Signal Model for the Prediction of Wind Speed In Nigeria

Abstract

Rapid development of wind energy as an alternative source of power is providing rich environment for wind energy related research. Several mathematical models have been used to study wind data and the models are mainly physical and statistical models. In this study, a signal

Modeling approach is developed to predict wind speed data in Nigeria. The signal modeling approach is based on the Markov property, which implies that given the present wind speed state, the future of the system is independent of its past. A Markov process is in a sense the probabilistic analog of causality and can be specified by defining the conditional distribution of the random process.

Key words: wind speed, dynamical system, signal model, Markov chain, ergodicity.