Abstract
Wind is one of the most essential sources of clean, environmental friendly, socially constructive, economically beneficial, and renewable energy. To intuit the potential of this energy in a region the accurate wind speed modeling and forecasting are crucially important, even for planning, conversion of wind energy to electricity, energy trading, and reducing instability. However, accurate prediction is difficult due to intermittency and intrinsic complexity in wind speed data. This study aims to suggest a more appropriate model for accurate wind speed forecasting in the Jhimpir, Gharo, and Talhar, regions of Sindh, Pakistan. Therefore, the present study combined the Autoregressive-Autoregressive (ARAR) and Artificial Neural Network (ANN) models to propose a new hybrid ARAR-ANN model for better prediction by precisely capturing different patterns of the wind speed time-series data sets. The proposed hybrid model is efficient in modeling, reducing statistical errors, and forecasting the wind speed effectively. The performance of the proposed hybrid ARAR-ANN model is compared using three error-statistics and Nash-Sutcliffe efficiency-coefficient. The empirical results of the four performance indices fully demonstrated the superiority of the hybrid ARAR-ANN model than persistence model, ARAR, ANN and SVM. Indeed, the proposed model is an effective and feasible approach for wind speed forecasting.
Highlights
Electricity is a great source of economic growth and development in many other sectors of a country, as the household appliances to major industrial processes heavily rely on electricity
Obtaining accurate wind speed predictions become vital for wind farm management and the research work for improving this aspect attracted intensive attention
The ARAR model became popular for the time series data with periodic pattern and the Artificial Neural Network (ANN) has shown much flexibility in modeling the nonlinear data
Summary
Electricity is a great source of economic growth and development in many other sectors of a country, as the household appliances to major industrial processes heavily rely on electricity. The population of the world is rapidly increasing and almost every facility is converted to an electrical mechanism that increased electricity consumption. It is a serious challenge to balance the demand and supply of electricity, especially for developing countries. Almost 68% of electricity is generated from fossil fuels [1]. The use of fossil fuels is harmful to the environment, the greatest threats form human health [2] and become the cause of global warming. It is a predominant alternative source that has been industrialized rapidly over the last two decades all over the world [4]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
