Research on short-term wind power volatility characteristics based on high-order Markov chain

Random meteorological variations cause stochastic wind power fluctuations that challenge stable state-transition modeling and grid operation. This paper proposes a probabilistic framework combining high-order Markov chains and Weibull state distributions to characterize short-term volatility. First-order differencing and exponential-similarity-based FCM are used to construct discrete power states with similar fluctuation features. A high-order Markov chain then captures multi-step temporal dependence and cumulative transition behavior, while