Airborne Wind Energy - to fly or not to fly?

This thesis investigates crosswind Airborne Wind Energy Systems (AWESs) in terms of power production and potential role in future electricity generation systems. The perspective ranges from the small scale, modelling AWE as a single system, to the large, implementing AWESs in regional electricity systems. \ua0To estimate the AWES power production, the thesis provides a dynamic system model that serves as the basis for all the work. The model describes the flight dynamics of a rigid wing that is exposed to tether and aerodynamic forces controlled by flight control surfaces. Index-3 Differential Algebraic Equations (DAEs) based on Lagrangian mechanics describe the dynamics. \ua0This model is validated by fitting it to real flight measurements obtained with a pumping-mode AWES, the prototype AP2 by Ampyx Power. The optimal power production of an AWES depends on complex trade-offs; this motivates formulating the power production computation as an Optimal Control Problem (OCP). The thesis presents the numerical methods needed to discretize the OCP and solve the resulting Nonlinear Program (NLP). \ua0Large-scale implementation of AWESs raises challenges related to variability in power production on the time scale of minutes to weeks. For the former, we investigate the periodic fluctuations in the power output of a single AWES. These fluctuations can be severe when operating a wind farm and have to be considered and reduced for an acceptable grid integration. We analyse the option of controlling the flight trajectories of the individual systems in a farm so that the total power output of the farm is smoothed. This controlled operation fixes the system\u27s trajectory, reducing the ability to maximize the power output of individual AWESs to local wind conditions. We quantify the lost power production if the systems are controlled such that the total farm power output is smoothed. Results show that the power difference between the optimal and fixed trajectory does not exceed 4% for the systems modelled in the study.\ua0The variations in AWESs power production on the timescale of hours to weeks are particularly relevant to the interaction between AWE and other power generation technologies. Investigating AWESs in an electricity system context requires power-generation profiles with high spatio-temporal resolution, which means solving a large number of OCPs. In order to efficiently solve these numerous OCPs in a sequential manner, this thesis presents a homotopy-path-following method combined with modifications to the NLP solver. The implementation shows a 20-fold reduction in computation time compared to the original method for solving the NLP for AWES power optimization.\ua0 For large wind-data sets, a random forest regression model is trained to a high accuracy, providing an even faster computation.The annual generation profiles for the modelled systems are computed using ERA5 wind data for several locations and compared to the generation profile for a traditional wind turbine. The results show that the profiles are strongly correlated in time, which is a sobering fact in terms of technology competition. However, the correlation is weaker in locations with high wind shear.\ua0 \ua0The potential role of AWESs in the future electricity system is further investigated. This thesis implements annual AWE-farm generation profiles into a cost-optimizing electricity system model. We find that AWE is most valuable to the electricity system if installed at sites with low wind speed within a region. At greater shares of the electricity system, even if AWESs could demonstrate lower costs compared to wind turbines, AWE would merely substitute for them instead of increasing the total share of wind energy in the system. This implies that the economic value of an AWES is limited by its cost relative to traditional wind turbines

Airborne Wind Energy - To fly or not to fly?

