Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dynamic Timing Analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transport coefficient approach for characterizing nonequilibrium dynamics in soft matter

Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details. We introduce an approach for extracting the transport coefficient, denoted as $J(t)$, from the XPCS studies. This coefficient is a fundamental parameter in nonequilibrium statistical mechanics and is crucial for characterizing transport processes within a system. Our method unifies the Green–Kubo formulas associated with various transport coefficients, including gradient flows, particle–particle interactions, friction matrices, and continuous noise. We achieve this by integrating the collective influence of random and systematic forces acting on the particles within the framework of a Markov chain. We initially validated this method using molecular dynamics simulations of a system subjected to changes in temperatures over time. Subsequently, we conducted further verification using experimental systems reported in the literature and known for their complex nonequilibrium characteristics. The results, including the derived $J(t)$ and other relevant physical parameters, align with the previous observations and reveal detailed dynamical information in nonequilibrium states. This approach represents an advancement in XPCS analysis, addressing the growing demand to extract intricate nonequilibrium dynamics. Further, the methods presented are agnostic to the nature of the material system and can be potentially expanded to hard condensed matter systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Differential emission measure analysis of a limb solar flare on 2012 July 19

We perform Differential Emission Measure (DEM) analysis of an M7.7 flare that occurred on 2012 July 19 and was well observed by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamic Observatory. Using the observational data with unprecedented high temporal and spatial resolution from six AIA coronal passbands, we calculate the DEM of the flare and derive the time series of maps of DEM-weighted temperature and emission measure (EM). It is found that, during the flare, the highest EM region is located in the flare loop top with a value varying between ∼8.4 × 10{sup 28} cm{sup –5} and ∼2.5 × 10{sup 30} cm{sup –5}. The temperature there rises from ∼8 MK at about 04:40 UT (the initial rise phase) to a maximum value of ∼13 MK at about 05:20 UT (the hard X-ray peak). Moreover, we find a hot region that is above the flare loop top with a temperature even up to ∼16 MK. We also analyze the DEM properties of the reconnection site. The temperature and density there are not as high as that in the loop top and the flux rope, indicating that the main heating may not take place inside the reconnection site. In the end, we examine the dynamic behavior of the flare loops. Along the flare loop, both the temperature and the EM are the highest in the loop top and gradually decrease toward the footpoints. In the northern footpoint, an upward force appears with a biggest value in the impulsive phase, which we conjecture originates from chromospheric evaporation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Binary frequencies in a sample of globular clusters. II. Sample analysis and comparison to models

Binary stars are predicted to have an important role in the evolution of globular clusters, so we obtained binary fractions for 35 globular clusters that were imaged in the F606W and F814W with the Advanced Camera for Surveys on the Hubble Space Telescope. When compared to the values of prior efforts, we find significant discrepancies, despite each group correcting for contamination effects and having performed the appropriate reliability tests. The most reliable binary fractions are obtained when restricting the binary fraction to q⩾0.5. Our analysis indicates that the range of the binary fractions is nearly an order of magnitude for the lowest dynamical ages, suggesting that there is a broad distribution in the binary fraction at globular cluster formation. Dynamical effects also appear to decrease the core binary fractions by a factor of two over a Hubble time, but this is a weak relationship. We confirm a correlation from previous work that the binary fraction within the core–radius decreases with cluster age, indicating that younger clusters formed with higher binary fractions. The strong radial gradient in the binary fraction with cluster radius appears to be a consequence of dynamical interactions. It is often not present in dynamically young clusters, but is nearly always present in dynamically old clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Glassy dynamics in CuMn thin-film multilayers

