The rapid expansion of renewable energy is one of the greatest success stories in the global effort to reduce the carbon dioxide emissions from energy production. After decades of being niche ‘alternative’ energy sources, wind and solar power have firmly reached the mainstream. Together they generated more than a tenth of global electricity for the first time in 2021 (Jones, 2022), and renewables now make up almost all net growth in global power station capacity (IEA, 2021). Focusing specifically on wind power, electricity generation has expanded more than five-fold since 2010, and is expected to more than double again by 2030 (IEA, 2022). This has been largely driven by dramatic cost reductions that have made wind power cost competitive with conventional generation (Jansen et al., 2020). Wind farms now provide the cheapest source of electricity in a dozen countries, including the UK, Brazil and China (BloombergNEF, 2022).
With commercial maturity comes a transition towards research into optimising the design and operation of existing technologies to achieve greater yields, and towards establishing the business case for projects in an ever-greater range of countries and settings. This themed issue of Proceedings of the Institution of Civil Engineers – Energy on wind power reflects these trends, featuring two papers on optimising wind farm operations to improve their predictability, energy yield and system lifetime. It also features two papers that are relevant for sites with low wind speed, which become increasingly attractive as economic viability improves. Finally, it includes two national case studies, evaluating the potential for wind power in two major countries that have yet to see significant uptake.
A challenge for integrating increasing shares of wind energy into power systems is the short-term variability in output. Techniques to improve the skill of short-term forecasting reduce the need for expensive balancing options that must react quickly to shortfalls or surpluses in production. In this issue's first paper, Guo et al. (2022) look at improving the short-term prediction of wind farm output by considering the variation in meteorological variables across the full face of the turbine's blades, rather than at a single height within the swept area. They combine modal decomposition with feature fusion into a machine learning model, finding this yields stable predictive performance against measured data from a wind farm in China. In the second paper, Zhang et al. (2022) provide a solution to a limitation of light detection and ranging (LiDAR) systems. These measure wind speeds at a specific distance away from a turbine's blades and introduce a time delay for processing the incoming data. To represent better the current wind speeds actually hitting the turbine blades at that moment, the paper introduces a novel pre-processing technique with variable time delay, improving turbine control and thus increasing energy yield and reducing maintenance requirements.
Early wind deployment was concentrated in areas with the best wind resource, but as technology costs fall, it becomes economically viable in areas with lower wind resources. In the issue's third paper, Kaplan (2022) assesses the validity of Weibull distributions for representing wind speeds at a low-wind site in Turkey. This method is widely employed at sites with high wind speeds, but its applicability to sites with lower wind resource is under-explored. The paper assesses seven techniques, finding that the moment method is the most accurate. In the fourth paper, Roga et al. (2022) evaluate the ‘perturb and observe’ technique for maximum power point tracking of a vertical-axis wind turbine (VAWT). VAWTs are an alternative to the three-bladed horizontal-axis turbine design that has become ubiquitous around the world, better suited to low-wind sites with gusty conditions, as they can exploit wind coming from any direction simultaneously. Through more accurate maximum power point tracking, the paper demonstrates improved energy yield during turbulent conditions.
The issue's final papers explore the role of wind energy in two country case studies. Vietnam has experienced a rapid boom in solar power (IEA, 2022), but wind energy has not taken off yet, despite the country having one of the largest offshore potentials in Asia (Bosch et al., 2018). Phap et al. (2022) review the history and status of the wind energy sector in Vietnam, and perform a financial appraisal of an offshore wind project. They find favourable returns on investment due to a new feed-in tariff provided by the government. In the sixth paper, ElMaamoun and Xydis (2022) consider the prospects of wind farms at multiple scales in Egypt. They evaluate large offshore projects and small-scale distributed projects attached to industrial sites, finding that the combined potential of both amounts to 40 GW of capacity, and raising the prospect of turning Egypt into a significant energy hub that connects Africa, Europe and the Middle East.
Together, these papers showcase the breadth of research in growing and optimising the potential for wind energy globally, which is an absolute necessity for putting the world on track for limiting the worst effects of climate change.