This thesis investigates crosswind Airborne Wind Energy Systems (AWESs) in terms of power production and potential role in future electricity generation systems. The perspective ranges from the small scale, modelling AWE as a single system, to the large, implementing AWESs in regional electricity systems. \ua0To estimate the AWES power production, the thesis provides a dynamic system model that serves as the basis for all the work. The model describes the flight dynamics of a rigid wing that is exposed to tether and aerodynamic forces controlled by flight control surfaces. Index-3 Differential Algebraic Equations (DAEs) based on Lagrangian mechanics describe the dynamics. \ua0This model is validated by fitting it to real flight measurements obtained with a pumping-mode AWES, the prototype AP2 by Ampyx Power. The optimal power production of an AWES depends on complex trade-offs; this motivates formulating the power production computation as an Optimal Control Problem (OCP). The thesis presents the numerical methods needed to discretize the OCP and solve the resulting Nonlinear Program (NLP). \ua0Large-scale implementation of AWESs raises challenges related to variability in power production on the time scale of minutes to weeks. For the former, we investigate the periodic fluctuations in the power output of a single AWES. These fluctuations can be severe when operating a wind farm and have to be considered and reduced for an acceptable grid integration. We analyse the option of controlling the flight trajectories of the individual systems in a farm so that the total power output of the farm is smoothed. This controlled operation fixes the system\u27s trajectory, reducing the ability to maximize the power output of individual AWESs to local wind conditions. We quantify the lost power production if the systems are controlled such that the total farm power output is smoothed. Results show that the power difference between the optimal and fixed trajectory does not exceed 4% for the systems modelled in the study.\ua0The variations in AWESs power production on the timescale of hours to weeks are particularly relevant to the interaction between AWE and other power generation technologies. Investigating AWESs in an electricity system context requires power-generation profiles with high spatio-temporal resolution, which means solving a large number of OCPs. In order to efficiently solve these numerous OCPs in a sequential manner, this thesis presents a homotopy-path-following method combined with modifications to the NLP solver. The implementation shows a 20-fold reduction in computation time compared to the original method for solving the NLP for AWES power optimization.\ua0 For large wind-data sets, a random forest regression model is trained to a high accuracy, providing an even faster computation.The annual generation profiles for the modelled systems are computed using ERA5 wind data for several locations and compared to the generation profile for a traditional wind turbine. The results show that the profiles are strongly correlated in time, which is a sobering fact in terms of technology competition. However, the correlation is weaker in locations with high wind shear.\ua0 \ua0The potential role of AWESs in the future electricity system is further investigated. This thesis implements annual AWE-farm generation profiles into a cost-optimizing electricity system model. We find that AWE is most valuable to the electricity system if installed at sites with low wind speed within a region. At greater shares of the electricity system, even if AWESs could demonstrate lower costs compared to wind turbines, AWE would merely substitute for them instead of increasing the total share of wind energy in the system. This implies that the economic value of an AWES is limited by its cost relative to traditional wind turbines

Methane Mitigation:Methods to Reduce Emissions, on the Path to the Paris Agreement

The atmospheric methane burden is increasing rapidly, contrary to pathways compatible with the goals of the 2015 United Nations Framework Convention on Climate Change Paris Agreement. Urgent action is required to bring methane back to a pathway more in line with the Paris goals. Emission reduction from “tractable” (easier to mitigate) anthropogenic sources such as the fossil fuel industries and landfills is being much facilitated by technical advances in the past decade, which have radically improved our ability to locate, identify, quantify, and reduce emissions. Measures to reduce emissions from “intractable” (harder to mitigate) anthropogenic sources such as agriculture and biomass burning have received less attention and are also becoming more feasible, including removal from elevated-methane ambient air near to sources. The wider effort to use microbiological and dietary intervention to reduce emissions from cattle (and humans) is not addressed in detail in this essentially geophysical review. Though they cannot replace the need to reach “net-zero” emissions of CO2, significant reductions in the methane burden will ease the timescales needed to reach required CO2 reduction targets for any particular future temperature limit. There is no single magic bullet, but implementation of a wide array of mitigation and emission reduction strategies could substantially cut the global methane burden, at a cost that is relatively low compared to the parallel and necessary measures to reduce CO2, and thereby reduce the atmospheric methane burden back toward pathways consistent with the goals of the Paris Agreement

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

Evaluating Cropland N2O Emissions and Fertilizer Plant Greenhouse Gas Emissions With Airborne Observations

