Browsing by Subject "Wind energy"

In this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields.

In this new method, nonstationarity is characterized and modeled via temporal coherence, which is quantified in the discrete frequency domain by probability distributions of the differences in phase between adjacent Fourier components.

The empirical distributions of the phase differences can also be extracted from measured data, and the resulting temporal coherence parameters can quantify the occurrence of nonstationarity in empirical wind data.

This dissertation (1) implements temporal coherence in a desktop turbulence simulator, (2) calibrates empirical temporal coherence models for four wind datasets, and (3) quantifies the increase in lifetime wind turbine loads caused by temporal coherence.

The four wind datasets were intentionally chosen from locations around the world so that they had significantly different ambient atmospheric conditions.

The prevalence of temporal coherence and its relationship to other standard wind parameters was modeled through empirical joint distributions (EJDs), which involved fitting marginal distributions and calculating correlations.

EJDs have the added benefit of being able to generate samples of wind parameters that reflect the characteristics of a particular site.

Lastly, to characterize the effect of temporal coherence on design loads, we created four models in the open-source wind turbine simulator FAST based on the \windpact turbines, fit response surfaces to them, and used the response surfaces to calculate lifetime turbine responses to wind fields simulated with and without temporal coherence.

The training data for the response surfaces was generated from exhaustive FAST simulations that were run on the high-performance computing (HPC) facilities at the National Renewable Energy Laboratory.

This process was repeated for wind field parameters drawn from the empirical distributions and for wind samples drawn using the recommended procedure in the wind turbine design standard \iec.

The effect of temporal coherence was calculated as a percent increase in the lifetime load over the base value with no temporal coherence.

As one of the windiest places in the world, it is no surprise that companies have flocked to Mexico's Isthmus of Tehuantepec, a narrow neck of land connecting the Atlantic and Pacific Oceans. Primarily foreign corporations have installed more than1500 wind turbines in less than ten years' time. While wind energy appears an ethereal, amorphous, and limitless resource, the wind can only become electricity through turbines that require vast tracts of land. The question of land ownership — a historical flashpoint in the region — has amplified tensions between residents, straining the already frayed web of social relations that have long bound this indigenous Zapotec community to one another.

Many of the indigenous Zapotec residents are thrilled these once bothersome winds are becoming productive — as profits, job security, and perhaps their shot at progress. Landowners are among the most ardent supporters of wind energy development, tending their livestock in the morning, leveraging their land in exchange for more favorable lease agreements with executives in the afternoon. Opponents of the industry liken their boosters to an earlier colonial power, asking, "What are we going to eat if you turn everything into gold?" – depicting wind energy as merely the latest in a long history of dispossessions. For them, the wind has always been productive, an actor in their everyday lives: it awakens the fruits of the sea, sustaining fishermen and feeding their families; it causes illness and destroys property, and it conjures residents to recall the joys of living in this place. What Istmeños are aware of are the stark geopolitical realities that have brought wind turbines to their doorstep.

In a moment when Mexico's oil reserves are dwindling and the state searches for alternative revenues, the case of wind energy development on the Isthmus of Tehuantepec complicates the utopian narrative that industry and government advocates recount regarding the so-called win-win possibilities for green energy development across the global South. What happens when the wind is transformed from its unruly natural state into a natural resource? Far from an isolated case, this dissertation draws upon broader theories of power, both electrical and economic, to show how individuals, institutions, and experts are laying claim to nature's force. Neither the fable of green techno-optimism nor a return to some mythical nature adequately explains the messiness of the everyday realities I observed. Based on more than 18 months of ethnographic fieldwork, I trace the generative possibilities of the wind, reconfiguring social relations through technological change. Ultimately, however, it is the imponderability of the natural world, its scale and power, and the very real consequences that efforts to mitigate global climate change are having in one particular place that I hope to convey in this work.

