Short-period wind speed prediction method and system based on interval type-2 T-S fuzzy model

A fuzzy model and wind speed prediction technology, which is applied in fuzzy logic-based systems, predictions, data processing applications, etc., can solve problems such as wind power energy instability and uncontrollability

Inactive Publication Date: 2018-05-18
HUAZHONG UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The instability and uncontrollability of wind power energy brin

Method used

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  • Short-period wind speed prediction method and system based on interval type-2 T-S fuzzy model
  • Short-period wind speed prediction method and system based on interval type-2 T-S fuzzy model
  • Short-period wind speed prediction method and system based on interval type-2 T-S fuzzy model

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Embodiment 1

[0082] The embodiment of the present invention provides a short-term wind speed prediction method based on the interval type 2 T-S fuzzy model, such as figure 1 shown, including the following execution steps:

[0083] In step 1, the wind speed observation data is preprocessed, and the original wind speed observation data is decomposed into K intrinsic mode functions (IntrinsicMode Function, abbreviated: IMF) by variational mode decomposition (Variational Mode Decomposition, abbreviated as: VMD) , and for each intrinsic mode function IMF, the input and output matrix (input, output) of the respective T-S fuzzy prediction model is established;

[0084] In step 2, corresponding to each intrinsic mode function IMF, an interval-type T-S fuzzy model is established, where the T-S fuzzy model is a nonlinear system described by a set of "IF-THEN" fuzzy rules, each rule Represents a subsystem, and the entire nonlinear system is a linear combination of each subsystem; the IF-THEN fuzzy ...

Embodiment 2

[0149] The embodiment of the present invention also provides a short-term wind speed prediction system based on the interval type 2 T-S fuzzy model, the system includes a wind speed detector and a server, and the wind speed detector is used to send the wind speed observation data data to the server, specifically:

[0150] The server is used for data preprocessing of wind speed observation data, decomposes the original wind speed observation data into K intrinsic mode functions IMF through variational mode decomposition VMD, and establishes respective T-S for each intrinsic mode function IMF The input and output matrix of the fuzzy prediction model (input, output);

[0151] Corresponding to each intrinsic mode function IMF, an interval-type T-S fuzzy model is established, where the T-S fuzzy model is a nonlinear system described by a set of "IF-THEN" fuzzy rules, and each rule represents a subsystem. The entire nonlinear system is a linear combination of each subsystem; the IF-...

Embodiment 3

[0163] In order to illustrate the effect of the present invention, the wind speed observation data recorded once every 10 minutes on January 5-11, 2014 in the Sotavento wind farm of the Galicia autonomous region in the northwest of Spain will be described in detail as the implementation object of the present invention to the method of the present invention below, There are 1008 pieces of data in total. Moreover, the embodiment of the present invention uses the method to test the accuracy of the model to adapt to the scene, and the specific process is as follows:

[0164] Step 1. Wind speed observation time series data data preprocessing, establish the input and output matrix (input, output) of the T-S fuzzy prediction model:

[0165] Step 1.1, using variational mode decomposition VMD to decompose the wind speed observation time series data data into K=5 intrinsic mode functions IMF, and perform the following steps independently for each IMF;

[0166] Step 1.2, get L=24 interv...

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Abstract

The invention discloses a short-period wind speed prediction method and a system based on an interval type-2 T-S fuzzy model. The method is characterized by carrying out variational modal decomposition VMD on historical real wind speed observation data and decomposing into K modals, carrying out attribute selection and normalization processing on each modal and establishing a predictive fuzzy model; using interval type-2 fuzzy C regression cluster IT2-FCR to carry out structure division on the model, and taking a weighted root mean square error of actual observation wind speed data and a fuzzymodel prediction result as a target function, and using a gravity search algorithm GSA to carry out model front component parameter optimization; and using a least square method to identify a model parameter so as to acquire a short-period wind speed prediction interval type-2 T-S fuzzy model taking the historical real observation data as input. In the invention, a novel type-2 hyperplane membership function is adopted, identification precision of a wind speed fuzzy prediction model can be increased, an accurate identification parameter can be acquired, and a corresponding wind speed prediction result matches with an actual observation wind speed.

Description

technical field [0001] The invention belongs to the technical field of short-term wind speed prediction, and more specifically relates to a short-term wind speed prediction method and system based on an interval-type T-S fuzzy model. Background technique [0002] The depletion of traditional fossil energy, global warming and other issues make the utilization of new clean energy increasingly urgent. Wind power is an energy system with huge reserves, rapid transformation and pollution-free. China's new energy strategy has begun to focus on the development of wind power generation. According to the national plan, in the next 15 years, the national wind power installed capacity will reach 20 million to 30 million kilowatts. The instability and uncontrollability of wind power energy bring severe challenges to the stable utilization of electric energy. An effective wind speed prediction mechanism can provide a reliable basis for wind farm maintenance plans and power system dispa...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N7/02
CPCG06N7/02G06Q10/04G06Q50/06
Inventor 李超顺邹雯甘振豪陈昊赖昕杰
Owner HUAZHONG UNIV OF SCI & TECH
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