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At least 829 records · Page 46

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗

Prototype Integrated Hydrogen Fuel Cell Powered Data Center (Cooperative Research and Development Final Report)

Data centers are the backbone of the modern economy-from the server rooms that power small- to medium-sized organizations, to the enterprise-class data centers that support American corporations, and the server farms that run cloud computing services. Rather than a traditional grid-centric data center approach, work under the CRADA will be directed towards implementing a proof-of-concept "hydrogen-based" data center utilizing hydrogen fuel cells, electrolyzers, and solar photovoltaics as key building blocks. This integrated proof-of-concept builds on preliminary work done by HPE and its partners Mercedes-Benz Research & Development North America, Inc. (MBRDNA) and Power Innovations, to dramatically simplify the electrical infrastructure in the data center, leverage the latest automotive-scale hydrogen fuel cell technologies, and tightly couple renewably generated DC power directly to the Information Technology (IT). While some limited aspects of this concept have been demonstrated previously the entire integrated proof of concept proposed here has not yet been realized.

08 HYDROGEN↗

A regional inter-disciplinary partnership focusing on the development of a carinata-centered bioeconomy

Brassica carinata or Ethiopian mustard, a non-edible oilseed brassica, is a low carbon, purpose-grown, and none-to-low indirect land-use change bioenergy feedstock for the production of drop-in sustainable aviation fuel, biodiesel, renewable diesel, and a suite of value-added coproducts. Carinata oil converted to drop-in fuel using an American Society for Testing and Materials approved Catalytic Hydrothermolysis process has been successfully tested in commercial and military aviation. Carinata meal, the residue after oil extraction, is a high-protein feed supplement for livestock, poultry, and swine, and can also yield specialty products. The Southeast Partnership for Advanced Renewables from Carinata (SPARC) is a public–private partnership formed with a twofold mission: (1) Removing physical, environmental, social, and economic constraints that prevent regional intensification of carinata production as a low-carbon feedstock for renewable fuel and coproducts and (2) demonstrating enhanced value across the entire value chain by mitigating risk to farmers and other stakeholders. The partnership's goal is to energize the US bioeconomy through sustainable agriculture and thus contribute to energy security and economic diversification. SPARC relies on a combination of cutting-edge multidisciplinary research and active industry engagement to facilitate adoption of the crop. This involves informing stakeholders along the entire supply chain, from producers to end-users, policymakers, influencers, and the public, about the opportunities and best practices related to carinata. This article provides context and background concerning carinata commercialization as a winter cash crop in the Southeast US for renewable fuels and bioproducts. The advances made to date in the areas of feedstock development, fuel and coproduct development, meal valorization, supply chain logistics, and stakeholder engagement are outlined.

09 BIOMASS FUELS↗

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity

Abstract Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a semi-continuous algal cultivation (SAC) to sustain optimal cell growth and minimize mutual shading. An aggregation-based sedimentation (ABS) strategy is then designed to achieve low-cost biomass harvesting and economical SAC. The ABS is achieved by engineering a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which increases cyanobacterial cell surface hydrophobicity and enables efficient cell aggregation and sedimentation. SAC unleashes cyanobacterial growth potential with 0.1 g/L/hour biomass productivity and 0.2 mg/L/hour limonene productivity over a sustained period in photobioreactors. Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 g/m 2 /day, bringing the minimum biomass selling price down to approximately $281 per ton.

09 BIOMASS FUELS↗

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗

Controlling Mass Transport in Direct Carbon Dioxide Zero-Gap Electrolyzers via Cell Compression