Thin-film multilayered spin-glass CuMn/Cu structures exhibit glassy dynamics. The freezing temperature T f was measured for 40 layers of CuMn films of thickness L = 4.5 , 9.0 , and 20.0 nm, sandwiched between nonmagnetic Cu layers of thickness ≈ 60 nm. The Kenning effect, T f ∝ ln L , is shown to follow from power-law dynamics where the correlation length grows from nucleation as ξ ( t , T ) = c 1 a 0 ( t / τ 0 ) c 2 ( T / T g ) , leading to [ ( T f / T g ) c 2 ln ( t co / τ 0 ) ] + ln c 1 = ln ( L / a 0 ) . Here, T g is the bulk spin-glass temperature, c 1 and c 2 are constants determined from the spin-glass dynamics, t co is the time for the correlation length to grow to the film thickness, τ 0 is a characteristic exchange time ≈ ℏ / k B T g , and a 0 is the average Mn-Mn separation. For t ≥ t co , the magnetization dynamics are simple activated, with a single activation energy Δ max ( L ) / k B T g = ( 1 / c 2 ) [ ln ( L / a 0 ) - ln c 1 ] that does not change with time. Values for all these parameters are found for the three values of L explored in these measurements. We find experimentally Δ max ( L ) / k B = 907 , 1246, and 1650 K, respectively, for the three CuMn thin-film multilayer thicknesses, consistent with power-law dynamics. Here, we perform a similar analysis based on the activated dynamics of the droplet model and find a much larger spread for Δ max ( L ) than found experimentally.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Virtual Cable Impedance based Load Sharing in a Microgrid for Parallel Connected Grid Forming Converters

This paper presents a novel approach to power sharing between direct connected grid-forming converters, utilizing virtual cable impedance and droop-based outer loop control. To enhance stability, resistive droop is implemented, while virtual cable impedance with non-zero resistive and inductive components ensures improved power sharing. The inner loop controller employs a Lyapunov energy function to achieve superior dynamic performance. The proposed control architecture is validated through comprehensive modeling and real-time processor-in-the-loop simulations, demonstrating its robustness and efficiency under various operating conditions. The results highlight the potential of this control strategy to improve the reliability and efficiency of renewable energy systems. Additionally, a comparative analysis with traditional methods underscores the advantages of the proposed approach in terms of stability and performance. The proposed control architecture offers a scalable and flexible solution for grid-forming converters, enabling seamless integration of renewable energy sources. Its robustness and adaptability make it an attractive solution for real-world applications. Furthermore, the approach can be extended to other power electronic systems, enhancing overall system performance and efficiency. By providing a reliable and efficient control strategy, this paper contributes to the advancement of renewable energy systems and their adoption in the energy sector. The proposed control strategy has far-reaching implications for the widespread adoption of renewable energy sources, enabling a more sustainable and efficient energy future. The overall system is modeled in MATLAB/Simulink and PLECS software domain.

grid forming converters (GFM)↗
DOE OSTI2016

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Abstract Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.

Melaas, Eli K.↗
DOE OSTI2019

Seasonal variability of forest sensitivity to heat and drought stresses: A synthesis based on carbon fluxes from North American forest ecosystems

Climate extremes such as heat waves and droughts are projected to occur more frequently with increasing temperature and an intensified hydrological cycle. It is important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to heat and drought stress as indicated by air temperature (T a ) and evaporative fraction (EF). Using normalized daily carbon fluxes from the FLUXNET Network for 34 forest sites in North America, the seasonal pattern of sensitivities of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (RE) in response to T a and EF anomalies were compared for different forest types. The results showed that warm temperatures in spring had a positive effect on NEP in conifer forests but a negative impact in deciduous forests. GEP in conifer forests increased with higher temperature anomalies in spring but decreased in summer. The drought-induced decrease in NEP, which mostly occurred in the deciduous forests, was mostly driven by the reduction in GEP. In conifer forests, drought had a similar dampening effect on both GEP and RE, therefore leading to a neutral NEP response. The NEP sensitivity to T a anomalies increased with increasing mean annual temperature. Drier sites were less sensitive to drought stress in summer. Natural forests with older stand age tended to be more resilient to the climate stresses compared to managed younger forests. The results of the Classification and Regression Tree analysis showed that seasons and ecosystem productivity were the most powerful variables in explaining the variation of forest sensitivity to heat and drought stress. Our results implied that the magnitude and direction of carbon flux changes in response to climate extremes are highly dependent on the seasonal dynamics of forests and the timing of the climate extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A multi-machine scaling of halo current rotation

