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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Importance of Nonequilibrium to Equilibrium Transition Pathways for the Efficiency and Stability of Organic Solar Cells

Controlled morphology of solution-processed thin films have realized impressive achievements for non-fullerene acceptor (NFA)–based organic solar cells (OSCs). Given the large set of donor–acceptor pairs, employing various processing conditions to realize optimal morphology for high efficiency and stable OSCs is a strenuous task. Therefore, comprehensive correlations between processing conditions and morphology evolution pathways have to be developed for efficient performance and stability of devices. Within the framework of the blend system, crystallization transitions of NFA molecules are tracked utilizing the first heating scan of differential scanning calorimeter (DSC) measurement correlating with respective morphology evolution of blend films. Real-time dynamics measurements and morphology characterizations are combined to provide optimal morphology transition pathways as NFA molecules are shown to be released from the mixed phase to form balanced ordered packing with variant processing conditions. Polymer:NFA films are fabricated using blade coating incorporating solvent additive or thermal annealing as processing conditions as a correlation is formulated between performance and stability of solar cells with morphology transition pathways. In conclusion, this work demonstrates the significance of processing condition-controlled transition pathways for the realization of optimal morphology leading to superior OSC devices.

14 SOLAR ENERGY↗
DOE OSTI2026

Evolution of size-selected Pt cluster catalysts on prototypical oxide supports

The current quest for new pathways into sustainable, efficient and durable energy conversion technologies makes the used for a fundamental understanding of the atomic-scale phenomena underlying catalytic processes ever more pressing. In this context, characterizing catalyst particles in situ provides valuable information about the evolution of their composition, structure, oxidation state and charge state during an ongoing process. To disentangle the influence of individual parameters – temperature, pressure, gas composition, cluster size, as well as support acidity, redox state and defect density – it is crucial to control them precisely and separately in experiments. At the example of size-selected Pt n clusters – i.e. sub-nm particles defined to the exact number of atoms – on flat oxide supports, we follow their rich evolution phenomena via (synchrotron-based) X-ray photoelectron spectroscopy (XPS) and scanning tunnelling microscopy (STM) during temperature ramps and in various gas environments. Here, we present our experience with these highly defined, yet complicated-to-create samples in ultra-high vacuum (UHV) and at mbar pressures. We discuss their stability during transport to synchrotrons and under reaction conditions on three prototypical oxide supports and show the various phenomena that can be disentangled. Ptn clusters on the non-reducible silicon dioxide, SiO 2 , remain size-selected and show remarkable stability. Doping strongly influences the size-dependent binding energy shifts and changes the Pt response to oxidative and reaction conditions, which we attribute to different cluster geometries: p-type doping leads to wetting, enhanced sinter resistance and a diminished response to oxidative environments, compared to clusters on n-type doped samples. We compare the system with our previous findings of a similar change in dimensionality for Pt 20 clusters on the reducible ceria, CeO 2 (111), support, induced by modulation of its O vacancy density. The Pt n /CeO 2 system is particularly interesting for strategies to stabilize and redisperse Pt clusters dynamically. Finally, we study the evolution of Pt n clusters on another reducible oxide support, magnetite, Fe 3 O 4 (001), in 0.1 mbar alternating redox conditions at RT and elevated temperature. In analogy to findings previously reported for Pt/TiO 2 (110), the clusters either become encapsulated by a thin oxide film via strong metal–support interaction (SMSI) or deeply buried in the magnetite. Overall, our approach of following the evolution of size-selected clusters on oxide supports leads to fundamental atomic-scale insights on nano-scale catalyst materials, on our path to sustainable, dynamic and self-repairing catalysts.