The development of high-performance CO 2 electrolyzers is crucial for accelerating the sustainable production of fuels and chemicals integrated with renewable energy sources. Here, we introduce a methodology to actively control mass transport inside a realistic zero-gap membrane electrode assembly of a CO 2 electrolyzer by varying the gasket thickness, which consequently changes the cell compression. This allows control over the thickness and porosity of the gas diffusion electrodes, influencing the overall electrolyzer performance, as demonstrated using Ag-deposited electrodes. At low operating voltages (<2.9 V), both high- and low-compression electrolyzers exhibit similar faradaic efficiencies and partial current densities for CO formation. However, at high voltages, the low-compression electrolyzer with high electrode porosity demonstrates superior CO selectivity and activity with suppressed H 2 formation. These experimental results are validated by the computational membrane electrode assembly (MEA) model developed by using the measured in situ electrode thicknesses and electrode porosities. Additionally, liquid electrolyte saturation at the catalyst layer is found to play a dominant role in determining the mass transport, resulting in a decreased electrolyzer performance with low electrode porosity. Finally, the systematic investigation in this study improves the understanding of the transport dynamics in MEA-based devices and provides insights into optimizing device design parameters for industry-relevant CO 2 electrolysis.

30 DIRECT ENERGY CONVERSION↗

High Penetration Power Electronics Grid: Modeling and Simulation Gap Analysis

Increased penetration of power electronics in the grid is happening through development of high-power drives (like in Type 3 or 4 wind turbines, industrial drives, etc.), high-voltage direct current (HVdc) systems, flexible alternating current transmission systems (FACTS), energy storage systems (ESSs), inverter-based renewables like solar and wind, electric vehicle chargers, and other technologies. Ongoing research and development in new power electronic technologies including, but not limited to, solid-state power substations (SSPS), extreme fast charging (XFC), solid-state transformers, and multi-port power electronics that integrate multiple sources/loads will further increase penetration levels. To ensure stakeholders can integrate high penetration of power electronic technologies safely and reliably requires tools and methods to assess and evaluate their impact on the grid. Objectives: This report surveys, assesses, and analyzes commercially available and open-source tools that can support the assessment and evaluation of power electronics in future grids with high penetration levels. The study includes aspects that range from power flow analysis to dynamics evaluation (including hardware-in-the-loop – HIL testing) for such systems. The challenges and gaps associated with the current generation of toolsets available to assess the technical impact of introducing high penetration of power electronics are reported. The method is summarized in Figure ES-1.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High Solids Loading Aqueous Slurry Formation of Corn Stover Before Pretreatment in a Fed-batch Bioreactor

With the increase on population the world will depend on renewable sources to meet the increasingly energy needs. Use of lignocellulosic biomass as a renewable source has been proven efficient for conversion to cellulosic ethanol and capable of contributing to achieve the threshold on energy demand while reducing greenhouse gases in 90% when compared with fossil fuels (Wang et al., 2007, 2012). However, the processing of biomass encounters limitations in feeding and flow within biorefineries due to the system plugging by compaction and slurry high yield stress, preventing transport of biomass materials and in some cases unexpected plant shutdowns that results in high operational costs (dos Santos et al., 2021; Ximenes et al., 2021). Different solutions for biomass handling and slurry formation from densified materials like pellets have been studied. Cellulosic biomass residues are typically processed in pretreatment reactors to which acid or base is added (Humbird et al., 2002). Other pretreatments such as liquid hot water (LHW) and steam explosion that act without the addition of chemicals use pressures above the saturation vapor of water, to disrupt biomass structure (Ruiz et al., 2021). Although these methods are widely known, the use of pretreatments like acid digestion and LHW present challenges like waste disposal and could be energy inefficient (Mosier et al., 2005). Alternatively other approaches like enzymatic liquefaction have been applied for biomass transformation into slurries with promising results and without the use of pretreatments (dos Santos et al., 2021). Nevertheless, enzymatic liquefaction implementation faces difficulties due to the recalcitrant properties of biomass, its variability, and the release of enzyme inhibitors. While it has been proven that chemical composition properties in biomass have effects on enzyme inhibition (Huang et al., 2022; Kim et al., 2011; Zhai et al., 2018), hindering the efficiency of the liquefaction, not ample research has been conducted in understanding the physical properties as particle size, porosity, water adsorption retention and their effect in the ability to form a slurry at high solids concentration (Yan et al., 2020). In order to improve lignocellulosic biomass handling and formation of biomass slurries, enzyme assisted liquefaction for slurry creation from corn stover at solids loadings up to 30% is reported in this work. Two different kinds of biomass (pelleted corn stover and cobs) were liquefied in a fed-batch process using commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU or 3 FPU per gram of dry solids in 10 mM sodium citrate buffer solution (pH 4.8). Pellets were fed into a 1 L stirred bioreactor according to a predefined fed-batch protocol over the first 5 hours until reaching 30% of solids loading. After 6, 24 and 96 hours, samples were taken and characterized with respect to their sugar composition, rheology and water absorption. Successful slurry creation with dramatically reduced yield stress was achieved for corn stover for both assessed enzymes. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3 FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme. Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours. Yield stress decreased when residence time increased with an enhanced fluidity noted for higher enzyme concentrations. A profile for 6, 24 and 96h of yield stress measurements is presented.

