Estimating the Probability of Wind Ramping Events: A Data-driven Approach
Cheng Wang, Wei Wei, Jianhui Wang, Feng Qiu
TL;DR
This paper introduces a data-driven approach to estimate the likelihood of wind ramping events, avoiding the need for detailed probability distribution functions, and validates it with real wind data.
Contribution
It presents a novel method for wind ramping probability estimation that does not rely on explicit PDF modeling, validated with actual wind data.
Findings
Effective estimation of wind ramping probabilities using real data.
Avoids complex PDF modeling for wind power analysis.
Validated approach with empirical wind data.
Abstract
This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.
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Taxonomy
TopicsEnergy Load and Power Forecasting · Wind Energy Research and Development · Electric Power System Optimization