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: (1) the machine-specific minimum current quench time, tauCQ; (2) the halo current rotation duration, trot; and (3) the average halo current rotation frequency, . These data reveal that the normalized rotation duration, trot/tauCQ, and the average rotation velocity, , are surprisingly consistent from machine to machine. Furthermore, comparisons between carbon and metal wall machines show that metal walls have minimal impact on the behavior of rotating halo currents. Finally, upon projecting to ITER, the empirical scalings indicate that substantial halo current rotation above = 20 Hz is to be expected. More importantly, depending on the projected value of tauCQ in ITER, substantial rotation could also occur in the resonant frequency range of 6-20 Hz. As such, the possibility of damaging halo current rotation during unmitigated disruptions in ITER cannot be ruled out.

Halo currents↗
DOE OSTI2015

Parallel scaling analysis for explicit solid dynamics in ALEGRA

Weak scaling studies were performed for the explicit solid dynamics component of the ALEGRA code on two Cray supercomputer platforms during the period 2012-2015, involving a production-oriented hypervelocity impact problem. Results from these studies are presented, with analysis of the performance, scaling, and throughput of the code on these machines. The analysis demonstrates logarithmic scaling of the average CPU time per cycle up to core counts on the order of 10,000. At higher core counts, variable performance is observed, with significant upward excursions in compute time from the logarithmic trend. However, for core counts less than 10,000, the results show a 3 × improvement in simulation throughput, and a 2 × improvement in logarithmic scaling. This improvement is linked to improved memory performance on the Cray platforms, and to significant improvements made over this period to the data layout used by ALEGRA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Theoretical Analysis of Fractional Viscoelastic Flow in Circular Pipes: Parametric Study

Pipe flow is one of the most commonly used models to describe fluid dynamics. The concept of fractional derivative has been recently found very useful and much more accurate in predicting dynamics of viscoelastic fluids compared with classic models. In this paper, we capitalize on our previous study and consider space-time dynamics of flow velocity and stress for fractional Maxwell, Zener, and Burgers models. We demonstrate that the behavior of these quantities becomes much more complex (compared to integer-order classical models) when adjusting fractional order and elastic parameters. We investigate mutual influence of fractional orders and consider their limiting value combinations. Finally, we show that the models developed can be reduced to classical ones when appropriate fractional orders are set.

Gritsenko, Dmitry (ORCID:0000000248181512)↗
DOE OSTI2016

TILT ANGLE AND FOOTPOINT SEPARATION OF SMALL AND LARGE BIPOLAR SUNSPOT REGIONS OBSERVED WITH HMI

We investigate bipolar sunspot regions and how tilt angle and footpoint separation vary during emergence and decay. The Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory collects data at a higher cadence than historical records and allows for a detailed analysis of regions over their lifetimes. We sample the umbral tilt angle, footpoint separation, and umbral area of 235 bipolar sunspot regions in Helioseismic and Magnetic Imager—Debrecen Data with an hourly cadence. We use the time when the umbral area peaks as time zero to distinguish between the emergence and decay periods of each region and we limit our analysis of tilt and separation behavior over time to within ±96 hr of time zero. Tilt angle evolution is distinctly different for regions with small (≈30 MSH), midsize (≈50 MSH), and large (≈110 MSH) maximum umbral areas, with 45 and 90 MSH being useful divisions for separating the groups. At the peak umbral area, we determine median tilt angles for small (7.°6), midsize (5.°9), and large (9.°3) regions. Within ±48 hr of the time of peak umbral area, large regions steadily increase in tilt angle, midsize regions are nearly constant, and small regions show evidence of negative tilt during emergence. A period of growth in footpoint separation occurs over a 72-hr period for all of the regions from roughly 40 to 70 Mm. The smallest bipoles (<9 MSH) are outliers in that they do not obey Joy's law and have a much smaller footpoint separation. We confirm the Muñoz-Jaramillo et al. results that the sunspots appear to be two distinct populations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Integrated Analyses of Multiple Worldwide Aerosol Mass Spectrometer Datasets for Improved Understanding of Aerosol Sources and Processes and for Comparison with Global Models

