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The solar furnace research project at Valparaiso University utilizes a decoupled solar thermal electrolysis process for the production of H2 from water. We are focusing on an iron oxide system, which involves the conversion of magnetite to hematite in a cyclical process. Our experimental study for the iron oxide system confirmed that the electrolytic oxidation and thermal reduction steps of the metal oxide occur in a laboratory scale environment. Unfortunately, some of the Fe+3 products for the magnetite system stays in solution when the electrolysis is done in a strong acid. We needed to develop methods to quantify the fraction of iron remaining in solution in order to maximize solid phase recovery. Our analyses provide data consistent with the expected Fe+2: Fe+3 ratio. We will continue with improving solid phase hematite recovery

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The solar furnace research project at Valparaiso University utilizes a decoupled solar thermal electrolysis process for the production of H2 from water. We are focusing on an iron oxide system, which involves the conversion of magnetite to hematite in a cyclical process. Our experimental study for the iron oxide system confirmed that the electrolytic oxidation and thermal reduction steps of the metal oxide occur in a laboratory scale environment. Unfortunately, some of the Fe+3 products for the magnetite system stays in solution when the electrolysis is done in a strong acid. We needed to develop methods to quantify the fraction of iron remaining in solution in order to maximize solid phase recovery. Our analyses provide data consistent with the expected Fe+2: Fe+3 ratio. We will continue with improving solid phase hematite recovery

The value of CO2-geothermal bulk energy storage to CO2

Two primary challenges for modern societies are to reduce the amount of carbon dioxide (CO2) that is emitted to the atmosphere and to increase the penetration of renewable energy technologies into electricity systems. CO2-bulk energy storage (CO2-BES) is a CO2 capture and storage (CCS) approach that can address both of these challenges by using CO2 emitted from large point sources (e.g., fossil fuel power plants, cement manufacturers) that is sequestered in sedimentary basin geothermal resources to take power from, and deliver power to, electricity grids. Electricity can be generated by wind and solar energy technologies regardless of whether there is demand for that electricity because wind and sunlight are variable resources. When over-generation occurs, the excess electricity can be used to compress and inject CO2 into sedimentary basin geothermal resources. Electricity can then be dispatched when needed by producing the pressurized and geothermally-heated CO2 from the storage reservoir and converting the heat to electricity in a CO2-geothermal power plant. In this way, CO2-BES can time-shift excess electricity that is generated by wind and solar energy facilities to when there is demand for that electricity. This ability can increase the utilization of installed wind and solar energy capacity. Thus, CO2-BES can (1) directly reduce CO2 emissions to the atmosphere by isolating them in porous and permeable subsurface reservoirs and (2) indirectly reduce CO2 emissions by displacing electricity from power plants that emit CO2 (e.g., fossil fuel plants) with electricity from wind and solar energy facilities. We present an approach to estimate the value of these direct and indirect benefits. Our approach uses an optimization model that we developed to determine the cost-minimizing dispatch of electricity-generating facilities to meet diurnal demand in regional electricity systems. In our analysis, electricity can be generated by base load and variable load power plants, wind- and solar-energy technologies, and CO2-BES facilities. We varied prices on CO2 emissions (e.g., a CO2 emissions tax) in order to determine the optimal CO2-BES storage capacity for each CO2 price. This method allows us to assign a monetary value to the optimized energy storage capacity. We use time increments of one hour, during which we assume electricity generation and demand are constant. Initial results using hypothetical but realistic scenarios for electricity demand and electricity generation by solar energy technologies suggest that the optimal energy storage capacity of CO2-BES is sensitive to a range of CO2 prices. That is, a small increase in the price on CO2 emissions can cause substantial change in the optimal distribution of electricity generation and the energy storage capacity of CO2-BES. Thus, independent system operators (ISOs) could dispatch CO2-BES without needing additional ancillary service compensation schemes if CO2 emissions were modestly taxed. This work was funded by the U.S. National Science Foundation Sustainable Energy Pathways program (grant 1230691)

Designing a Calorimeter to Calibrate an Optical Radiative Flux Measurement System to Find the Power Entering a Solar Reactor

A solar furnace has been constructed at Valparaiso University to test the performance of various solar chemical reactors. A primary performance index of a solar chemical reactor is the efficiency, or the fraction of the energy that enters the reactor that is utilized in the chemical reaction. To calculate this efficiency, we must first know how much solar power is entering the reactor. An optical radiative flux measurement system has been developed that gives the solar flux distribution over the aperture of the reactor, but must be calibrated to provide the actual power level. Therefore, a calorimeter was designed and built to perform this calibration. The calorimeter is designed so that the solar power entering the aperture is transferred to water flowing through the tubes that make up the cavity. Then, by measuring the flow rate of the water and the temperature of the water at the inlet and outlet, the energy entering the calorimeter can be calculated using the first law of thermodynamics. The uncertainty in the calculated power level has also been established through a thermal loss and measurement uncertainty analysis

Development of a Solar Rotary-Kiln Reactor for the Reduction of Metal Oxide Particles

A solar rotary-kiln reactor has been fabricated for the reduction of metal oxide particles at ~1650 K as part of a solar thermal decoupled water electrolysis process for the production of hydrogen. Particle motion is controlled through the reactor’s angular speed of rotation. At rotational speeds greater than 65 rpm, the internal walls of the reactor are fully covered with particles. Simultaneously, mixing elements generate a particle cloud in the reactor in order to increase the absorption of incident solar radiation. A model of the reactor that solves the energy conservation equation and includes the kinetics of the metal oxide reduction suggests that peak thermal efficiencies of 47 percent are possible for the reduction of hematite to magnetite. In parallel, the solid state kinetics for the reduction of cobalt oxide (a promising alternative to iron oxide) in a low oxygen partial pressure atmosphere has been determined. Reduction follows the shrinking core model and is initially limited by the rate of oxygen diffusion in the gas phase and later limited by the chemical kinetics at the shrinking reactive interface. Regression of the model to isothermal and non-isothermal thermogravimetric analyzer data yielded the temperature-dependent reaction rate parameters

