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Bastankhah, M., & Porté-Agel, F. (2014). A new analytical model for wind-turbine wakes. Renewable energy, 70, 116-123.

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Article

A Simulation-Based Study at Kenya's Ngong Hills Site, Optimizing Wind Farm Layouts for Cost-Effective Energy Production

1Jomo Kenyatta University of Agriculture and Technology

2MultiMedia University of Kenya


American Journal of Energy Research. 2025, Vol. 13 No. 2, 72-79
DOI: 10.12691/ajer-13-2-3
Copyright © 2025 Science and Education Publishing

Cite this paper:
Omboto J.K, Kamau J.N, Saoke C.O, Wekesa D.W. A Simulation-Based Study at Kenya's Ngong Hills Site, Optimizing Wind Farm Layouts for Cost-Effective Energy Production. American Journal of Energy Research. 2025; 13(2):72-79. doi: 10.12691/ajer-13-2-3.

Correspondence to: Omboto  J.K, Jomo Kenyatta University of Agriculture and Technology. Email: ombotojane04@gmail.com

Abstract

Wind farm design increasingly demands careful balancing of energy yield, wake effects, and economic costs to meet renewable energy targets affordably. This study develops a simulation-based optimization framework tailored to the Ngong Hills wind farm in Kenya. Using a Python-based genetic algorithm paired with the Jensen wake model, we evaluate four layout scenarios: homogeneous layouts of Vestas V52 (850 kW) and NREL 5 MW turbines, as well as mixed configurations combining these or mid-sized Vestas V66 (1.75 MW) and V90 (3.0 MW) turbines, across 800,000 m² site with realistic wind speed and direction distributions. The genetic algorithm optimized turbine placements while enforcing minimum rotor-diameter-based spacing and varying hub heights in the same wind farm to mitigate wake interactions. Results showed that homogeneous V52 and NREL layouts achieved comparable LCOE of $52/MWh, but required trade-offs between the number of turbines and spacing. A hybrid layout mixing V52 and NREL turbines achieved the lowest LCOE of $37/MWh and reduced wake losses by 18.2%, highlighting the value of integrating heterogeneous turbines with staggered hub heights. In contrast, the V66+V90 layout, despite its higher AEP potential, suffered from increased wake interactions and capital costs, leading to an LCOE of $58/MWh. These findings show that a comprehensive economic evaluation, beyond assessing power output alone, proved essential to identifying truly optimal layouts. The mixed V52 + NREL configuration exemplifies how combining high-capacity turbines with densely packed smaller units can mitigate wake effects and minimize LCOE, outperforming homogeneous arrangements. These insights support a strategic layout and turbine design philosophy that considers site-specific wind characteristics, varied turbine types, and cost metrics to create more cost-effective and sustainable wind farms.

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