Determination method and system for wind power state number upper limit in wind power generating algorithm

A technology for wind power and determination methods, applied in calculation, data processing applications, instruments, etc., can solve the problems that the transition between wind power output states does not have Markovian nature, violates the theoretical basis of MCMC method, etc.

Pending Publication Date: 2017-05-31
CHINA ELECTRIC POWER RES INST +2
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  • Abstract
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  • Application Information

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Problems solved by technology

However, too many states will cause the transition between wind power output states to be non-Markovian, which violates the

Method used

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  • Determination method and system for wind power state number upper limit in wind power generating algorithm
  • Determination method and system for wind power state number upper limit in wind power generating algorithm
  • Determination method and system for wind power state number upper limit in wind power generating algorithm

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Embodiment 1

[0048]The invention provides a method for determining the upper limit of the number of wind power states in an MCMC-based wind power generation algorithm. This method first collects and organizes historical wind power output data, and divides them into different numbers of output states, calculates the state transition frequency and state transition probability matrix between the wind power output data points under different numbers of output states, and compares them to Carry out the chi-square test to determine the critical output state number that conforms to the Markov transition characteristic as the upper limit of the divisible output state number. It laid a theoretical foundation for the in-depth study of wind power output time series modeling. Such as figure 1 As shown, the specific implementation steps are as follows:

[0049] Step 1: Collect and organize the historical data of wind power output of wind farms with a time length of 1 year and a time resolution of 15 ...

Embodiment 2

[0073] Based on the same idea, the present invention also provides a system for determining the upper limit of the number of wind power states in the MCMC-based wind power generation algorithm, including:

[0074] Collection module: used to collect and organize the historical data of wind power output of wind farms with a time length of 1 year and a time resolution of 15 minutes;

[0075] Processing module: used to collect and normalize the historical data of wind farms;

[0076] Calculation module: used to determine the Markov transition probability matrix;

[0077] Critical state determination module: determine the critical state of wind power transfer subject to Markov distribution.

[0078] The processing module is further used to: calculate the ratio of the historical wind power output time series of the wind farm station to the data value of the wind power installed capacity at the corresponding time, and obtain the normalized historical wind power output value.

[007...

Embodiment 3

[0084] A specific calculation example is given below, the data used is the data of some wind farms in Jiangsu for one year, the time resolution is 15min, and the number of data points is 35040. Using formula (1) to formula (6) can be calculated as N=112 , it is a critical state.

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Abstract

The invention relates to a determination method and system for a wind power state number upper limit in a wind power generating algorithm based on MCMC. According to the method, first, historical wind power exerting data is collected and sorted out, the data is divided into exerting states in different numbers, a state transition frequency number and a state transition probability matrix of all wind power exerting data points under the exerting states in different numbers are calculated respectively, a chi-square test is performed on the exerting states to determine a critical exerting state number conforming to Markov transition characteristics, and the critical exerting state number serves as a dividable exerting state number upper limit. A theoretical basis is laid for profound research of wind power exerting time sequence modeling. Through the chi-square distribution test method, a maximum wind power state number needing to be divided can be determined, and the precision of a wind power sequence generated through the MCMC method is improved to the maximum extent.

Description

technical field [0001] The invention relates to the technical field of new energy power generation, in particular to a method and system for determining the upper limit of the number of wind power states in an MCMC-based wind power generation algorithm. Background technique [0002] The Markov Chain Monte Carlo (MCMC) method is a simple and practical method for the random generation of wind power output time series. The wind power output random variable generated by this method can meet the transition probability requirements between different defined states, and the MCMC method can make the generated wind power output time series retain the mean value, standard deviation, probability density function (Probability Density Function, PDF) and autocorrelation coefficient (Autocorrelation Function, ACF), so it has a high practical value. [0003] However, the MCMC method can only be used to generate discrete state points. The value of wind power in each state is arbitrary, and ...

Claims

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Application Information

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IPC IPC(8): G06Q50/06
CPCG06Q50/06
Inventor 李驰刘纯黄越辉王跃峰杨硕礼晓飞马烁许晓艳张楠许彦平潘霄锋王晶
Owner CHINA ELECTRIC POWER RES INST
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