Modeling wind speed using probability distribution function, Markov and ARMA models

Power utilities' demand for renewable energy resources is increasing, but the complexities of integrating conventional and renewable resources into the active networked distribution system can be prohibitive. Wind power is the most popular renewable resource worldwide due to its efficiency and cost. Effective planning of wind power integration requires accurate wind speed modeling. However, achieving this accuracy is challenging. New research is needed to determine the most accurate modeling method for wind power. In this paper, probability distribution function (pdf), Markov chain and Auto-Regressive Moving Average (ARMA) are evaluated for accuracy in modeling to forecast short- and long-term wind speed and power, and the ease of integrating wind power into the system.