Agricultural activity is a significant source of greenhouse gas emissions. The fertilizer production process emits N2O, CO2, and CH4, and fertilized croplands emit N2O. We present continuous airborne observations of these trace gases in the Lower Mississippi River Basin to quantify emissions from both fertilizer plants and croplands during the early growing season. Observed hourly emission rates from two fertilizer plants are compared with reported inventory values, showing agreement for N2O and CO2 emissions but large underestimation in reported CH4 emissions by up to a factor of 100. These CH4 emissions are consistent with loss rates of 0.6–1.2%. We quantify regional emission fluxes (100 km) of N2O using the airborne mass balance technique, a first application for N2O, and explore linkages to controlling processes. Finally, we demonstrate the ability to use airborne measurements to distinguish N2O emission differences between neighboring fields, determining we can distinguish different emission behaviors of regions on the order of 2.5 km2 with emissions differences of approximately 0.026 μmol m−2 s−1. This suggests airborne approaches such as outlined here could be used to evaluate the impact of different agricultural practices at critical field‐size spatial scales.Key PointsReported N2O and CO2 emissions from fertilizer plants agree with observations, but CH4 is underestimated by orders of magnitudeWe demonstrate mass balance quantification of N2O emissions from agriculture at 10–100 km scalesAirborne measurements can observe and quantify N2O emission differences between agricultural fields of ∼2.5 km2Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156438/3/jgrd56401.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156438/2/jgrd5640-sup-0001-Figure_SI-S01.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156438/1/jgrd56401_am.pd

Constraining industrial ammonia emissions using hyperspectral infrared imaging

Atmospheric emissions of reactive nitrogen in the form of nitrogen dioxide (NO) and ammonia (NH) worsen air quality and upon deposition, dramatically affect the environment. Recent infrared satellite measurements have revealed that NH emitted by industries are an important and underestimated emission source. Yet, to assess these emissions, current satellite sounders are severely limited by their spatial resolution. In this paper, we analyse measurement data recorded in a series of imaging surveys that were conducted over industries in the Greater Berlin area (Germany). On board the aircraft were the Telops Hyper-Cam LW, targeting NH measurements in the longwave infrared at a resolution of 4 m and the SWING+ spectrometer targeting NO measurements in the UV–Vis at a resolution of 180 m. Two flights were carried out over German’s largest production facility of synthetic NH , urea and other fertilizers. In both cases, a large NH plume was observed originating from the factory. Using a Gaussian plume model to take into account plume rise and dispersion, coupled with well-established radiative transfer and inverse methods, we retrieve vertical column densities. From these, we calculate NH emission fluxes using the integrated mass enhancement and cross-sectional flux methods, yielding consistent emissions of the order of 2200 t yr−1 for both flights, assuming constant fluxes across the year. These estimates are about five times larger than those reported in the European Pollutant Release and Transfer Register (E-PRTR) for this plant. In the second campaign, a co-emitted NO plume was measured, likely related to the production of nitric acid at the plant. A third flight was carried out over an area comprising the cities of Staßfurt and Bernburg. Several small NH plumes were seen, one over a production facility of mineral wool insulation, one over a sugar factory and two over the soda ash plants in Staßfurt and Bernburg. A fifth and much larger plume was seen to originate from the sedimentation basins associated with the soda ash plant in Staßfurt, indicating rapid volatilization of ammonium rich effluents. We use the different measurement campaigns to simulate measurements of Nitrosat, a potential future satellite sounder dedicated to the sounding of reactive nitrogen at a resolution of 500 m. We demonstrate that such measurements would allow accurately constraining emissions in a single overpass, overcoming a number of important drawbacks of current satellite sounders

Quantifying Local to Regional Emissions of Methane Using UAV-based Atmospheric Concentration Measurements

The uncertainty in methane (CH4) emissions that go into the global methane cycle is significant, and accurate atmospheric measurements and quantification of CH4 is of vital importance to reduce this uncertainty. This thesis explores the use of an unmanned aerial vehicle (UAV) in combination with a high accuracy methane sampling tool to measure and quantify CH4 emissions. First, a suitable instrument capable of accurate measurements of greenhouse gases (GHGs) is developed and tested. Second, using this newly developed instrumentation, a technique for quantifying methane emissions from a point source is developed. Finally, this instrumentation and technique is used to sample and quantify the regional CH4 emissions from a large industrial coal mining region. The results coming from this thesis has helped progress the use of mobile unmanned aerial vehicles for atmospheric trace gas research, and shows that quantification techniques using UAVs can be a powerful tool to make accurate measurements of CH4 and other trace gases, and further help in lowering the overall uncertainty on the atmospheric carbon cycle