Piecewise linear approximation for identifying wind power ramp events

WPREs (wind power ramp events) are one of the most critical factors affecting the security and protection of the electrical system. Accurate ramp event detection may help power systems better manage extreme events and reduce financial damage. In this study, We present an improved piecewise linear approximation for recognizing wind ramps in Kanyakumari district. In practise, wind power ramps can be decreased by properly managing and dispatching flexible reserve and associated services. This necessitates the use of proper ramp detection techniques as well as precise ramp forecasts. The method's plan to break down wind power signal into increasing with increasing ramps, making ramp identification easier and ensuring that all conceivable ramps of varying lengths are identified. Using observed wind power data, the ramp detection method is used to assess the performance of an energy wind farm. The results reveal that identifying wind power ramps using the segmentation method is equivalent to optical ramp identification.

Automated summary

WPRE is one of the most critical factors affecting the security of the electrical system. Accurate detection of ramp events can help manage extreme events and reduce financial damage. This study presents an improved method for recognizing wind power ramps in Kanyakumari district, which can effectively identify ramps of varying lengths and assess the performance of an energy wind farm.