Gutierrez, Diana↗

Exploring sustainable electricity system development pathways in South America’s MERCOSUR sub-region

South America has abundant natural water and energy resources, and exploiting these resources to achieve a clean energy future is central to the continent’s economic and sustainable development objectives for the next several decades. Designing pathways to achieving this clean energy future requires better understanding the structural, techno-economic, and policy forces that may influence the future development of the electricity sector in the region. Here, we focus on an interconnected electricity system of five South American countries – Argentina, Brazil, Chile, Paraguay, and Uruguay – which represent major electricity generation, consumption, and trade dynamics in the region. We explore the implications of various forces that could shape the future composition of the power sector in the sub-region, including: evolving renewable energy cost and performance, natural gas prices, cross-border interconnection facilities, early retirement of installed hydropower, and different decarbonization goals. We use a model framework based on a power system planning platform (GridPath) to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results in a Reference scenario indicate that the electricity system can maintain a relatively clean energy portfolio by leveraging existing hydropower capacity and integrating increasingly cost-competitive wind and solar power. However, dependence on natural gas in the region is likely to remain high. A low-carbon electricity system can cost-effectively be achieved through policy interventions (e.g., renewable portfolio standards) and by diversifying investments in wind, solar, battery storage, and some new hydropower capacity. We also find that existing hydropower is critical for maintaining reliable future grid operations. Enhanced regional electricity trade, mostly based on existing interconnection capacities with nominal investment in new transmission, can significantly benefit the clean energy transition in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Toward efficient single-atom catalysts for renewable fuels and chemicals production from biomass and CO 2

Transformation of biomass and CO 2 into renewable value-added chemicals and fuels has been identified as a promising strategy to fulfill high energy demands, lower greenhouse gas emissions, and exploit under-utilized resources. Cost-effective and performance-efficient catalysts are of great importance to lowering the conversion cost of biomass and CO 2 . Significant progress has been made to advance the catalyst design for these processes, with metal catalysts playing a critical role in many involved catalytic reactions. Traditional nanoparticle-based metal catalysts still require improvement in metal utilization rates, stability, and selectivity tunability. Single-atom catalysts, which have maximum atomic efficiency and a uniform and tunable metal center, as well as an adjustable metal-support interaction, provide potential opportunities to boost catalyst efficiency and thermal stability. Their well-defined and uniform structure also provides advantages to fundamental studies for understanding of the intrinsic reaction mechanism and site requirement in biomass and CO 2 conversion. In this article, we summarize and highlight the recent advances in converting biomass and CO 2 to renewable fuels and chemicals using single-atom catalysts. We discuss the design principles of single-atom catalysts and their potential applications to biomass and CO 2 upgrading as well as the origins of catalytic activity. Moreover, we compare the catalytic efficiency of various catalysts reported thus to provide a fair assessment of these catalysts. Finally, perspectives are given on the interesting fields that may guide future studies.

09 BIOMASS FUELS↗

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m −3 ) and negligible self‐discharge that makes them uniquely suited as compact, stand‐alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi‐cycle efficiency and high‐levelized cost of storage. In this study, a model is developed to predict the pulverization limit or R crit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy‐efficient manufacturing process (solid‐state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of R crit on hydration and dehydration kinetics is also investigated.

