Abstract
Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA. Results show that the proposed optimized SDA method provided better performance than the L1-Ramp Detect with Sliding Window (L1-SW) method but with significantly less (almost 1,400 seconds less) computational requirements, and it was also used as a baseline to determine the optimal value of the tunable parameter in the original SDA for ramp detection.
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