Falling, Lorenz J. [Technical Univ. of Munich (Ger↗
DOE OSTI2021

How Cooperative Engagement Programs Strengthen Sequencing Capabilities for Biosurveillance and Outbreak Response

The threat of emerging and re-emerging infectious diseases continues to be a challenge to public and global health security. Cooperative biological engagement programs act to build partnerships and collaborations between scientists and health professionals to strengthen capabilities in biosurveillance. Biosurveillance is the systematic process of detecting, reporting, and responding to especially dangerous pathogens and pathogens of pandemic potential before they become outbreaks, epidemics, and pandemics. One important tool in biosurveillance is next generation sequencing. Expensive sequencing machines, reagents, and supplies make it difficult for countries to adopt this technology. Cooperative engagement programs help by providing funding for technical assistance to strengthen sequencing capabilities. Through workshops and training, countries are able to learn sequencing and bioinformatics, and implement these tools in their biosurveillance programs. Cooperative programs have an important role in building and sustaining collaborations among institutions and countries. One of the most important pieces in fostering these collaborations is trust. Trust provides the confidence that a successful collaboration will benefit all parties involved. With sequencing, this enables the sharing of pathogen samples and sequences. Obtaining global sequencing data helps to identify unknown etiological agents, track pathogen evolution and infer transmission networks throughout the duration of a pandemic. Having sequencing technology in place for biosurveillance generates the capacity to provide real-time data to understand and respond to pandemics. We highlight the need for these programs to continue to strengthen sequencing in biosurveillance. By working together to strengthen sequencing capabilities, trust can be formed, benefitting global health in the face of biological threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

From Micro-environments to Macroscopic Effects: How the Alkaline Hydrogen Evolution Reaction Drives Cu Cathodic Corrosion

Cathodic corrosion of copper (Cu) has posed a significant challenge for over a century, impeding various technological progresses such as electrochemical conversion of CO 2 (eCO 2 RR) into fuels and other value-added carbon products. Here, in this study, employing a combined Density Functional Theory (DFT) and kinetic Monte Carlo (kMC) simulation approach, we delve into the atomistic level mechanism driving this phenomenon in Cu. Our hypothesis posits the pivotal role of alkaline hydrogen evolution reaction (HER) in facilitating cathodic corrosion in Cu. We rigorously develop a pH-dependent hydroxide (OH) adsorption mechanism and calculate the equilibrium OH coverage (𝜃 OH ) at varying pH levels, the thermodynamic stability of subsurface oxygen (O sub ), as well as the Cu-vacancy mediated diffusion of subsurface oxygens (O sub ). Through comprehensive analysis, we establish correlation among various microenvironments, including oxygen diffusion in subsurface layers, pH-dependent OH adsorption, and Cu dissolution into the electrolyte as (Cu-OH) complexes. Furthermore, our investigation explores the correlation between surface coordination environment of active sites and cathodic corrosion of Cu. Finally, by integrating DFT-derived thermodynamic data into a kMC model, we successfully predict the formation of experimentally observed corrosion pits on Cu-surfaces. This combined approach not only advances our fundamental understanding of Cu cathodic corrosion but also offers insights crucial for developing effective corrosion mitigation strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Open Cluster Chemical Abundances and Mapping Survey. V. Chemical Abundances of CTIO/Hydra Clusters Using The Cannon

Open clusters are key chemical and age tracers of Milky Way evolution. While open clusters provide significant constraints on galaxy evolution, their use has been limited due to discrepancies in measuring abundances from different studies. We analyze medium-resolution ( R ~ 19,000) Cerro Tololo Inter-American Observatory/Hydra spectra of giant stars in 58 open clusters using The Cannon to determine [Fe/H], [Mg/Fe], [Si/Fe], [Al/Fe], and [O/Fe]. This work adds an additional 55 primarily southern hemisphere open clusters calibrated to the Sloan Digital Sky Survey/Apache Point Observatory Galactic Evolution Experiment DR16 metallicity system. This uniform analysis is compared to previous studies [Fe/H] measurements for 23 clusters and we present spectroscopic metallicities for the first time for 35 open clusters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Composition, Activity, and Stability of IrO x Oxygen Evolution Reaction Electrocatalysts

