Search NASA⌕ Search

SEARCH · Search NASA

Results for “Profiling optimization”

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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. In this work, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13 C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A mathematical model of tree harvesting in age-structured forests subject to beetle infestations

In this paper, we investigate a mathematical model for age-structured forest–beetle interactions that includes harvesting of trees. The aim is to broaden the understanding of the synergistic effects of harvesting and insect infestation on the age structure of the forests and the harvesting benefit. In the first part of this study, we consider different scenarios of the forest infestation by beetles and observe that the quantitative age profile of the forest depends significantly on whether the beetle population is in its endemic or epidemic states. In the second part, we also include harvesting of the forest trees and analyze two different harvesting strategies: cutting all trees older than a certain age, and cutting a fixed proportion of trees older than a certain age. Numerical simulations are implemented to determine the optimal cutting age for both harvesting strategies. The numerical simulations reveal that, independent of the steady state of the beetle population (that is, no beetles, endemic or epidemic state) clear cutting all trees older than a given age provides a higher harvesting benefit. Our numerical simulations further indicate that to obtain a fixed harvesting yield, a forest under a beetle epidemic state has to be cut at a younger age than if the forest were at an endemic beetle state or a no-beetle state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Accelerated aging test of new plastic scintillators

Fogging in plastic scintillators is a degradation mechanism that reduces light collection efficiency. In an effort to reduce maintenance costs, multiple groups have attempted to understand and prevent this problem by changing plastic compositions and system level designs. New formulations have been produced that are promising with respect to fogging resistance. In this paper, we study a variety of new compositions by subjecting them to an accelerated aging experiment with varying temperature and humidity profiles. Compositions are analyzed for their resistance to degradation after saturation periods, with those containing polymethyl methacrylate and divinyl benzene being the most promising. Pulse height spectra revealed that after environmental aging, many of the samples suffered a reduction in light yield to different degrees, a result that could be due to heating of the samples and may be prevented by further production optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Charge exchange recombination spectroscopy at Wendelstein 7-X

The Charge Exchange Recombination Spectroscopy (CXRS) diagnostic has become a routine diagnostic on almost all major high temperature fusion experimental devices. For the optimized stellarator Wendelstein 7-X (W7-X), a highly flexible and extensive CXRS diagnostic has been built to provide high-resolution local measurements of several important plasma parameters using the recently commissioned neutral beam heating. This paper outlines the design specifics of the W7-X CXRS system and gives examples of the initial results obtained, to include typical ion temperature profiles for several common heating scenarios, toroidal flow and radial electric field derived from velocity measurements, beam attenuation via beam emission spectra, and normalized impurity density profiles under some typical plasma conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Toroidal modeling of runaway electron loss due to 3-D fields in DIII-D and COMPASS

The 3-D field induced relativistic runaway electron (RE) loss has been simulated for DIII-D, COMPASS and ITER plasmas, utilizing the MARS-F code incorporated with the recently developed and updated RE orbit module (REORBIT). Modeling shows effectively 100% loss of a post-disruption, high-current runaway beam in DIII-D, due to the 1 kG level of magnetic field perturbation produced by a fast growing n = 1 resistive kink instability. The RE loss is shown to be independent of the particle energy or the initial location of particles in the configuration space. Applied resonant magnetic perturbation (RMP) fields from in-vessel coils are not effective for RE beam mitigation in DIII-D, but do produce finite (>10%) RE loss in COMPASS, consistent with experimental observations in above two devices. The major reasons for this difference in RE control by RMP between these two devices are (i) the coil proximity to the RE beam and (ii) the effective coil current scaling versus the machine size and the toroidal magnetic field. About 10% RE loss fraction is also predicted for an ITER 15 MA scenario with pre-disruption plasma, highlighting the role of the plasma response. Up to 30% loss is computed, however, by artificially scaling the equilibrium pressure to zero. This is due to the more resistive plasma response and stronger resulting field line stochasticity. Distributions of the lost REs to the limiting surface show poloidally peaked profile near the high-field-side in both DIII-D and COMPASS, covering about 100o poloidal angle. Higher perturbation field level and/or higher particle energy also result in REs being lost to the low-field-side of the limiting surface of these two devices, increasing the effective wetted area. Finally, for the modeled ITER plasmas, the applied RMP field, with optimal poloidal spectrum that maximizes the edge localized mode control, leads to REs being lost to the lower divertor region of the limiting surface within a narrow poloidal band.

3-D field↗
DOE OSTI2022

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗
DOE OSTI2019

Genome-Wide Analysis of Nitrate Transporter (NRT/NPF) Family in Sugarcane Saccharum spontaneum L.

