A comparison between wind speed distributions derived from the maximum entropy principle and Weibull distribution. Case of study; six regions of Algeria

The knowledge of the probability density function of wind speed is of paramount importance in many applications such as wind energy conversion systems and bridges construction. An accurate determination of the probability distribution of wind speed allows an efficient use of wind energy, thus rendering wind energy conversion system more productive. In the present paper, the maximum entropy principle (MEP) is used to derive a family of pre-exponential distributions in order to fit wind speed distributions. Using averaged hourly wind speed of six different regions in Algeria, it has been found that the proposed pre-exponential distributions fit the wind speed distributions better than the conventional Weibull distributions in terms of root mean square error. However, it has been found also that MEP based distributions have shown some practical limitations such as the choice of pre-exponential order and interval of definition.