Multi-wind-power-plant output scene generation method and system considering space-time correlation

A technology of time-space correlation and space correlation, which is applied in the field of wind power, can solve the problems of low calculation efficiency, insufficient depth of dual angles of time correlation and space correlation, and insufficient fluctuation of multi-wind farm output, so as to improve calculation efficiency, More predictable data, more accurate and reasonable prediction data

Active Publication Date: 2020-09-08
RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The current research mainly simulates correlation variables from different angles. However, the research on the dual perspectives of temporal correlation and spatial correlation is not deep enough. The time correlation angle is simulated separately, and the calculation efficiency is low, which brings certain difficulties to the operation simulation and planning of the power system
In addition, the current research on the output fluctuation of multiple wind farms in the medium and long term is also slightly insufficient.

Method used

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  • Multi-wind-power-plant output scene generation method and system considering space-time correlation
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  • Multi-wind-power-plant output scene generation method and system considering space-time correlation

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Embodiment 1

[0034] Aiming at the problems of single prediction angle and low calculation efficiency in the prior art, this embodiment discloses a flow chart of a method for generating output scenarios of multiple wind farms considering temporal and spatial correlations, as shown in the attached figure 1 As shown, the main steps are:

[0035] (1) Obtain the original output data of multiple wind farms, and classify and count the data at the same time every day in the same week of each year in the original output data of each wind farm;

[0036] (2) For the data classified and counted in step (1), calculate the marginal distribution of the output of each wind farm based on kernel density estimation, and then establish a joint distribution model of the output of multiple wind farms based on the Copula function and the above-mentioned respective marginal distributions;

[0037] Among them, the joint distribution function is the function after connecting the marginal distribution functions by t...

Embodiment 2

[0133] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, one of the first implementation examples is realized. The steps of the generation method of multi-wind farm output scenarios considering the temporal-spatial correlation.

Embodiment 3

[0135] The purpose of this embodiment is to provide a computer-readable storage medium.

[0136] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of a method for generating output scenarios of multiple wind farms considering temporal-spatial correlation in Embodiment 1 are executed.

[0137] Based on the same inventive idea, a multi-wind farm output scenario generation system considering temporal and spatial correlation is disclosed, including:

[0138] The marginal distribution calculation module of the output of wind farms obtains the original output data of multiple wind farms and calculates the marginal distribution of the output of each wind farm;

[0139] The joint distribution function establishment module is based on the Copula function and the above-mentioned respective marginal distributions to establish the joint distribution function of the output of multiple wind farms;

[0140] ...

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Abstract

The invention provides a multi-wind-power-plant output scene generation method considering space-time correlation. The method comprises the steps: obtaining the original output data of a plurality ofwind power plants, and calculating the edge distribution of the output of each wind power plant; based on the Copula function and the edge distribution of the Copula function and the edge distributionof the Copula function, a joint distribution function of multi-wind-power-plant output is established; random sampling is carried out on the joint distribution function to obtain an initial output scene considering the spatial correlation of multiple wind power plants; considering the time correlation in the original output sample of the multiple wind power plants, carrying out the time sequencereconstruction of the initial output scene, and generating the output scene of the multiple wind power plants considering the space-time correlation. According to the method, the time sequence reconstruction technology is adopted to reconstruct the initial scene, more accurate prediction is carried out, the calculation efficiency is improved compared with an existing method, and then more accuratebasic data are provided for operation simulation and planning of a power system.

Description

technical field [0001] The disclosure belongs to the technical field of wind power, and in particular relates to a method and system for generating output scenarios of multiple wind farms considering temporal and spatial correlations. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] With the integration of renewable energy into the grid, the inherent randomness and volatility of renewable energy power generation have an increasing impact on the power system. In order to better provide more accurate basic data for power supply planning, probabilistic power flow, and economic dispatch of the power system, it is necessary to fully consider the time correlation of the output of each wind farm and the relationship between wind farms when predicting wind output. spatial correlation. Therefore, there is a need for a multi-wind farm output multi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02E10/76
Inventor 李雪亮刘晓明袁振华赵龙曹相阳牟颖孙东磊陈博安鹏张丽娜张玉跃付一木田鑫张栋梁孙毅王男薄其滨杨斌刘冬张家宁魏佳杨思高效海魏鑫王轶群程佩芬王宪
Owner RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER
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