Global advocacy for climate change mitigation aims to minimize fossil-derived fuel and support cleaner resources such as wind energy. The stochastic nature of wind makes this particular energy an intermittent source. To overhaul this situation, planning in the form of future predictions can assist in avoiding monetary losses and improving consumer satisfaction by having a backup power supply to meet the ever-rising energy demand. Recently, many predictive machine- and deep-learning models have been designed for wind speed forecasting in various countries and regions, but limited to no such studies are reported for the case of Fiji. Therefore, this Ph.D. research aims to design new hybrid deep-learning models for forecasting wind speed in Fiji to address the research gaps.