The transition from fossil fuel to a green economy has led to the rise of renewable energy sources. Wind energy stands out because it is free, clean, inexhaustible, has the capacity to generate greater power, and has lower energy costs. From local to global scales, the environmental effects of wind power are frequently positive, in contrast to the negative impacts associated with fossil fuel technologies. These include air pollution, climate change, health risks, high mortality rates, especially in infants, and greenhouse gas emissions. However, all energy sources have an impact on the environment and the economy including wind energy. With the rapid growth of wind energy over the last decade and the future potential of wind power generation, strategic assessment of these environmental and economic impacts, both positive and negative, and developing ways to mitigate these negative impacts are prerequisite operations to be carried out in the overall development of human-, economically- and ecologically-friendly wind energy.

The global population is moving away from fossil fuel technologies due to their many disadvantages, such as air pollution, greenhouse gases emission, global warming, acid rain, health problems, and high costs. These disadvantages make fossil fuels unsustainable. As a result, renewable energy is becoming more attractive due to its steadily decreasing costs. Harnessing renewable energy promises to meet the present energy demands of the African continent. The enormous renewable energy potential available across the African continent remains largely untapped, especially for wind energy. However, marginal and fair wind speeds and power densities characterize African wind energy resulting in low and unsustainable power in many areas. This research develops a techno-economic model for wind energy cost analysis for a novel, Ferris wheel-based wind turbine. The model is used to techno-economically analyze the siting of wind turbine sites in low wind speed areas on the African continent. The wind turbine’s technical performance is characterized by calculating the annual energy production and the capacity factor using the wind Weibull probability distribution of the cities and theoretical power curve of the wind turbine. Its economic performance is evaluated using annualized financial return on investment, simple payback period, and levelized cost of electricity. The techno-economic model is validated for 21 African cities and shows that the Ferris wheel-based design is very competitive with four current, commercial wind turbines, as well as with other sources of energy. Hence, the new wind turbine may help provide the economical, clean, renewable energy that Africa needs.

This paper posits that a low-speed wind turbine design is suitable for harnessing wind energy in Africa. Conventional wind turbines consisting of propeller designs are commonly used across the world. A major hurdle to utilizing wind energy in Africa is that conventional commercial wind turbines are designed to operate at wind speeds greater than those prevalent in most of the continent, especially in sub-Sahara Africa (SSA). They are heavy and expensive to purchase, install, and maintain. As a result, only a few countries in Africa have been able to include wind energy in their energy mix. In this paper, the feasibility of a novel low-speed wind turbine based on a Ferris wheel is demonstrated for low wind speed applications in Africa. The performance of Ferris wheel wind turbines (FWT) with 61 m (200 ft), 73 m (240 ft) and 104 m (341 ft) diameter rims and an 800 kW generator are evaluated for selected African cities. The research also compares the Weibull wind distribution of the African cities of interest. A comparison between the FWT and the conventional commercial wind turbines in terms of efficiency, rated wind speed, cost, performance, and power to weight is included. Results show that the FWT has the potential for economic power generation at rated wind speeds of 6.74 m/s, which are lower than the average of 12 m/s for conventional wind turbines and have lower power to weight ratios of 5.2 kW/tonne as compared to 6.0–9.2 kW/tonne for conventional wind turbines.

The design and development of wind turbines in low-wind-speed areas involves several technical and financial challenges related to maximizing conversion efficiency and minimizing cost. Unfortunately, much of the African continent is dominated by low-wind-speed resources. In this study, a multi-parameter optimization method is used to explore the design of a novel Ferris wheel wind turbine (FWT) technology, which has an 800-kW generation capability. We used the tip speed ratio, lift-to-drag ratio and power coefficient to determine the optimal efficiency by varying the number of blades and rim diameters. The capital cost estimates, as affected by rim diameter and the number of blades, are presented. This paper studies FWTs at their rated wind speeds because wind turbines have their maximum performance at the rated wind speeds, and this allows one to observe the effects of changing the rim diameter and the number of blades without the need to consider the location of the turbine. The results show that reducing the number of spokes by half (from 64 to 32) on the four rim diameters studied decreases the efficiency by less than 0.19%, while reducing the acquisition cost by 42%, installation cost by 42% and mass by 28%. Reducing the number of spokes to a quarter (i.e., from 32 to 16) decreases the efficiency by less than 0.31%, reduces the acquisition and installation costs by 36% and 35.5%, respectively, and the mass by 19.2%, of the four rim diameters studied. The reduction of the number of blades has a significant effect on the efficiency and capital cost with varying rim diameters. This paper shows the potential for Ferris-wheel-based wind turbines for low-wind-speed conditions, such as those that prevail in parts of Africa.

Nigeria’s urban areas continue to face unreliable electricity supply, rising demand, and dependence on costly, polluting petrol and diesel generators. Hybrid renewable energy systems (HRES) — integrating solar, wind, and battery technologies — offer a viable pathway to provide clean, decentralized, and resilient power. This review critically examines the policy, institutional, and governance factors shaping HRES deployment in urban Nigeria, identifying the key barriers and reforms required to scale adoption. Findings reveal that expansion is constrained by fragmented regulation, weak institutional coordination, limited access to affordable finance, and fossil-fuel subsidies that distort energy prices and discourage renewable investment. Institutional overlap among the relevant agencies further constrains implementation. Technical barriers, such as limited local expertise, high component import costs, and poor grid integration, further elevate project risks and reduce system reliability. The study recommends regulatory harmonization under the new Electricity Act (2023), implementation of performance-based fiscal incentives, and expansion of green financing mechanisms to lower investment risk. Strengthening local manufacturing, research and development, and workforce capacity will be essential to reduce dependence on imports and sustain long-term growth. Finally, promoting gender equity, community participation, and inclusive business models can enhance social acceptance and promote fair distribution of the benefits associated with HRES across all urban populations. Collectively, these measures can accelerate Nigeria’s transition toward a cleaner, more reliable, and climate-resilient urban energy future.

Previous studies on wind turbine and wind farm optimization for Levellized cost of energy (LCOE) and annual energy production (AEP) have focused on horizontal axis wind turbines (HAWT) and vertical axis wind turbines (VAWT). Regions with lower wind speed resources tend to have a higher levellized cost of energy and lower annual energy production. In this paper, the authors investigate the optimization of a novel, Ferris wheel wind turbine (FWT) for low wind speed regions of Africa. The research used an Excel‐based Multi‐Objective Optimization (EMOO) model. The EMOO program has both binary‐coded and real‐coded Elitist Non‐Dominated Sorting Genetic Algorithm (NSGA‐II). The optimization is conducted by studying the effect of varying the rim diameter, number of blades, and the rated wind speeds for an 800‐kW generator on the performance and economics in 21 African cities. The results show that, on average, the return‐on‐investment increases over the base design by up to 182%, and both the simple payback period (SPP) and the levellized cost of electricity decreased by 39% as the rim diameter increases combined with a 50% reduction in blade numbers. In addition, a 75% reduction in blade numbers caused a further 32% decrease on average for both the simple payback period and the levellized cost of electricity.