belongs to the field of power system operation and control, and relates to an improved general distribution and general mixed distribution model representing the probability distribution of wind power. Background technique [0002] In the first half of 2015, China's new grid-connected capacity of wind power was 9.16 million kilowatts. By the end of June, the cumulative grid-connected capacity of wind power in the country was 105.53 million kilowatts, ranking first in the world. Global wind power generation capacity reached 432.42 million kilowatts at the end of 2015, an increase of 17% from the end of 2014, surpassing nuclear power generation for the first time. With the large-scale access of wind power to the power system, the randomness and volatility of wind power have brought unprecedented challenges to the safe operation and scheduling control of the power grid. basic question. [0003] For the randomness of wind power, the classic...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 徐箭唐程辉孙元章刘继曹慧秋江海燕洪敏周过海
Owner 武汉龙德控制科技有限公司
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