Abstract
The wind power ramp event includes large fluctuations in wind power within a short period of time. To maintain grid stability, defining, identifying, and predicting the wind power ramp event is inevitable. Therefore, a comprehensive assessment method of wind power ramp events that combines the generalized information of the source, grid, and load sides is proposed. In this method, we put forward a channel self-selected multi-layer coefficient correction model (CSMCC) and wind power ramp threshold, according to the allowable value of a grid frequency change. Additionally, the availability of data-driven modeling methods is verified by performing autocorrelation analysis. Finally, the comprehensive evaluation method, which combines the back propagation (BP) neural network, supports the vector machine and CSMCC model is proved to be effective. This paper has a certain reference significance for basic research on large-scale wind power safety and efficient utilization.
Highlights
In China, renewable energy has developed rapidly in recent years
This paper studies the comprehensive evaluation method of wind power ramp events combined with
This paper studies the comprehensive evaluation method of wind power ramp events combined with generalized source-grid-load information, and the conclusions are as follows
Summary
In China, renewable energy has developed rapidly in recent years. According to statistics from the National Energy Administration, installed wind power capacity and photovoltaic power capacity increased by 12.4% and 34%, respectively, year-on-year in 2018. The wind power ramp event has been one of the research focuses in the field of wind power for a long time [4,5]. There are four existing definition methods (as shown in Table 1) were introduced in literature [12], and pointed out that their key and common point is the time interval and threshold selection of wind power change, which affect the effective identification of ramp events. Each of these four definition methods has advantages and disadvantages [12]
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