Browsing by Subject "Energy"

Wind energy has emerged as one of the most promising and rapidly growing renewable energy technologies in the United States and over the world. The offshore wind energy is of special interest because it has more consistent and faster wind speed, and is usually close to large population areas that are along the coast. However, wake shielding on offshore wind farms substantially reduces the efficiency of downstream wind turbines due to the interaction with the energy-depleted wakes from upwind turbines. This research considers a method to mitigate the wake shielding effect by tilting the turbine axes upward, which causes streamwise vorticity in the near wake so that the energy depleted wakes transport upward alleviating shielding, and pumping more energetic fluid into downstream turbines.

The wake simulations in this research employ a specially developed hybrid free-wake method for wind turbine wakes, that utilizes Vortex Lattice Method (VLM) for near wake representation with appropriate stall and unsteady models, and Constant Circulation Contours Method (CCCM) for turbine far wake representation with a large degree of downwind vorticity diffusion. This approach has been implemented to capture the natural behavior of multi-filament multi-blade complex turbine wakes in relatively short computation time, with the capability to simulate wake interaction with downstream turbines. It is validated through comparison to two wind tunnel tests, NREL/NASA-Ames Wind Tunnel Test and MEXICO, and two turbine wake numerical models, BEM and QBlade.

The wake steering effect for tilted turbines is verified and the degree of effectiveness is assessed. Detailed turbine wake structure is studied to obtain insights into how to strengthen the steering effect and decrease wake velocity deficit. Inline two turbine simulations where one turbine operates in the wake of the other have been performed to assess the advantage of wake steering in power generation of a system of turbines. Beyond the single rotor tilted turbine, an intermeshed rotor wind turbine configuration, consisting of two partially overlapping counter-rotating rotors, has been studied to assess its potential to strength wake steering effect and to intensify wake deficit recovery. These two turbine configurations are compared along with a discussion of potential advantages and challenges. Several model refinements for more robust turbine wake simulation are under development or considered as future research goals.

The rising carbon dioxide emissions contributing to climate change has lead to the examination of potential ways to mitigate the environmental impact. One such method is through the geological sequestration of carbon (CCS). Although there are several different forms of geological sequestration (i.e. Saline Aquifers, Oil and Gas Reservoirs, Unminable Coal Seams) the current projects are just initiating the large scale-testing phase. The lead entry point into CCS projects is to combine the sequestration with enhanced oil recovery (EOR) due to the improved economic model as a result of the oil recovery and the pre-existing knowledge of the geological structures. The potential scope of CCS-EOR projects throughout the continental United States in terms of a systematic examination of individual reservoir storage potential has not been examined. Instead the majority of the research completed has centered on either estimating the total United States storage potential or the potential of a single specific reservoir.

The purpose of this paper is to examine the relationship between oil recovery, carbon dioxide storage and cost during CCS-EOR. The characteristics of the oil and gas reservoirs examined in this study from the Nehring Oil and Gas Database were used in the CCS-EOR model developed by Sean McCoy to estimate the lifting and storage costs of the different reservoirs throughout the continental United States. This allows for an examination of both technical and financial viability of CCS-EOR as an intermediate step for future CCS projects in other geological formations.

One option for mitigating climate change is to store industrial CO2 emissions in geologic reservoirs as part of a process known as carbon capture and storage (CCS). There is general consensus that large-scale deployment of CCS would best be initiated by combining geologic sequestration with enhanced oil recovery (EOR), which can use CO2 to improve production from declining oil fields. Revenues from the produced oil could help offset the current high costs of CCS.

The cumulative potential of CCS-EOR in the continental U.S. has been evaluated in terms of both CO2 storage capacity and additional oil production. This thesis examines the same potential, but on a reservoir-by-reservoir basis. Reservoir properties from the Nehring Oil and Gas Database are used as inputs to a CCS-EOR model developed by McCoy (YR) to estimate the storage capacity, oil production and CCS-EOR costs for over 10,000 oil reservoirs located throughout the continental United States.

We find that 86% of the reservoirs could store ≤1 y or CO2 emissions from a single 500 MW coal-fired power plant (i.e., 3 Mtons CO2). Less than 1% of the reservoirs, on the other hand, appear capable of storing ≥30 y of CO2 emissions from a 500 MW plan. But these larger reservoirs are also estimated to contain 48% of the predicted additional oil that could be produced through CCS-EOR. The McCoy model also predicts that the reservoirs will on average produce 4.5 bbl of oil for each ton of sequestered CO2, a ratio known as the utilization factor. This utilization factor is 1.5 times higher that arrived at by the U.S. Department of Energy, and leads to a cumulative production of oil for all the reservoirs examined of ~183 billion barrels along with a cumulative storage capacity of 41 Mtons CO2. This is equivalent to 26.5 y of current oil consumption by the nation, and 8.5 y of current coal plant emissions.