The AMS is the only current instrument that provides real-time, quantitative, and size-resolved data on submicron non-refractory aerosol species with a time resolution of a few minutes or better. The AMS field data are multidimensional and massive, containing extremely rich information on aerosol chemistry, microphysics and dynamics—basic information that is required to evaluate and quantify the radiative climate forcing of atmospheric aerosols. The high time resolution of the AMS data also reveals details of aerosol dynamic variations that are vital to understanding the physico-chemical processes of atmospheric aerosols that govern aerosol properties relevant to the climate. There are two primary objectives of this 3-year project. Our first objective is to perform highly integrated analysis of dozens of AMS datasets acquired from various urban, forested, coastal, marine, mountain peak, and rural/remote locations around the world and synthesize and inter-compare results with a focus on the sources and the physico-chemical processes that govern aerosol properties relevant to aerosol climate forcing. Our second objective is to support our collaboration with global aerosol modelers, in which we will supply the size-resolved aerosol composition and temporal variation data (via a public web interface) and our analysis results for use in model testing and validation and for translation of the rich AMS database into model constraints that can improve climate forcing simulations. Several prominent global aerosol modelers have expressed enthusiastic support for this collaboration. The specific tasks that we propose to accomplish include 1) to develop, validate, and apply multivariate analysis techniques for improved characterization and source apportionment of organic aerosols; 2) to evaluate aerosol source regions and relative contributions based on back-trajectory integration (PSCF method); 3) to summarize and synthesize submicron aerosol information, including composition, concentration, size distribution and (inferred) shape and mixing state in various environments and their regional and seasonal variations within the context of regional and global modeling; and 4) to quantitatively evaluate important processes in various atmospheric environments and during different seasons, focusing on acid-catalyzed SOA formation, new particle growth, and photochemical processes of atmospheric organic aerosols (i.e., SOA production and POA oxidation). We will also examine the correlations and compile the ratios between important pairs of aerosol and gas phase species using region-specific and season-specific correlations and as a function of photochemical age and compare them with the ratios produced by various models. To enable our collaborations with the modelers, we will supply (via a public web interface) AMS data and our analysis results for use in model testing and validation and facilitate the use of the AMS information to constrain calculations of radiative forcing. Model output and AMS measurements and derived parameters will be compared with a focus on regional variability of model/measurement discrepancies and their causes. Finally we will share results, insights and data mining algorithms through peer-reviewed publications, presentations/tutorials at conferences/workshops, and web dissemination of analysis results and in-house developed software packages.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling of Thermal Decomposition of TATB-Based Explosive for Safety Analysis

We investigate and model the cook-off behavior of LX-17 to understand the response of explosive systems in abnormal thermal environments. Decomposition has been explored via conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (Thermo-Gravimetric Analysis), and DSC (Differential Scanning Calorimetry) experiments under isothermal and ramped temperature profiles. The data were used to fit reaction rate parameters for proposed schemes in an ALE3D computational model. This model includes chemical reactions, thermo- and hydro-dynamics, and material properties, including thermal expansion, compressibility, and strength. These parameterizations were carried out utilizing a Python evolutionary optimization method on LLNL’s high-performance computing clusters. Additional experiments are being developed to further characterize and monitor decomposition intermediates to improve the model. Once experimentally validated, this model will be scalable to several applications involving LX-17. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials.

