Simulation of Wind Speeds with Spatio-Temporal Correlation

Abstract

Nowadays, there is a growing trend to incorporate renewables in electrical power systems and, in particular, wind energy, which has become an important primary source in the electricity mix of many countries, where wind farms have been proliferating in recent years. This circumstance makes it particularly interesting to understand wind behavior because generated power depends on it. In this paper, a method is proposed to synthetically generate sequences of wind speed values satisfying two important constraints. The first consists of fitting the given statistical distributions, as the generally accepted fact is assumed that the measured wind speed in a location follows a certain distribution. The second consists of imposing spatial and temporal correlations among the simulated wind speed sequences. The method was successfully checked under different scenarios, depending on variables, such as the number of locations, the duration of the data collection period or the size of the simulated series, and the results were of high accuracy.

Comparative Study between Flatness-Based and Field-Oriented Control Methods of a Grid-Connected Wind Energy Conversion System

“…Wind energy is an alternative to meet the growing energy demand and to protect the environment [1]. The Global Wind Energy Council has reported a global capacity of 651 GW with 60.4 GW of new installations in 2019 and an expectation of growth of more than 100 GW in annual installations over the next decade [2,3].…”