Robust optimization scheduling method considering wind power multivariate correlation ellipsoid set

A technology of wind power and scheduling method, applied in wind power generation, electrical components, circuit devices, etc., can solve the problems of no judgment standard and weak correlation

Active Publication Date: 2020-08-28
DALI POWER SUPPLY BUREAU YUNNAN POWER GRID
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Problems solved by technology

However, the time correlation of forecast error is only significant within a limited time scale, and the time correlatio...

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  • Robust optimization scheduling method considering wind power multivariate correlation ellipsoid set
  • Robust optimization scheduling method considering wind power multivariate correlation ellipsoid set
  • Robust optimization scheduling method considering wind power multivariate correlation ellipsoid set

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Embodiment Construction

[0070] The present invention will be further described below in conjunction with the accompanying drawings.

[0071] The present invention considers the robust optimal scheduling method of multivariate correlation ellipsoid set of wind power, based on a Gaussian Copula model that simultaneously considers the time correlation of prediction error and the correlation between the prediction value and the prediction error condition, and proposes that only those with strong correlation Multiple ellipsoidal uncertain ensemble optimization methods for finite time scales. This set embodies multiple strong correlations, and can remove a large number of extremely low-probability scenarios in robust scheduling, thereby reducing the degree of conservatism. The specific implementation process is as follows:

[0072] Step 1: Obtain the marginal probability distribution of the real value and predicted value of wind power according to the historical data of the wind farm.

[0073] The Copula...

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Abstract

The invention discloses a robust optimization scheduling method considering a wind power multivariate correlation ellipsoid set. The method comprises the steps of obtaining edge probability distribution of a wind power true value and a wind power prediction value according to historical data of a wind power plant; initializing a cyclic variable; calculating a covariance matrix; calculating parameters of multivariate normal condition distribution; sampling the condition distribution to obtain an actual value sample; constructing a multi-ellipsoid set; calculating a multi-ellipsoid integrity index and a high-efficiency index with the dimension TR of historical data on the dth day; traversing all dates, and calculating comprehensive indexes; traversing all TR to obtain an optimal correlationtime scale; constructing a multi-dimensional ellipsoid uncertainty set according to the latest day-ahead prediction value; and based on the multi-dimensional ellipsoid uncertainty set, constructing amicrogrid two-stage robust scheduling model, and finding an economic optimal scheduling scheme in the worst uncertainty scene. The method is used for solving the uncertainty of wind power in a microgrid, improving the economy of a robust scheduling scheme and reducing unbalanced power.

Description

technical field [0001] The present invention relates to an optimal scheduling method, more specifically, relates to a robust optimal scheduling method considering wind power multiple correlation ellipsoid sets. Background technique [0002] With the depletion of fossil fuels and increasing environmental pollution, renewable energy such as wind power has played an increasingly important role, accounting for an increasing proportion of power system energy supply. However, the inherent randomness and volatility of renewable energy sources such as wind power pose challenges to power system scheduling. When optimizing scheduling, it is necessary to consider the possible impact of this randomness in order to achieve the economy and stability of scheduling. [0003] Robust optimal scheduling considers that random variables fluctuate within the range of an uncertain set, and the obtained solutions can resist the interference of this uncertainty. Robust optimization can deal with t...

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Application Information

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IPC IPC(8): H02J3/00H02J3/38G06Q10/04G06Q50/06
CPCH02J3/004H02J3/0075H02J3/381G06Q10/04G06Q50/06H02J2203/20H02J2300/28Y02E10/76
Inventor 张成杜文佳董庆九
Owner DALI POWER SUPPLY BUREAU YUNNAN POWER GRID
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