Recent publications
This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. The key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.
In this paper, a practical ambient-frequency-data-based inertia estimation method using a physical equation is proposed and validated by real measurement data from Hawaii island grids. With high renewable penetration, accurate inertia estimation is important and urgent. Ambient frequency oscillation always exists in power grids, so the proposed method has advantages of real-time inertia estimation and no need for additional disturbances. This paper first developed the physical equation for inertia estimation to offer a clear mechanism for easy implementation in practice. To apply the proposed method in actual grids, a practical method to extract the ambient frequency oscillation from frequency measurement is further proposed. The inertia estimation using the physical equation is validated by KIUC simulation data and HECO field data, in which error rates are around 2% and 8%, respectively. Practical inertia estimation is challenging due to the large amounts of resources contributing to the power grid's effective inertia, but the method provided in this paper can offer a novel way for practical inertia estimation, which can help renewable penetration to boost carbon-free grid.
Grid-forming (GFM) inverters are increasingly recognized as a solution to facilitate massive grid integration of inverter-based resources and enable 100% power-electronics-based power systems. However, the overcurrent characteristics of GFM inverters exhibit major differences from those of conventional synchronous machines. Accordingly, an in-depth characterization of GFM current-limiting strategies is needed to ascertain their performance during off-nominal conditions. Although GFM current-limiting controls are primarily necessary to protect the inverter power stage, they determine the inverter behavior during and after an off-nominal system disturbance. As a result, they can profoundly impact device-level stability, transient system stability, power system protection, and fault recovery. This paper offers a comprehensive review of state-of-the-art current-limiting techniques for GFM inverters and outlines open challenges where innovative solutions are needed. One key contribution of this paper is the use of graphical methods that allow for intuitive understanding and visually-aided comparisons of current-limiting methods. With this approach, we evaluate various performance criteria for different limiting methods, such as fault current contribution, voltage support, stability, and post-fault recovery. We also discuss the latest standards and trends as they require inverter dynamics under off-nominal conditions and outline pathways for future developments.
The escalating global demand for oil, coupled with declining fossil fuel production, prompts the urgent exploration of renewable alternatives. To address this challenge, researchers are actively seeking environmentally friendly fuels like biodiesel. Among potential feedstocks, oil that is produced from salmon smoking process during industry emerges as a promising option. Smoked salmon oil could be a challenge when producing biodiesel due to its high content of omega-3 compounds. Using homogenous commercial catalyst from alkali to achieve the highest yield from salmon smoking oil was the aim of the current study. A Box–Behnken design and response surface methodology in Design Expert software (version 13) was used to study the effect of four main factors on the biodiesel yield from salmon smoking oil. The optimum biodiesel values were 70°C, 90 min, 0.753 wt.%, and 20 wt.% for temperature, reaction time, sodium hydroxide concentration, and methanol concentration, respectively. At these optimum values, the highest biodiesel production was 92.0% with fatty acid methyl ester contents of 83.4% and conversion efficiency of 77%. Thin-layer chromatography and thermal gravimetric analysis confirmed the successful production of biodiesel at optimized conditions. Using Aspen Plus simulation software confirmed the cost-effectiveness of the homogenous catalyst used for enhancing biodiesel production from salmon smoking oil.
Cyanobacteria are photosynthetic organisms that play important roles in carbon cycling and are promising bioproduction chassis. Here, we isolate two novel cyanobacteria with 4.6Mbp genomes, UTEX 3221 and UTEX 3222, from a unique marine environment with naturally elevated CO₂. We describe complete genome sequences for both isolates and, focusing on UTEX 3222 due to its planktonic growth in liquid, characterize biotechnologically relevant growth and biomass characteristics. UTEX 3222 outpaces other fast-growing model strains on a solid medium. It can double every 2.35 hours in a liquid medium and grows to high density (>31 g/L biomass dry weight) in batch culture, nearly double that of Synechococcus sp. PCC 11901, whose high-density growth was recently reported. In addition, UTEX 3222 sinks readily, settling more quickly than other fast-growing strains, suggesting favorable economics of harvesting UTEX 3222 biomass. These traits may make UTEX 3222 a compelling choice for marine carbon dioxide removal (CDR) and photosynthetic bioproduction from CO₂. Overall, we find that bio-prospecting in environments with naturally elevated CO₂ may uncover novel CO₂-metabolizing organisms with unique characteristics.
