Single-wind-field wind power output simulation method based on data mining

A wind power output and data mining technology, which is applied in the direction of electrical digital data processing, CAD numerical modeling, special data processing applications, etc., can solve the problems of not considering the characteristics of wind speed distribution, gaps, wind speed distribution and timing characteristics, etc. Achieve high flexibility, convenience, and high fit

Pending Publication Date: 2022-05-17
国网山西省电力公司经济技术研究院
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AI Technical Summary

Problems solved by technology

[0003] 1. Ultra-short-term wind power forecasting based on wind power forecasting methods, such as gray models, can only be done in the ultra-short term, and cannot take into account the distribution and timing characteristics of wind speed;
[0004] 2. Using random sampling in the Weibull distribution to obtain wind speed data can satisfy the distribution characteristics of wind speed, but lacks timing considerations, and the characteristic parameters of the Weibull distribution of

Method used

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  • Single-wind-field wind power output simulation method based on data mining
  • Single-wind-field wind power output simulation method based on data mining
  • Single-wind-field wind power output simulation method based on data mining

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Embodiment 1

[0027] A method for simulating wind power output of a single wind field based on data mining, comprising the following steps:

[0028] Step 1. Obtain raw data: Obtain historical output data of a single wind farm;

[0029] Step 2. Missing value filling and abnormal value repairing: fill in missing data values, and repair negative values ​​and outliers to obtain valid wind power output data;

[0030] Step 3. Establish a processing model for converting wind power output into wind speed, and convert wind power output data into wind speed data;

[0031] Step 4, using data mining methods to obtain information such as cut-in wind speed, cut-out wind speed, and rated power;

[0032] Step 5. Establish a preliminary model based on the Weibull distribution characteristics of the wind speed and the stochastic difference equation, and obtain the K and C values ​​of the Weibull distribution and the parameter θ value in the stochastic difference equation;

[0033] Step 6. Based on the K, C...

Embodiment 2

[0041] see Figure 1~3 , a single wind farm wind power output simulation method based on data mining, including the following steps:

[0042] Step 1: Obtain raw data: Obtain the historical output data of a single wind farm, generally three to five years old, from dispatching or wind power plants.

[0043] Step 2: Missing value filling and abnormal value repairing: Carry out missing value filling, negative value and outlier repair on the data to obtain effective wind power output data. Wind turbines have their corresponding parameters, such as rated output, maximum output, etc. The measured wind power output data should be within the range of minimum output and maximum output, that is, 0≤P t ≤P max (P max is the maximum output of the wind farm). falls in the [0,P max ] are identified as abnormal data, and the abnormal data are replaced with the same method as the missing value filling.

[0044] Specifically, x d,t Indicates the output of d∈D day t∈T time, let d j ∈ Dtht...

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Abstract

The invention discloses a single-wind-field wind power output simulation method based on data mining. The method comprises the following steps: acquiring original data; filling missing values and repairing abnormal values; establishing a processing model for converting wind power output into wind speed; acquiring information such as cut-in wind speed, cut-out wind speed and rated power by using a data mining method; establishing a preliminary model based on Weibull distribution characteristics of wind speed and a random difference equation, and calculating to obtain K and C values of Weibull distribution and a parameter theta value in the random difference equation; based on the K, C and theta values in the step 5, generating future wind speed data in a time sequence by using a random difference equation model; and converting the generated wind speed data into wind power output data. The method has the beneficial effects that the output characteristics of the wind field and the fan estimation parameters are obtained only according to the historical data of the single wind field through a data mining method, so that future wind field output simulation is carried out, the time sequence and the distribution characteristics of the wind speed are considered at the same time, a user does not need to configure excessive extra parameters, and the method is suitable for practical engineering application.

Description

technical field [0001] The invention relates to a method for simulating wind power output, in particular to a method for simulating wind power output of a single wind farm based on data mining, and belongs to the technical field of power system planning. Background technique [0002] At present, the simulation of wind farm output is mainly divided into the following categories: [0003] 1. Ultra-short-term wind power forecasting based on wind power forecasting methods and forecasting models such as gray models can only do ultra-short-term forecasting, and cannot take into account the distribution and timing characteristics of wind speed; [0004] 2. Using random sampling in the Weibull distribution to obtain wind speed data can satisfy the distribution characteristics of wind speed, but lacks timing considerations, and the characteristic parameters of the Weibull distribution of the wind field must be known in advance; [0005] 3. Based on the time series ARIMA model method...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F17/12G06F111/10G06F113/06
CPCG06F30/20G06F17/12G06F2111/10G06F2113/06
Inventor 李旭霞王尧胡迎迎王鹏王志刚
Owner 国网山西省电力公司经济技术研究院
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