Novel wind turbine designs are deemed acceptable through a simulation-based certification process that involves generating a synthetic wind record and using it as an input to a computer model of the turbine. Naturally, whether the simulation loads reflect the loads that the turbine would actually experience depends on the accuracy of the wind turbine model and, more importantly, on the accuracy of the method used to generate the synthetic wind record. The simulation methods that are commonly used for this purpose are spectral-based and produce Gaussian, stationary random fields. These methods prescribe a power spectral density (PSD) of the wind velocity, which fixes the magnitudes of the Fourier components, then assumes that the Fourier phase angles are independent and uniformly distributed. An inverse Fast Fourier Transform (IFFT) is then used to transform the wind velocity field to the time domain.

This thesis applies the concept of phase coherence---i.e., Fourier phase angles that are not independent---to the stochastic modeling and simulation of wind velocity fields. Using a large dataset available from the National Wind Technology Center (NWTC), a joint distribution is characterized for the mean wind speed U, turbulence σ_u, Kaimal length scale L, and a metric for the degree of phase coherence in wind data, R. The correlations between these four parameters, the vertical height, and another phase coherence parameter are presented; only U, σ_u, and L have any significant degree of correlation. The joint distribution is used to generate synthetic wind records, which are then compared with measured data that have the same parameter values. For data with low to medium coherence values, the synthetic records have a similar qualitative appearance to the data. For high levels of phase coherence, the records simulated with the proposed model were qualitatively different from records with the same parameter values due to the variation of the phase difference spread in the spectral domain. Lastly, the importance of correctly modeling phase coherence is demonstrated by using the data and the synthetic records as inputs to a single-degree-of-freedom (SDOF) oscillator and comparing the peak response statistics and damage equivalent loads (DELs).

This PhD dissertation presents three studies that individually aim to increase understanding of various aspects of solar and wind energy and the challenge of integrating them in the electricity power system. The first study explores the opportunity to improve the technical and economic performance of concentrated solar thermal power plants (CSPs) through joint installation and operation with fossil-fuel combined cycle power plants (CCPPs). The second study presents an analysis of the feasibility and technical, environmental, and economic effects of integrating large levels of distributed solar Photovoltaic (PV) into a rather inflexible (nuclear-heavy generating base) power system. The last study evaluates the potential of off-grid distributed generation (DG) technologies including solar PV and wind systems to provide a cost-effective solution to supply electricity to isolated loads in Saudi Arabia.

Several tools and models have been developed to accomplish these studies including a thermodynamic model developed in MATLAB environment to simulate ISCC plant operations, a PV production model that estimates hourly PV power output, a unit commitment and real-time economic dispatch (UC−ED) model that simulates hourly system operations and a mixed integer linear programing that determines the optimal off-grid energy mix and capacity.

Although two of three main studies presented do not focus specifically on Saudi Arabia, they provide valuable insights for a transition of its electricity sector towards less dependence on fossil fuels and increased use of renewables.

Saudi Arabia, the world’s largest oil producer, relies on fossil fuels as the primary energy source to meet its electricity needs. Its existing electricity generation fleet consists of a large number of old and inefficient gas combustion and steam turbines, several gas and oil-fired combined cycle power plants, and many diesel combustion engines located in non-interconnected areas. The recently launched governmental plan Saudi Arabia Vision 2030 intends to enhance the resiliency of the Saudi economy by diversifying the electricity generation portfolio through the inclusion of renewable and nuclear energy.

Pertinent to the Kingdom of Saudi Arabia (KSA), the first study shows that Integrated Solar Combined Cycle Power Plants (ISCCs) offer an opportunity to reduce fossil-fuel consumption while reducing the levelized cost of solar thermal energy (LCOE) by 35-40%. The third study shows that the in three non-interconnected regions of KSA, off-grid distributed generation including more than 300 MW of solar PV and wind energy is a cost-effective alternative assuming plausible scenarios for fuel prices and electricity demand. In addition, the results reveal that the local excellent solar resources and the high efficiency of the wind turbine technologies that could be installed make the LCOE of solar PV and wind lower than the LCOE of highly efficient oil-fired combined cycle power plants (CCPP) under moderate and high oil price scenarios.

Finally, the second study illustrates a potential barrier to the integration of a high share of distributed intermittent energy sources into a power network that operates large base-load thermal generation units and rather inflexible nuclear power plants.