An Optimized Swinging Door Algorithm for Identifying Wind Ramping Events

• Published in: IEEE transactions on sustainable energy Vol. 7; no. 1; pp. 150 - 162
• Main Authors: Cui, Mingjian, Zhang, Jie, Florita, Anthony R., Hodge, Bri-Mathias, Ke, Deping, Sun, Yuanzhang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2016
• Subjects: Algorithms; Approximation algorithms; Doors; Dynamic programming; Economics; Heuristic algorithms; Optimization; Power measurement; POWER TRANSMISSION AND DISTRIBUTION; Ramps; Renewable energy; Renewable energy sources; Segments; sliding window; swinging door algorithm (SDA); WIND ENERGY; Wind power; Wind power generation; wind power ramp events (WPREs); Windows (intervals); wind power ramp events (WPREs); swinging door algorithm (SDA); Dynamic programming; sliding window
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2015.2477244

With the increasing penetration of renewable energy in recent years, wind power ramp events (WPREs) have started affecting the economic and reliable operation of power grids. In this paper, we develop an optimized swinging door algorithm (OpSDA) to improve the state of the art in WPREs detection. The swinging door algorithm (SDA) is utilized to segregate wind power data through a piecewise linear approximation. A dynamic programming algorithm is performed to optimize the segments by: 1)merging adjacent segments with the same ramp changing direction; 2)handling wind power bumps; and 3)postprocessing insignificant-ramps intervals. Measured wind power data from two case studies are utilized to evaluate the performance of the proposed OpSDA. Results show that the OpSDA provides 1)significantly better performance than the SDA and 2)equal-to-better performance compared to the L1-Ramp Detect with Sliding Window (L1-SW) method with significantly less computational time.