Wind power series generation

Does wind power generation time series exhibit persistent low or high velocities?

Not only the wind velocities, but also wind power generation time series exhibit extremely long periods of persistent low or high values. To show this, we analyze aggregated wind power generation time series documented in the renewables.ninja dataset v.1.1 obtained for the period 1980–2016 65, see Fig. 6.

What is a stochastic wind power model?

Abstract: 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.

How is a wind power state series generated?

First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series.

Why is generation of wind power time series important?

Generation of wind power time series is an important foundational task for assisting electric power system planning and making decision.

How are wind power scenarios generated?

The majority of previous wind power scenario generation studies have used statistical methods, which require first building a specific mathematical model to describe the probability distribution of wind power, and then constructing the scenario set by random sampling methods such as Monte Carlo Sampling (MCS) or Latin Hypercube Sampling (LHS).

Which regions favor wind power generation?

We identified regions with high power densities, low seasonal variability, and limited weather fluctuations that favor wind power generation, such as the American Midwest, Australia, the Sahara, Argentina, Central Asia, and Southern Africa.