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A Probabilistic Modeling Method of Renewable Energy Output Power Based on Orthogonal Series

A technology of renewable energy and output power, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as time-consuming and complex calculations, and achieve small differences, high fitting accuracy, and strong stability Effect

Active Publication Date: 2019-03-01
SOUTHEAST UNIV +3
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Problems solved by technology

A common non-parametric estimation is kernel density estimation, but this method needs to calculate the bandwidth value, which is complicated and time-consuming

Method used

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  • A Probabilistic Modeling Method of Renewable Energy Output Power Based on Orthogonal Series
  • A Probabilistic Modeling Method of Renewable Energy Output Power Based on Orthogonal Series
  • A Probabilistic Modeling Method of Renewable Energy Output Power Based on Orthogonal Series

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Embodiment Construction

[0050] The technical solution of the present invention will be further introduced below in combination with specific embodiments.

[0051] The invention discloses a probabilistic modeling method for output power of renewable energy sources based on orthogonal series. The invention will be further described below by taking a photovoltaic power supply as an example and combining with the accompanying drawings.

[0052]S1: Select a typical quarter in Nanchang, Jiangxi Province (sampling interval is 10min) and a half-year photovoltaic power source measurement data in an area in Jiaxing, Zhejiang Province (sampling interval is 5min) for simulation analysis. The random variable p=(P-Pmin) / (Pmax-Pmin) can be obtained by projecting the power P onto the interval [0, 1]. Divide the obtained data into training data and test data. Then, choose an orthonormal basis. Common basis functions include Hermite basis, Laguerre basis, and cosine basis. The choice of base mainly depends on the d...

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Abstract

The invention discloses a renewable energy output power probability modeling method based on orthogonal series. The method includes the following steps of S1, obtaining a renewable energy output power value through a monitoring system, and selecting a group of standard orthogonal bases to write a function in the form of the orthogonal series; S2, selecting a shrinkage coefficient for the orthogonal series form in the step S1 through a trimming estimator method, minimizing the deviation and variance of a risk function and a balance function to obtain a cut-off point, and finally determining a probability density function; S3, judging whether the probability density function can reflect the true distribution of renewable energy output power or not through test of goodness of fit. The selection of a bandwidth value does not need to be considered, the model calculation process is simple, and the calculation speed is higher; compared with the prior art, the difference of model output value and actual-measurement data is the smallest. Meanwhile, the method is not restrained by time and space conditions and has the advantages of being high in fitting precision, stability and applicability.

Description

technical field [0001] The invention relates to new energy technologies, in particular to a probabilistic modeling method for output power of renewable energy sources based on orthogonal series. Background technique [0002] With the growth of renewable energy demand, photovoltaic power generation accounts for an increasing proportion of installed capacity in the power system, and its impact on power system planning, simulation, dispatch and control has also attracted great attention. The output power of renewable energy, such as photovoltaic and wind power, has random characteristics, and its probability distribution characteristics have important guiding significance for the planning, operation and reliability analysis of distributed power. [0003] At present, the analysis of the characteristics of the output power probability is mainly divided into two categories, namely, parametric analysis methods and non-parametric analysis methods. The parametric analysis method nee...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50
CPCG06F30/367Y02E60/00
Inventor 吴在军徐怡悦王洋窦晓波胡敏强
Owner SOUTHEAST UNIV
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