Using CO₂-Plume geothermal (CPG) energy technologies to support wind and solar power in renewable-heavy electricity systems

CO₂-Plume Geothermal (CPG) technologies are geothermal power systems that use geologically stored CO₂ as the subsurface heat extraction fluid to generate renewable energy. CPG technologies can support variable wind and solar energy technologies by providing dispatchable power, while Flexible CPG (CPG-F) facilities can provide dispatchable power, energy storage, or both simultaneously. We present the first study investigating how CPG power plants and CPG-F facilities may operate as part of a renewable-heavy electricity system by integrating plant-level power plant models with systems-level optimization models. We use North Dakota, USA as a case study to demonstrate the potential of CPG to expand the geothermal resource base to locations not typically considered for geothermal power. We find that optimal system capacity for a solar-wind-CPG model can be up to 20 times greater than peak-demand. CPG-F facilities can reduce this modeled system capacity to just over 2 times peak demand by providing energy storage over both seasonal and short-term timescales. The operational flexibility of CPG-F facilities is further leveraged to bypass the ambient air temperature constraint of CPG power plants by storing energy at critical temperatures. Across all scenarios, a tax on CO₂ emissions, on the order of hundreds of dollars per tonne, is required to financially justify using renewable energy over natural-gas power plants. Our findings suggest that CPG and CPG-F technologies may play a valuable role in future renewable-heavy electricity systems, and we propose a few recommendations to further study its integration potential

The transmission ramifications of social and environmental siting considerations on wind energy deployment

Increasing the capacity of wind power is critical to achieving climate goals, however its continued deployment faces environmental and social siting challenges. For example, the United States government is increasingly emphasizing the importance of a just energy transition by considering the social impacts of energy and environmental justice (EEJ). In this study, we investigate the impact of considering available EEJ metrics and environmental impacts into siting wind power and transmission by applying SimWINDPRO. SimWINDPRO is an infrastructure optimization tool that can site wind energy technologies and transmission by concurrently considering wind resource potential, transmission costs, EEJ, and environmental impacts. We demonstrate the impacts of considering EEJ and environmental factors in the context of Midcontinent Independent System Operator’s (MISO) western region, which includes some of the best wind energy potential in the United States. We show that prioritizing EEJ and environmental considerations in wind deployment can result in exponentially more transmission deployment for the same amount of wind power delivered, and results in selecting different wind farm sites. Our results also show that, depending on how it is considered, it is possible that constraining sites based on EEJ and environmental factors can reduce the available capacity of wind energy enough that energy transition capacity targets cannot be met

The performance of solvent-based direct air capture across geospatial and temporal climate regimes

IntroductionLiquid-solvent direct air capture (DAC) is a prominent approach for carbon dioxide removal but knowing where to site these systems is challenging because it requires considering a multitude of interrelated geospatial factors. Two of the most pressing factors are: (1) how should DAC be powered to provide the greatest net removal of CO2 and (2) how does weather impact its performance?.MethodsTo investigate these questions, this study develops a process-level model of a liquid-solvent DAC system and couples it to a 20-year dataset of temperature and humidity conditions at a ~9km resolution across the contiguous US.Results and discussionWe find that the amount of CO2 sequestered could be 30% to 50% greater than the amount of CO2 removed from the atmosphere if natural gas is burned on site to power DAC, but that the optimal way to power DAC is independent of capture rate (i.e., weather), depending solely on the upstream GHG intensity of electricity and natural gas. Regardless of how it is powered, air temperature and humidity conditions can change the performance of DAC by up to ~3x and can also vary substantially across weather years. Across the continuous US, we find that southern states (e.g., Gulf Coast) are preferrable locations for a variety of reasons, including higher and less variable air temperature and relative humidity. Lastly, we also find the performance of liquid-solvent DAC calculated with monthly means is within 2% of the estimated performance calculated with hourly data for more than a third of the country, including in the states with weather most favorable for liquid-solvent DAC

Validity and Validation of Computer Simulations—A Methodological Inquiry with Application to Integrated Assessment Models

Our purpose is to advance a reasoned perspective on the scientific validity of computer simulation, using an example—integrated assessment modeling of climate change and its projected impacts—that is itself of great and urgent interest to policy in the real world. The spirited and continuing debate on the scientific status of integrated assessment models (IAMs) of global climate change has been conducted mostly among climate change modelers and users seeking guidance for climate policy. However, it raises a number and variety of issues that have been addressed, with various degrees of success, in other literature. The literature on methodology of simulation was mostly skeptical at the outset but has become more nuanced, casting light on some key issues relating to the validity and evidentiary standing of climate change IAMs (CC-IAMs). We argue that the goal of validation is credence, i.e., confidence or justified belief in model projections, and that validation is a matter of degree: (perfect) validity is best viewed as aspirational and, other things equal, it makes sense to seek more rather than less validation. We offer several conclusions. The literature on computer simulation has become less skeptical and more inclined to recognize that simulations are capable of providing evidence, albeit a different kind of evidence than, say, observation and experiments. CC-IAMs model an enormously complex system of systems and must respond to several challenges that include building more transparent models and addressing deep uncertainty credibly. Drawing on the contributions of philosophers of science and introspective practitioners, we offer guidance for enhancing the credibility of CC-IAMs and computer simulation more generally