Successful transition to net-zero emissions electricity systems relies primarily on the use of renewable or zero-carbon sources. The 2020 share of electricity generated from renewables was globally around one-quarter of the total generation, with hydropower being the largest contributor and wind and solar being the fastest growing. The continuous fall in costs of solar and wind technologies along with ambitious climate policies in the EU, the USA, China, and India, among others, contributed to raise renewable capacities and power generation. However, meeting targets of net-zero emissions electricity systems, typically by midcentury, will require substantial solar and wind capacity additions, whose share currently totals less than 10% of the worldwide electricity generation.
I aim to facilitate large-scale integration of renewable energy generation in future net-zero emissions energy systems and identify geophysical constraints and unintended consequences if deployed at scale. My research is motivated by the need to provide sustainable solutions to energy systems and the human communities that rely on them in an era of global environmental change and rapid growth of energy consumption. I draw on extensive experience studying the physics of fluids and the dynamics of energy systems to develop innovative solutions to better understand and build the next generation of renewable energy harvesting technologies.
Large-scale integration of wind and solar generation for decarbonized electricity systems (2020-present)
Renewable resources, such as wind and solar, are highly variable in space and time and not always available when needed to meet electricity demand. Although wind and solar resources have some degree of complementarity that helps mitigate and smooth their variability, reliable power systems mostly based on variable energy sources require effective grid management, backup power systems, and energy storage capacity. I am investigating strategies for optimal and long-term planning of distributed wind generation in increasingly decarbonized electricity systems. I am using use a macro energy system model to reveal and disentangle system-level relationships and characteristics of optimal siting of distributed wind and solar generation in a decarbonized electricity system.
Understanding limits to wind power generation at regional scale (2019-2021)
This research project aimed at understanding the physics of wind power extraction for regional-scale wind farms and which physical parameters control their power extraction. The geophysical limit to maximum power density of large wind farms (regional scale) is related to the rate of replenishment of kinetic energy removed from the atmosphere by wind turbines. By means of both numerical atmospheric simulations and analytic expressions, I unmasked how atmospheric pressure gradients and the latitude-dependent Coriolis parameter control the power density of large-scale wind farms (Antonini et al. 2021a). I also identified the length scale at which a wind farm reaches its generation limits. This analysis provides a better understanding and a physical explanation to the scalability of wind farms and defines spatial constraints in large scale expansion of wind power plants (Antonini et al. 2021b).
Optimizing wind farm layouts using computational fluid dynamical models and adjoint methods (2014-2019)
During my PhD program, I conducted research on computational modeling and design optimization of wind farms. My contributions have furthered accurate modeling of wake effects in wind farms and CFD-based layout optimization. I analyzed the effect of turbulence modeling on CFD simulations of wind turbine wakes and provided useful insights and recommendations for their use (Antonini et al. 2016, 2018a). Moreover, I revealed the contribution of wind direction uncertainty to the discrepancies usually found between CFD predictions of wake wind speed and field measurements (Antonini et al. 2019). To optimize wind farm layouts and integrate CFD models in a design methodology, I developed and implemented an innovative adjoint method for gradient calculations within the framework of a gradient-based optimization (Antonini et al. 2018b). The developed optimization methodology integrated CFD models and overcame the high computational costs of a CFD-based optimization. This unique methodology enabled for the first time the optimization of wind farms in complex terrains with realistic ambient conditions and flow structures (Antonini et al. 2020).
Numerical modelling of wind turbine aerodynamics (2013-2014)
During my MSc program, I was engaged in computational modeling of both horizontal and vertical axis wind turbines. Their design methods are usually based on blade element-momentum theory, which in turn relies on the accuracy of the chosen airfoils’aerodynamic database. To assess their accuracy, I reviewed and compared four widely used aerodynamic coefficient databases for vertical axis wind turbine simulations and provided practical guidance to wind turbine designers for different rotor sizes and working conditions (Bedon at al. 2014). I also developed models based on vortex theory to analyze the rotor performance of these machines and establish new and reliable design procedures. An innovative vortex model that I proposed was used to simulate the complex dynamic stall behavior of turbine blades and provided excellent agreement with experimental data at a reduced computational cost (Antonini et al. 2015).