IMPORTANCE
Cyanobacteria provide a potential avenue for both biomanufacturing and combatting climate change via high-efficiency photosynthetic carbon sequestration. This study identifies novel photosynthetic organisms isolated from a unique geochemical environment and describes their genomes, growth behavior in culture, and biochemical composition. These cyanobacteria appear to make a tractable research model, and cultures are made publicly available alongside information about their culture and maintenance. Application of these organisms to carbon sequestration and/or biomanufacturing is discussed, including unusual, rapid settling characteristics of the strains relevant to scaled culture.
Herein, we report a selective photooxidation of commodity postconsumer polyolefins to produce polymers with in‐chain ketones. The reaction does not involve the use of catalyst, metals, or expensive oxidants, and selectively introduces ketone functional groups. Under mild and operationally simple conditions, yields up to 1.23 mol% of in‐chain ketones were achieved. Installation of in‐chain ketones resulted in materials with improved adhesion of the materials and miscibility of mixed plastics relative to the unfunctionalized plastics. The introduction of ketone groups into the polymer backbone allows these materials to react with diamines, forming dynamic covalent polyolefin networks. This strategy allows for the upcycling of mixed plastic waste into reprocessable materials with enhanced performance properties compared to polyolefin blends. Mechanistic studies support the involvement of photoexcited nitroaromatics in consecutive hydrogen and oxygen atom transfer reactions.
Herein, we report a selective photooxidation of commodity postconsumer polyolefins to produce polymers with in‐chain ketones. The reaction does not involve the use of catalyst, metals, or expensive oxidants, and selectively introduces ketone functional groups. Under mild and operationally simple conditions, yields up to 1.23 mol% of in‐chain ketones were achieved. Installation of in‐chain ketones resulted in materials with improved adhesion of the materials and miscibility of mixed plastics relative to the unfunctionalized plastics. The introduction of ketone groups into the polymer backbone allows these materials to react with diamines, forming dynamic covalent polyolefin networks. This strategy allows for the upcycling of mixed plastic waste into reprocessable materials with enhanced performance properties compared to polyolefin blends. Mechanistic studies support the involvement of photoexcited nitroaromatics in consecutive hydrogen and oxygen atom transfer reactions.
Annual energy production (AEP) is commonly used in objective functions for wind farm layout optimization. AEP is proportional to wind farm power production integrated over an annual distribution of free‐stream wind conditions. Physics‐based estimates of wind farm power production typically rely on low‐fidelity engineering wake models that approximate the steady‐state wind farm flow field. AEP estimates are then obtained by performing independent simulations for discrete wind conditions and using rectangular quadrature to account for each condition's expected frequency of occurrence. Depending on the number of simulated discrete wind conditions, this numerical integral could be hampered by poor accuracy or high computational costs. The FLOWERS AEP model instead poses an analytical integral of the engineering wake model over the variable wind conditions, yielding a closed‐form, analytical function for wind farm AEP. This paper derives the analytical functions for FLOWERS AEP and its derivatives with respect to turbine position, which are useful for gradient‐based wind farm layout optimization, in nondimensional form. We then analyze the benefits of the FLOWERS AEP model over conventional reference models, focusing on its low cost, adequate wake loss predictions, and smooth design space. Although the FLOWERS approach is found to predict the exact value of AEP with some error relative to the reference model (within 14% on average), it dramatically reduces computation time by an order of magnitude, produces a qualitatively similar design space at relatively low resolution, and yields comparable optimal layouts. This significant speed improvement is critical in layout optimization applications, where determining an optimal layout in an efficient manner is more important than precise AEP prediction.
The efficiency potential for single‐junction photovoltaics (PV) is described by the detailed balance model, which requires the elimination of nonradiative recombination and perfect minority carrier collection. Improvements in GaAs, Si, and perovskite PV follow this model. It might be more complex for CdTe, a leading thin‐film PV technology. While lifetime, passivation, and doping goals for 25% efficient CdTe solar cells are largely reached, voltage is ≈20% below the detailed balance limit. Why is that? In Se‐alloyed CdSexTe1‐x (Se is required for >20% efficiency) additional losses can occur due to electrostatic and bandgap fluctuations and due to electronic trap states. To understand mechanisms limiting CdSeTe solar cell performance and to suggest improvements, carrier dynamics, and transport in CdSexTe1‐x with variation in Se composition and as doping is analyzed. It is shown that trapping, likely due to anion‐site defects and their complexes, is correlated with low charge carrier mobility of 0.1–0.6 cm² (Vs)⁻¹. Even with 1000 ns charge carrier lifetimes, carrier diffusion length is less than the absorber thickness, reducing efficiency to ≈23%. Device simulations are used to analyze the performance of CdSexTe1‐x solar cells; thermodynamic models are not sufficient for absorbers with electronic disorder and trapping.