25 ENERGY STORAGE↗

DEEP Solar: Data DrivEn Modeling and Analytics for Enhanced System Layer ImPlementation

Realizing the SETO 2030 mission of reducing solar energy costs to 3-5 c/kWh will require innovative enabling research on effective, cost-efficient integration of local PV within distribution systems. However, the intermittent and variable nature of PVs compels operators to impose conservative hosting capacity constraints. Given the extremely high variability of (intermittent and unpredictable) solar energy generation, relaxing the capacity constraints (which are currently around 15%) and achieving 100% or greater integration of renewables will require a fundamental transformation of the power grid via the utilization of exponentially larger amounts of AMI enabled fine-grained data. To address the challenges in increasing the penetration of renewable energy based DERs, this project envisions an Enhanced System Layer (ESL) at the distribution network level that is reliable, cost-effective and scalable to millions of Distributed Energy Resources (DERs)/devices. This includes developing: 1) Transformative and highly scalable machine learning based predictive analytics tools that plug into distribution system planning and provide real-time situational awareness at the distribution level for short and long-term operational planning. The tools will be built using novel data-driven energy models of millions of active nodes with AMI, 2) Adaptive stochastic analysis and optimization algorithms for real-time grid operations, 3) Dynamic Scenario Analysis using parallel Cloudenabled implementations with < 1 minute computational cycle times.

14 SOLAR ENERGY↗

Corn stover‐derived porous carbon for asymmetric supercapacitors

In this investigation, hydrothermal liquefaction‐derived hydrochar from pulverized corn stover (avg. particle size 1.12 mm and ash content 6.75 wt%) is chemically activated with aqueous KOH in the presence of Pluronic F127 surfactant and thermally treated further up to 800°C to generate porous carbon (POC) with higher specific surface area and porosity. POC obtained under different processing conditions is thoroughly characterized by Brunauer‐Emmett‐Teller surface area analyzer, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy. Metallic impurity present in POC is characterized by inductively coupled plasma mass spectrometry. Higher specific surface area POC is observed with the use of the surfactant during the activation process. Fully characterized POC is used with (Mn, Ti)‐mixed oxide electrode to fabricate asymmetric supercapacitor (ASC). Specific capacitance of ASC is measured by cyclic voltammetry (CV) technique using Gamry G‐300 potentiostat/galvanostat/ZRA. CV plots are obtained with different voltage scan rates whereas galvanostatic charge‐discharge plots are studied by varying the current density. Renewable corn stover‐derived POC prepared using Pluronic F127/KOH activation method is found to be highly suitable as an electrode material because of higher capacitance and electrochemical stability over 100 charging‐discharging cycles.

25 ENERGY STORAGE↗

Sodium-ion Battery

Room temperature rechargeable sodium-ion batteries (NIBs) are one of the most promising candidates for large-scale energy storage and load leveling of renewable energy sources due to the abundance, low cost of Na resources, and their relatively high energy density. NIBs are primarily based on intercalation chemistry and are similar to Lithium-ion batteries (LIB). The rich knowledge gained in LIBs for the past 4 decades have accelerated the discovery and development of high energy density NIBs cathode and anode materials. The use of sustainable Na, Al current collector, and Mn and Fe based cathode materials is expected to stabilize the cost and demand for Li, Co, Ni and Cu.

Omenya, Fredrick O.↗

Sorbent Regeneration via Radiofrequency-Assisted Dielectric Heating for Direct Air Capture of CO 2

Direct air capture (DAC) of CO 2 is a negative emission technology that utilizes sorbents requiring a regeneration step for repeated ab(/d)sorption–desorption cycles. Here we report an unconventional approach to desorb captured CO 2 from a porous sorbent using radiofrequency (RF) irradiation for dielectric heating and targeted energy transfer, thus enabling modularity and promoting renewable energy input. Regeneration of composites of functional ionic liquid and metal–organic framework with high CO 2 capacity and enhanced transport is demonstrated under conditions relevant to DAC. RF-assisted dielectric heating at the megahertz frequency range shows effective absorption of electromagnetic energy and consequently rapid release of the captured CO 2 .

Ionic liquids↗

Exploring Sources of Surface Bias in HRRR Using New York State Mesonet

In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.

54 ENVIRONMENTAL SCIENCES↗