The oxygen evolution reaction (OER) is integral to several electrochemical energy conversion and storage technologies, including carbon dioxide reduction to value added fuels, nitrogen reduction to ammonia, reversible fuel cells, rechargeable metal−air batteries, and water electrolysis to produce hydrogen. Iridium oxide (IrO x ) is widely recognized as the benchmark OER catalyst for acidic environments. Despite widespread use of IrO x catalysts, most notably in proton-exchange membrane water electrolyzers (PEMWEs), a comprehensive understanding of the physicochemical properties of commercial catalysts and the impact of these properties on both the activity and stability of these catalysts is lacking. Here, we study commercial IrO x catalysts with different physicochemical properties, three nominally considered amorphous and three rutile, to elucidate how structural and compositional variations affect OER activity and stability. Utilizing standardized aqueous electrochemical protocols, time-resolved dissolution quantification using inductively-coupled plasma mass spectrometry, and physicochemical characterization, including multiple synchrotron X-ray techniques, we systematically correlate catalyst properties with OER performance and degradation behavior aided by principal component analysis (PCA). Our results demonstrate the general trend of amorphous IrO x having higher intrinsic activity but limited stability and crystalline rutile IrO 2 having lower activity but enhanced stability against dissolution. The trends within the amorphous and rutile catalyst groups correlate with inherent material properties, including phase composition and structure, crystallinity, particle size, surface area, and surface structure/chemistry. Notably, we identify a rutile catalyst with the largest crystallite/ domain sizes, moderate surface area, a small fraction of hydrous phase, and a favorable pore structure (trimodal distributions of pore sizes ranging from 2−5 nm) that exhibits the best balance between activity and stability among the six catalysts studied here. These findings illustrate a fundamental structure-governed trade-off between activity and stability and highlight the critical role of surface chemistry modification and structure engineering in IrO x catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ruthenium-lead oxide for acidic oxygen evolution reaction in proton exchange membrane water electrolysis

Developing an active and stable anode catalyst for the proton exchange membrane water electrolyzer (PEM-WE) is a critical objective to enhance the economic viability of green hydrogen technology. However, the expensive iridium-based electrocatalyst remains the sole practical material with industrial-level stability for the acidic oxygen evolution reaction (OER) at the anode. Ruthenium-based catalysts have been proposed as more cost-effective alternatives with improved activity, though their stability requires enhancement. The current urgent goal is to reduce costs and noble metal loading of the OER catalyst while maintaining robust activity and stability. Here, in this study, we design a Ru-based OER catalyst incorporating Pb as a supporting element. This electrocatalyst exhibits an OER overpotential of 201 mV at 10 mA.cm -2 , simultaneously reducing Ru noble metal loading by similar to 40%. Normalization of the electrochemically active surface area unveils improved intrinsic activity compared to the pristine RuO 2 catalyst. During a practical stability test in a PEM-WE setup, our developed catalyst sustains stable performance over 300 h without notable degradation, underscoring its potential for future applications as a reliable anodic catalyst.

Electrocatalysis↗
DOE OSTI2020

Multiplex Evolution of Antibody Fragments Utilizing a Yeast Surface Display Platform

Advances in high-throughput synthetic biology technologies based on the CRISPR/Cas9 system have enabled a comprehensive assessment of mutations conferring desired phenotypes, as well as a better understanding of genotype-phenotype correlations in protein engineering. Engineering antibodies to enhance properties such as binding affinity and stability plays an essential role in therapeutic applications. Here we report a method, multiplex navigation of antibody structure (MINAS), that combines a CRISPR/Cas9-based trackable editing method and fluorescent-activated cell sorting (FACS) of yeast-displayed libraries. We designed mutations in all of the complementarity-determining and framework regions of a well-characterized scFv antibody and mapped the contribution of these regions to enhanced properties. We identified specific mutants that showed higher binding affinities up to 100-fold compared to the wild-type. This study expands the applicability of CRISPR/Cas9-based trackable protein engineering by combining it with a surface display platform.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A reflection on lithium-ion battery cathode chemistry

Abstract Lithium-ion batteries have aided the portable electronics revolution for nearly three decades. They are now enabling vehicle electrification and beginning to enter the utility industry. The emergence and dominance of lithium-ion batteries are due to their higher energy density compared to other rechargeable battery systems, enabled by the design and development of high-energy density electrode materials. Basic science research, involving solid-state chemistry and physics, has been at the center of this endeavor, particularly during the 1970s and 1980s. With the award of the 2019 Nobel Prize in Chemistry to the development of lithium-ion batteries, it is enlightening to look back at the evolution of the cathode chemistry that made the modern lithium-ion technology feasible. This review article provides a reflection on how fundamental studies have facilitated the discovery, optimization, and rational design of three major categories of oxide cathodes for lithium-ion batteries, and a personal perspective on the future of this important area.