Chemistry - Chemical explosives↗
DOE OSTI2017

A multi-mode state-space dynamic model for Pyrofusion neutron sources - 371

Pyrofusion neutron sources are compact, low power systems which may be capable of producing short intense pulses of neutrons from D-D fusion reactions. The neutron pulse duration has been too short for use as a continuous wave source, and too long for application in interrogation techniques. However, initial analysis of Pyrofusion dynamics has indicated the potential to manipulate the pulse characteristics through system control. This paper introduces the development of state-space multimode system models in MATLAB/Simulink that may be used to support the predictability and control of the neutron pulse. Preliminary examples of frequency-domain studies, stability analysis and time-domain simulations are reported. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Robust Predictive Control for Modular Solid-State Transformer With Reduced DC Link and Parameter Mismatch

This paper presents the analysis and implementation of a predictive control method for dc-link regulation and voltage balance in a cascaded modular reduced dc-link solid-state transformer (SST). Passive components like bulky dc links limit the power density of power converters, especially medium-voltage (MV) SST. Reduced dc-link or low-inertia converters can dramatically reduce the size, cost, and weight by tolerating larger dc-link ripples and improve the reliability with electrolytic capacitor-less dc link. However, a small dc link leads to tight coupling between the input and the output stages, which is a challenge for control design. In stacked low-inertia converters (SLIC), the low-inertia converter modules are stacked for MV applications, resulting in coupling between the modules and making the control more challenging. A new model predictive control method which can achieve deadbeat regulation on the dc link without weighting factors has been proposed to address this novel problem. This paper focuses on analyzing the condition of the low-inertia dc link up to 80% ripple, the robustness of the control under parameter mismatches, high-order terms, and important implementation issues such as model-based sampling and computation delay compensation. Significantly, the high-order terms are introduced because of the large dc-link ripple. These high-order terms are unique to the SLIC and negligible in conventional high-inertia converters. A discrete-time large-signal model is built to capture the dc-link’s nonlinear dynamics, and the eigenvalues of a small-signal Jacobian matrix are analyzed with Floquet theory to evaluate stability, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. Simulation and experimental results of an MVDC M-S4T verify the analysis and the predictive control method. Finally, the general application of the predictive control to low-inertia converters is compared against a conventional PI controller using a reduced dc-link active-front-end (AFE) rectifier as an example.

14 SOLAR ENERGY↗
DOE OSTI2012

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Impacts of High Variable Renewable Energy Futures on Electric-Sector Decision Making: Demand-Side Effects

Previous work by the Berkeley Lab describes how high shares of variable renewable energy (VRE) such as wind and solar power could change wholesale electricity price dynamics. These include the timing of when electricity is cheap or expensive, locational differences in the cost of electricity, and the degree of regularity or predictability in those costs. Many decentralized decision-makers on the demand-side may not yet have considered the implications of these possible future changes. In this report, we evaluate the sensitivity of a set of demand-side decisions to different levels of VRE penetration ranging from a low of 5-20% to a high of 40-50%. The analysis builds on hourly wholesale energy and capacity prices in different VRE scenarios for four wholesale markets in the United States for the year 2030 (CAISO, ERCOT, NYISO, and SPP). The principal question for this exploration is whether private and public electric-sector decisions that are made based on assumptions reflecting low VRE levels still achieve their intended objective in a high VRE scenario with 40-50% wind and solar? This scoping report evaluates the impacts of changing patterns of peak system needs on the benefits of demand reductions by examining the altered value of different energy efficiency (EE) measures. Similarly, we investigate new opportunities for large energy consumers that may arise from periods with very low wholesale electricity prices. We calculate the value of new process investments (e.g., hydrogen production and other generalized electro-commodities), showcase the varying value of new product storage investments (such as reservoir extensions at a desalination plant), and estimate the benefits of increased process flexibility that uses electricity as a process-input in addition to traditional fossil fuels (e.g., district energy systems). Finally, many decentralized decision-makers and end-use customers are not directly exposed to wholesale electricity prices but instead receive price signals from their retail electricity rates. As wind and solar shares increase, we compare the economic efficiency of flat retail rates relative to more dynamic time-of-use tariffs with and without critical peak-pricing events.

14 SOLAR ENERGY↗