Comparative study of chaotic features in hourly wind speed using recurrence quantification analysis

Due to the shortage in electricity supply in Nigeria, there is a need to improve the alternative power generation from wind energy by analysing the wind speed data available in some parts of the country, for a better understanding of its underlying dynamics for the purpose of good prediction and modelling. The wind speed data used in this study were collected over a period of two years by National Space Research and Development Agency (NASRDA) from five different stations in the tropics namely; Abuja (7(0)50'02.09N and 6(0)04'29.97E), Akungba (6(0)59'05.40N and 5(0)35'52.23E), Nsukka (6(0)51'28.14N and 7(0)24'28.15E), Port Harcourt (4(0)47'05.41N and 6(0)59'30.62E), and Yola (9(0)17'33.58N and 12(0)23'26.69E). In this paper, recurrence plot (RP) and recurrence quantification analysis (RQA) are applied to investigate a non-linear deterministic dynamical process and non-stationarity in hourly wind speed data from the study areas. Using RQA for each month of the two years, it is observed that wind speed data for the wet months exhibit higher chaoticity than that of the dry months for all the stations, due to strong and weak monsoonal effect during the wet and dry seasons respectively. The results show that recurrence techniques are able to identify areas and periods for which the harvest of wind energy for power generation is good (high predictability) and poor (low predictability) in the study areas. This work also validates the RQA measures (L-max, DET and ENT) used and establishes that they are similar/related as they give similar results for the dynamical characterization of the wind speed data. (c) 2018 Author(s).