ARIMA-Based Time Series Model of Stochastic Wind Power Generation

• Published in: IEEE transactions on power systems Vol. 25; no. 2; pp. 667 - 676
• Main Authors: Peiyuan Chen, Pedersen, Troels, Bak-Jensen, Birgitte, Zhe Chen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: ARIMA processes; Autoregressive processes; Correlation; Driving; Markov models; Markov processes; Offshore; Power measurement; Power system modeling; Power system planning; Probability distribution; Stochastic processes; Stochasticity; Temporal logic; time series; Wind energy; Wind farms; Wind power; Wind power generation; Wind speed

This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...