Multi-layer collaborative real-time classification early warning method for wind power climbing event

A wind power and event technology, which is applied in the field of multi-layer collaborative real-time classification and early warning of wind power power ramp events, can solve problems such as loss of ramp information and low probability of correct prediction of ramp events.

Active Publication Date: 2020-12-11
HEFEI UNIV OF TECH
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Problems solved by technology

The most widely used method is the indirect prediction method, which is to identify slope events based on wind power prediction information. However, in order to improve the overall prediction accuracy in

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  • Multi-layer collaborative real-time classification early warning method for wind power climbing event
  • Multi-layer collaborative real-time classification early warning method for wind power climbing event
  • Multi-layer collaborative real-time classification early warning method for wind power climbing event

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Embodiment Construction

[0055] The technical solution of this patent will be further described in detail below in conjunction with specific implementation cases.

[0056] Such as figure 1 As shown, a multi-layer collaborative real-time classification and early warning method for wind power ramp events includes the following steps:

[0057] S1) Obtain the historical data of wind power time series for preprocessing, and obtain the preprocessed wind power time series, denoted as {Y(t)} t＝1,2,...,T , Y(t) is the wind power at time t, and T is the total number of samples;

[0058] S2) Formulate a classification strategy for wind power ramp events:

[0059] S2.1) Take the wind power sequence {Y(t+m)} of M time points in the future after time point t m＝1,2,...,M As a basis, formula (1) is used to establish the wind power climbing trend factor R at time t t :

[0060]

[0061] In formula (1), Y(t+m) is the wind power at the mth time point in the future after time point t; sign(.) is a sign function a...

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Abstract

The invention discloses a multi-layer cooperative real-time classification early warning method for a wind power climbing event. The method comprises the following steps: 1, obtaining wind power historical data for preprocessing; 2, formulating a wind power climbing event classification strategy; 3, establishing a multi-layer collaborative prediction model of a decomposition layer, a prediction layer, a correction layer and a feedback layer; and 4, identifying different types of wind power climbing events to carry out real-time early warning. According to the method, EMD decomposition, GRU prediction, SVR correction and multi-step rolling prediction of actual measurement information feedback are utilized, real-time early warning is carried out after different types of wind power climbing events are recognized according to the wind power climbing event classification criterion, corresponding measures can be taken in time before the climbing events happen, and therefore safe and stable operation of a power system is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of power system prediction and control, and in particular relates to a multi-layer collaborative real-time classification and early warning method for wind power power ramp events. Background technique [0002] In order to cope with the shortage of traditional fossil energy and severe environmental problems around the world, the proportion of new energy connected to the grid is increasing. Wind energy, as one of the green and clean renewable energy sources, has been rapidly developed and widely used around the world. With the increase of wind power penetration rate, affected by extreme weather, the wind power power changes greatly in a short period of time, and wind power power climbing events are very likely to occur, resulting in a large shortage of power in a short period of time in the system, affecting peak regulation and frequency regulation, resulting in Mass load loss. Therefore, accurate predictio...

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Application Information

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IPC IPC(8): G06K9/62G06N3/08G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06G06N3/08G06F18/24
Inventor 何耀耀王云肖经凌张婉莹陈悦
Owner HEFEI UNIV OF TECH
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