A cost-effective pathway towards net-zero electric power systems requires an extraordinary deployment of new solar and wind generation assets. This aggressive expansion driving unprecedented investment entails a fundamental understanding of the challenge ahead of us. This dissertation seeks to provide a multidisciplinary perspective of research questions that shine the light on rapid and cost-efficient strategies for the energy transition. Integrating operations research and geospatial analysis methods, the dissertation utilizes a multidisciplinary approach when addressing three questions.

First, the dissertation examines the role of battery energy storage technologies (i.e., utility-scale lithium-ion batteries) on reducing the greenhouse gas emissions of an electric power system while simultaneously achieving a reduction in carbon abatement costs. The study uses a cost-based production model (day-ahead unit commitment and a real-time economic dispatch) to simulate the optimal operation of all the generation resources in the largest vertically-integrated electric service region in the U.S. The study explores a multitude of configurations to identify optimal sizing of battery energy storage systems when paired with utility-scale photovoltaics.

Next, the dissertation studies the effect of incorporating high-resolution data when identifying suitable land for renewable energy projects over a geographically defined region. Using a python-based user-friendly siting tool implemented in ArcGIS Pro to perform suitability and cost analysis of utility-scale photovoltaic projects in North Carolina under three scenarios (representing conditions ranging from favorable to restrictive). The study finds that the land suitable for utility-scale photovoltaics reduces substantially when parcel-level data reflecting local land-use restrictions are incorporated. The study's findings highlight the necessity of integrating detailed land-use data that reflects local regulation (zoning ordinances) into siting models while simultaneously increasing their spatial granularity.

Lastly, the dissertation analyzes the benefits of weatherizing wind power farms enabling their operation under extreme climates (winter storms). The study uses global reanalysis data with operational information from the Electric Reliability Council of Texas (ERCOT) during the 2021 winter storm Uri to simulate a continued operation of wind power farms under low-temperature environments. The study finds that the financial benefits that winterized wind turbines would have received during winter storm Uri would have outweighed the capital costs required to implement ice-accretion mitigation actions (before winter storm URI).

Abundant and widely available solar energy is one possible solution to the increasing demands for clean energy. The Thermodynamics and Sustainable Energy Laboratory (T-SEL) in Duke University has been dedicated to investigating methods to harness solar energy. Hybrid Solar System (HSS) is one of the promising methods to use solar energy, as it absorbs sunlight to produce hydrogen, which then can electrically power equipment through fuel cells. Hydrogen is produced through a biofuel reforming process, which occurs at a high temperature (over 700℃ for methane). Methods to design a high-temperature solar selective coating are investigated in this thesis.

The solar irradiance spectrum was assumed to be the same as Air Mass (AM) 1.5. A transfer-matrix method was adopted in this work to calculate the optical properties of the NREL #6, a design of nine-layer solar selective coating. Based on the design of NREL #6 coating, Differential Evolution (DE) algorithm was introduced to optimize this design. Two objective functions were considered: selectivity-oriented function and efficiency-oriented function, yielding the design of Revision #1 and Revision #2 respectively. The results showed a high selectivity (around 13) with low efficiency (66.6%) in Revision #1 and a high efficiency (82.6%) with moderate selectivity (around 9) in Revision #2.

Residential energy consumption represents a large share of total end use energy and shows strong correlation with monthly cooling and heating degree days. This study focuses on quantifying temporal change in the relationship between monthly degree days and monthly U.S. residential use of electricity and natural gas for each of the 48 contiguous states from 1990 to 2017. We introduce a single degree day predicator to characterize the non-linear relationship between degree-day and state-level electricity and natural gas use. By looking at trends in three DD-energy use coordinates and curvature from single quadratic fits on a year-by-year and state-by-state basis, we confirm the non-linear relationship between DD and residential energy use and reveal processes that might influence the relationship. We find that residential electricity energy use has become more sensitive to seasonal fluctuations in temperature in most states. While the lowest electricity use per year has risen, natural gas use has fallen since 1990 in most states. We further group the states into 17 classes for electricity use and 21 classes for natural gas use based on combinations of temporal trends in quadratic curve variables. These large groupings for electricity have shown a similar spatial distribution as that of the climate regions defined by the U.S. Department of Energy, reaffirming temperature and humidity as influential factors in the climate-energy relationship. We also compare our results with the household and end uses information from U.S. Energy Information Administration’s Residential Energy Consumption (REC) Surveys and recognize electricity as a growing heating source in all U.S. regions. We further address economic development, energy efficiency of end uses, and building codes as potential trends that affect the relationship between degree day and residential energy use at national, regional and state levels.