Science & Technology - Other Topics↗
DOE OSTI2021

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗
DOE OSTI2025

Informing ARC divertor design and plasma facing material selection through integrated modeling

This INFUSE 2023 project between UCLA and Commonwealth Fusion Systems used computer modeling to test whether tungsten materials can survive in CFS's ARC fusion reactor divertor. The team simulated plasma conditions and material responses, finding that tungsten-rhenium alloys resist grain growth better than pure tungsten, and that hydrogen buildup depends more on particle flux than temperature. The work helps CFS design durable plasma-facing components for their fusion power plant.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accelerated Irradiation Effects Qualification in the AMMT Program

This presentation discusses the ongoing and upcoming efforts to use combined neutron and ion irradiation experiments for materials qualification within the Advanced Materials and Manufacturing Technologies (AMMT) program for the 2024 AMMT program review meeting. The microstructure evolution of additively manufactured 316 L and 316 H stainless steels are discussed, as well as the development of the AMMT challenge problem for this topic.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗
DOE OSTI2021

A linked-scale coupled model of mass erosion and redistribution in plasma-exposed micro-foam surfaces

Surface evolution due to exposure to harsh environments is of importance in many scientific and technological applications. In plasma-exposed materials, the surface receives charged particles from the plasma, leading to a series of processes that drive the system far from equilibrium and may lead to the severe deterioration of the surface properties. Although surface morphological changes are driven by atomic collisions taking place over picoseconds and nanometers, these processes result in mass loss and redistribution of matter over much larger length and time scales. This necessitates a multi-scale approach capable of capturing the range of processes linking primary atomic collision events with engineering-level surface geometry changes. In this paper, we develop a computational model to simulate the morphological evolution and effective erosion rate of micro-architected tungsten foams during low-energy plasma ion bombardment. Furthermore, the model acts on several length scales, with the energy and angular dependence of the sputtering yield of flat tungsten surfaces determined using the SRIM code based on the binary collision approximation. This information is introduced into a low-fluence, short-term Monte Carlo raytracing model, and further into a high-fluence, long-term particle transport model. In the latter, material particles representing billions of atoms are described in a digitized 3-D representation of the foam structure from X-ray tomography data, and are sputtered off and redeposited using the atomistic information. We show that the redeposition of sputtered atoms leads to partial self-healing in the bottom layers with a sharp reduction in the sputtering coefficient of low density foams, roughly 25% of the solid W value. This is in qualitative agreement with recent experiments on low porosity W structures. At high fluence, the foam structure degrades considerably as there are fewer ligaments available to recapture sputtered atoms and, consequently, the sputtering rate increases again.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Evolution of Wayfinding Within Airports

The process of navigating within airports has evolved over the years, with various technologies emerging. Historically, wayfinding began with static signage and airport staff members before progressing into digital signs, interactive kiosks and displays. In recent years, wayfinding has continued along its digital path through the use of indoor positioning technology, mobile applications, and even robot guides. The future of wayfinding will likely be heavily linked to further digital developments such as facial recognition and autonomous vehicle navigation. This paper delves into the history of interior wayfinding in airports, its present state, and the anticipated future. Key wayfinding technologies are discussed in detail with an emphasis on smartphone applications. Other considerations such as traveler stress, legal issues, pandemic safety, and language barriers are included.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

The Evolution of Wayfinding Within Airports

The process of navigating within airports has evolved over the years, with various technologies emerging to complement static signage. Historically, wayfinding began with static signage and airport staff members providing personal guidance, before progressing into digital signs, interactive kiosks, and displays. In recent years, wayfinding has continued along its digital path using mobile applications, indoor positioning technology, and even robot guides. With ever- larger airport facilities and a growing number of travelers, the future of wayfinding will likely be heavily linked to further digital developments such as facial recognition, augmented-reality technology, and autonomous vehicle navigation. This report delves into the history of interior wayfinding in airports, its present state, and the anticipated future. Key wayfinding technologies are discussed in detail, with an emphasis on emerging smartphone applications. Other considerations such as traveler stress, legal issues, pandemic safety, and language barriers are included. A wayfinding framework is proposed, with static wayfinding technologies serving as the base upon which dynamic and personalized digital technologies are built. In this framework, electronic wayfinding technologies do not replace - but rather augment - traditional methods. These technologies can be integrated into existing wayfinding systems for a seamless traveler experience.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗
DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