<![CDATA[This study presents a rigorous assessment of wind energy potential in Gorontalo Regency, Indonesia, through statistical modeling utilizing the two-parameter Weibull distribution applied to hourly wind speed data from 2022 to 2024 across three geographic zones and three elevation levels (50 m, 80 m, 100 m). The model exhibited strong statistical agreement with observed data, evidenced by high variation (R² > 0.9869) and low RMSE values (< 0.011), confirming its robustness in capturing wind behavior. Mean wind speeds, along with key Weibull-derived metrics—most probable wind speed (vmp) and wind speed for maximum energy contribution (vme)—showed a positive correlation with altitude, where zone 1 recorded the highest vme at 7.45 m/s at 100 m. Derived power density values indicated that Zones 1 and 3 fall within the "acceptable" classification (130.52 W/m² and 115.58 W/m², respectively), validating their technical viability. Simulated performance of the Goldwind GW 140/3.4 wind turbine revealed that Zone 1 yielded the highest annual energy output (Eout) of 10.34 GWh with a corresponding capacity factor (Cf) of 11.56%, followed by zones 3 and 2, which, while exhibiting lower outputs, maintained operational feasibility for decentralized small-to-medium scale deployment. Wind rose analysis confirmed predominant southeast and southern wind flows across all zones, offering critical input for optimizing turbine orientation. Collectively, the findings substantiate that zones 1 and 3 present favorable wind regimes for sustainable wind energy development, offering a data-driven foundation for future investment and regional energy planning.]]>
Copyrights © 2025