In hybrid metal halide perovskites, chiroptical properties typically arise from structural symmetry breaking by incorporating a chiral A-site organic cation within the structure, which may limit the compositional space. Here we demonstrate highly efficient remote chirality transfer where chirality is imposed on an otherwise achiral hybrid metal halide semiconductor by a proximal chiral molecule that is not interspersed as part of the structure yet leads to large circular dichroism dissymmetry factors (gCD) of up to 10⁻². Density functional theory calculations reveal that the transfer of stereochemical information from the chiral proximal molecule to the inorganic framework is mediated by selective interaction with divalent metal cations. Anchoring of the chiral molecule induces a centro-asymmetric distortion, which is discernible up to four inorganic layers into the metal halide lattice. This concept is broadly applicable to low-dimensional hybrid metal halides with various dimensionalities (1D and 2D) allowing independent control of the composition and degree of chirality.
2D materials, particularly transition metal dichalcogenides (TMDCs), have shown great potential for microelectronics and optoelectronics. However, a major challenge in commercializing these materials is the inability to control their doping at a wafer scale with high spatial fidelity. Interface chemistry is used with the underlying substrate oxide and concomitant exposure to visible light in ambient conditions for photo‐dedoping wafer scale MoS2. It is hypothesized that the oxide layer traps photoexcited holes, leaving behind long‐lived electrons that become available for surface reactions with ambient air at sulfur vacancies (defect sites) resulting in dedoping. Additionally, high fidelity spatial control is showcased over the dedoping process, by laser writing, and fine control achieved over the degree of doping by modulating the illumination time and power density. This localized change in MoS2 doping density is very stable (at least 7 days) and robust to processing conditions like high temperature and vacuum. The scalability and ease of implementation of this approach can address one of the major issues preventing the “Lab to Fab” transition of 2D materials and facilitate its seamless integration for commercial applications in multi‐logic devices, inverters, and other optoelectronic devices.
Determining the electronic levels associated with polarons, the fundamental charge carriers in organic semiconductors, is key to understanding the charge transport properties of these materials. Recent findings challenge the traditional view of these electronic levels by highlighting the importance of intra‐molecular Coulomb interactions in polarons. Experimental evidence was previously presented for a revised model of the negative polaron in the case of the polymer semiconductor poly(NDI2OD‐T2); there, the addition of an excess electron was seen to lead to the emergence of a singly occupied state within the energy gap of the undoped material and an unoccupied state above the edge of the conduction states. Here, focus is on a small‐molecule semiconductor, C60, and spectral evidence is provided of a similar picture for the new states appearing upon polaron formation. Specifically, direct and inverse photoemission spectroscopy is used to investigate the density of states in C60 films n‐doped with two dimeric dopants. The Coulomb interaction energy (Hubbard U) of the C60 anion is experimentally determined to be ≈1.1 eV, a value that aligns closely with theoretical predictions.
Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.
The use of membrane-forming curing compounds on fresh concrete has been widely adopted by many States’ Departments of Transportation as it is feasible where there is a deficiency of water, on sloping surfaces where curing with water is challenging, and in cases where large areas like pavement have to be cured. However, the evaluation of the curing compound application effectiveness is difficult because most of the evaluation test methods are not performed during the early age of the concrete. Moreover, the ASTM C156 standards test of water retention for the qualification of curing compounds has met criticism as the moisture retention is performed only on the mortar specimens, with a fixed application rate and curing condition. Therefore, in this study, the embedded resistance technique was used as a test replacement for the moisture retention test to assess concrete curing. The findings from this study showed that a correlation can be found between the moisture retention test and the embedded resistance test. Based on the findings, the embedded resistance test could be a suitable replacement for the moisture loss test, because the test is much simpler and quicker to be performed both in the lab and in the field.
Onsite production of gigawatt-scale wind- and solar-sourced hydrogen (H2) at industrial locations depends on the ability to store and deliver otherwise-curtailed H2 during times of power shortages. Thousands of tonnes of H2 will require storage in regions where subsurface storage is scarce, which may only be possible using liquid organic H2 carriers. We evaluate aboveground system with a focus on providing technical insights into toluene/methylcyclohexane (TOL/MCH) storage systems in locations suitable for gigawatt-scale wind- and solar-powered electrolyzer systems in the United States. Here we show that the levelized cost of storage, at a national median of US dollar $1.84/kg-H2 is spatially heterogeneous, causing minor impact on the cost of H2 supply in the Midwest, and significant impact in Central California and the Southeast. While TOL/MCH may be the cheapest aboveground bulk storage solution evaluated, upfront capital costs, modest energy efficiency, reliance on critical materials and pre-sulfided catalysts, and greenhouse gas emissions from heating are opportunities for further development.
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