Artificial Neural Network-Based Forecasting and Control of Small Wind Turbines in Tobruk, Libya

This paper consolidates datasets, aerodynamic modeling, control strategies and machine-learning forecasting approaches applied to a 20kW wind turbine sited for Tobruk, Libya. Using synthetic hourly meteorological data (8760 hours) and published regional wind analyses, we compare a baseline fixed-Cp model against an enhanced dynamic Cp(λ, β) model with active pitch control and ANN-informed forecasting. We present the mathematical models, simulation framework, performance metrics, sensitivity and economic analyses, and policy recommendations. The enhanced model yields a substantial a 52.5% increase in annual energy production (AEP) and improved forecast accuracy; limitations and recommendations for field validation and economic assessment are discussed.