Carbon Capture and Storage (CCS) technologies provide a means to significantly reduce carbon emissions from the existing fleet of fossil-fired plants, and hence can facilitate a gradual transition from conventional to more sustainable sources of electric power. This is especially relevant for coal plants that have a CO2 emission rate that is roughly two times higher than that of natural gas plants. Of the different kinds of CCS technology available, post-combustion amine based CCS is the best developed and hence more suitable for retrofitting an existing coal plant. The high costs from operating CCS could be reduced by enabling flexible operation through amine storage or allowing partial capture of CO2 during high electricity prices. This flexibility is also found to improve the power plant’s ramp capability, enabling it to offset the intermittency of renewable power sources. This thesis proposes a solution to problems associated with two promising technologies for decarbonizing the electric power system: the high costs of the energy penalty of CCS, and the intermittency and non-dispatchability of wind power. It explores the economic and technical feasibility of a hybrid system consisting of a coal plant retrofitted with a post-combustion-amine based CCS system equipped with the option to perform partial capture or amine storage, and a co-located wind farm. A techno-economic assessment of the performance of the hybrid system is carried out both from the perspective of the stakeholders (utility owners, investors, etc.) as well as that of the power system operator.

In order to perform the assessment from the perspective of the facility owners (e.g., electric power utilities, independent power producers), an optimal design and operating strategy of the hybrid system is determined for both the amine storage and partial capture configurations. A linear optimization model is developed to determine the optimal component sizes for the hybrid system and capture rates while meeting constraints on annual average emission targets of CO2, and variability of the combined power output. Results indicate that there are economic benefits of flexible operation relative to conventional CCS, and demonstrate that the hybrid system could operate as an energy storage system: providing an effective pathway for wind power integration as well as a mechanism to mute the variability of intermittent wind power.

In order to assess the performance of the hybrid system from the perspective of the system operator, a modified Unit Commitment/ Economic Dispatch model is built to consider and represent the techno-economic aspects of operation of the hybrid system within a power grid. The hybrid system is found to be effective in helping the power system meet an average CO2 emissions limit equivalent to the CO2 emission rate of a state-of-the-art natural gas plant, and to reduce power system operation costs and number of instances and magnitude of energy and reserve scarcity.

This dissertation shows the use of Constructal law to find the relation between the morphing of the system configuration and the improvements in the global performance of the complex flow system. It shows that the better features of both flow and heat transfer architecture can be found and predicted by using the constructal law in energy systems. Chapter 2 shows the effect of flow configuration on the heat transfer performance of a spiral shaped pipe embedded in a cylindrical conducting volume. Several configurations were considered. The optimal spacings between the spiral turns and spire planes exist, such that the volumetric heat transfer rate is maximal. The optimized features of the heat transfer architecture are robust. Chapter 3 shows the heat transfer performance of a helically shaped pipe embedded in a cylindrical conducting volume. It shows that the optimized features of the heat transfer architecture are robust with respect to changes in several physical parameters. Chapter 4 reports analytically the formulas for effective permeability in several configurations of fissured systems, using the closed-form description of tree networks designed to provide flow access. The permeability formulas do not vary much from one tree design to the next, suggesting that similar formulas may apply to naturally fissured porous media with unknown precise details, which occur in natural reservoirs. Chapter 5 illustrates a counterflow heat exchanger consists of two plenums with a core. The results show that the overall flow and thermal resistance are lowest when the core is absent. Overall, the constructal design governs the evolution of flow configuration in nature and energy systems.

Cooking fuel “stacking,” or the use of multiple types of fuels, can be problematic in interventions when households are using both clean and dirty fuels at the same time. Dirty fuels such as firewood contribute to indoor air pollution, cause detrimental health effects, and are inefficient forms of energy. In this study, cooking fuel preference data was collected from 360 households in peripheral-urban Kathmandu, Nepal during August 2019. Respondents provided fuel information and gave economic preferences for a contingent valuation experiment on their reported primary fuel type. We explored two aims through multiple regression analyses: the relationship between fuel stacking behavior and willingness to pay (WTP), and the household characteristics associated with fuel stacking behavior. The analyses showed that stacking does not affect WTP, and household expenses are a significant factor associated with WTP only among households using LPG as their primary fuel. The secondary aim found that the main household characteristics associated with fuel stacking are household size, firewood gathering behavior, and if the household was affected by the 2015 LPG blockade. The relationships of these characteristics are complex and depend on whether the household is using more LPG or more firewood when stacking. More research is needed to better understand fuel stacking, and why most people in peri-urban Kathmandu prefer LPG as their primary fuel.