Nitrate is the predominant nitrogen source for plant growth and development. However, sugarcane, globally used as the primary sugar crop and biofuel feedstock, displays a low nitrate use efficiency due to a low capacity in storing nitrate in shoots. It is well studied that the nitrate transporter (NRT/NPF) family functions as the gatekeeper in governing nitrogen uptake and distribution, and optimizing nitrogen utilization in plants. This makes it a promising target for improving nitrogen use efficiency in sugarcane. Here, we carried out a comprehensive analysis of NRT/NPF genes at a genome-wide scale in Saccharum spontaneum. A BLAST search of NRT/NPF genes was initially performed against recently released sugarcane genome, followed by phylogenetic, gene structure and protein motif analysis. Additionally, NRT/NPF gene expression profile from various tissues was obtained from RNA-seq data analysis. As a result, we identified 178 NPF, 20 NRT2, and 6 NRT3 genes which spread across all 8 monoploid chromosomes. NPF and NRT3 exhibit high levels of genetic diversities as opposed to NRT2 which is more evolutionarily conserved. Interestingly, several SsNPF genes are products of gene fusions of several tandem duplications, which provide valuable structural resources for functional characterization of nitrate transporters. Moreover, several genes are tissue-specific expressed, indicating roles in tissue-specific nitrate translocations. A substantial number of NRT/NPF genes are heterogeneous in terms of their gene structures and mRNA abundance. Taken together, our work provides a genetic foundation for future investigations of molecular and physiological functions of sugarcane nitrate transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Isotope dependence of transport in ST40 hot ion mode plasmas

The ST40 compact, high-field spherical tokamak, operating at 2.1 T and with 1.8 MW of neutral beam heating, achieved central carbon impurity ion temperatures in excess of 10 keV, surpassing their business milestone of 100 M °C (8.6 keV). The high temperature discharges were in the hot ion mode, with $T_i \gg T_e$, and they were achieved in both hydrogen and deuterium plasmas with deuterium neutral beam injection. In order to achieve the high temperature scenarios, careful wall conditioning and scenario optimization was carried out in $H^0 \rightarrow H^+$, $D^0 \rightarrow H^+$, and finally in $D^0 \rightarrow D^+$ plasmas. The TRANSP transport code was employed to study the dependence of confinement and transport on isotopic mass, and the conditions that led to the high measured central ion temperatures in the $D^0 \rightarrow H^+$ and $D^0 \rightarrow D^+$ plasmas. The kinetic profiles input into TRANSP were inferred from line-of-sight and limited radial measurements as well as consistency with a number of other experimental constraints. The TRANSP results first showed that the main species central ion temperature was only 0.5–1 keV lower than the measured carbon impurity temperature, and thus in the high performance plasmas also surpassed the 100 M °C level. TRANSP also showed that while the electron thermal conduction loss was dominant, reductions in central ion transport, and an effective decoupling of the ions from the electrons, led to an increase in central ion temperatures with increasing plasma mass. In fact, the associated confinement times exhibited a strong dependence on the isotopic mass of the thermal plasma. These preliminary results are foundations for dedicated experiments with full kinetic profile measurements on ST40 in the next run campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Foreground-immune CMB lensing reconstruction with polarization

Extragalactic foregrounds are known to generate significant biases in temperature based CMB lensing reconstruction. Several techniques, which include "source hardening'" and "shear-only estimators'' have been proposed to mitigate contamination and have been shown to be very effective at reducing foreground-induced biases. Here we extend both techniques to polarization, which will be an essential component of CMB lensing reconstruction for future experiments and investigate the "large lens'' limit analytically to gain insight on the origin and scaling of foreground biases, as well as the sensitivity to their profiles. Furthermore, using simulations of polarized point sources, we estimate the expected bias to both Simons Observatory and CMB-S4 like (polarization-based) lensing reconstruction, finding that biases to the former are minuscule while those to the latter are potentially non-negligible at small scales ($L$ ~ $1000-2000$). In particular, we show that for a CMB-S4 like experiment, an optimal linear combination of point-source hardened estimators can reduce the (point-source induced) bias to the CMB lensing power spectrum by up to two orders of magnitude, at a ~ 4% noise cost relative to the global minimum variance estimator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing

The recent development of deep learning has been mostly focusing on Euclidean data, such as images, videos, audios, etc. However, most real-world information and relation are often expressed as graphs. To efficiently learn from graph data, graph convolutional networks (GCNs) emerge as a promising approach, showing advantages in several practical applications such as social network analysis, knowledge discovery, 3D modeling, motion capturing, etc. Real-world graphs are usually extremely large and imbalanced, posting significant performance demand and design challenges on the hardware dedicated for GCN inference. In this paper, we propose an architecture design called UW-GCN to accelerate graph convolutional network inference. To tackle the major performance bottleneck from workload imbalance, we propose dynamic neighborhood stealing and remote chunk shuffling techniques, relying on hardware flexibility to achieve hardware auto-tuning under negligible area or delay overhead. Specifically, UW-GCN is able to smartly profile the sparse graph pattern while continuously adjusting the workload distribution via routing reconfiguration among parallel processing elements (PEs). The ideal configuration is then reused in the remaining iterations. To the best of our knowledge, this is the first accelerator design particularly for GCN and the first work relying on hardware auto-tuning, which is normally based on software, to achieve near-optimal workload balance in processing sparse structures.

Geng, Tong↗
DOE OSTI2021

Coordinated Optimization and Control of Residential Solid State Power Substations in Electrical Distribution Network

This paper proposes a computationally efficient mixed integer linear programming (MILP) model for the coordinated optimization of solid-state power substations (SSPSs) in a feeder considering the full unbalanced three-phase structure of the distribution grid and its characteristics. The proposed model determines the optimal real and reactive power of each SSPS at the point of common coupling (PCC) that minimizes the operating cost and maximizes the system performance, e.g., voltage regulation and phase balancing. To improve the computational efficiency, an inscribed octagon is introduced to approximate the quadratic capacity constraints of components. Numerical simulation results show the effectiveness of the proposed model and significant improvements in voltage profiles and power imbalance between phases.

Liu, Guodong↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2026

Strong-field QED limitations on TeV-class plasma wakefield accelerators

We demonstrate that quantum and classical radiation effects can become non-negligible for TeV-class beams propagating through plasma channels typical of staged plasma accelerators. Although the quantum nonlinearity parameter χ e remains small under currently envisioned experimental conditions, the cumulative influence of radiation over long acceleration distances can lead to significant modifications to the beam’s energy spread, emittance, and polarization. Our analytic models, validated by particle-in-cell simulations, highlight that for standard Gaussian beams, the orbit-induced energy spread dominates over quantum stochastic effects but can be mitigated by tailoring the beam profile, for example, through ring-shaped transverse distributions. In regimes where the radiation reaction approaches the accelerating force, the emittance may be cooled, forming distinctive ring-shaped phase-space structures. Finally, we analyze the influence of the radiation effect on spin transport inside the wakefield. These findings underscore the importance of considering both classical and quantum radiation dynamics in the design and optimization of future high-intensity plasma accelerators.

accelerator↗
DOE OSTI2022

Tuning the Porous Structure in PMMA-Templated Mesoporous MoO 2 for Pseudocapacitive Li-Ion Electrodes

MoO 2 is an exciting candidate for next-generation energy storage. It can be used for fast-charging applications in nanoscale form, but its kinetic performance is often limited by insulating MoO 3 surface oxide layers. Here, we developed methods to produce polymer-templated porous MoO 2 powders where electrical conductivity was well-maintained throughout the structure, even in the presence of some surface oxidation. Porosity, pore size, and crystallite size were controlled by varying the amount and size of the colloidal templates and through calcination temperature. The electrochemical performance was correlated with nanoscale structure: samples with high porosity, medium pore sizes, and good crystallinity display optimal rate capabilities, with over 100 mAh g −1 delivered in 3 min and 93% capacity retention after 1000 cycles. Kinetic studies were performed on samples with the largest and smallest crystallite sizes to understand the charge storage mechanism. In the sample with the smallest crystallite size, 85% of the total stored charge was capacitive, compared to 60% for the largest crystallite size. Sloping voltage profiles in materials with smaller domain sizes further suggest suppression of intercalation-induced phase transitions. This work thus provides insights into the mechanisms of charge storage in nanoscale MoO 2 and design parameters for the production of fast charging materials.

25 ENERGY STORAGE↗
DOE OSTI2019

Influence of optics vibration on synchrotron beam coherence

Vibration of optics is one of the major limiting factors of the performance of state-of-the-art beamlines at low-emittance synchrotron facilities. In this work, we present a theoretical model with experimental data describing vibration-induced effects on X-ray beam coherence. Owing to the Van Cittert-Zernike theorem, the coherence function of an X-ray beam perturbed by optics vibrations can be adequately characterized by modeling the spatial profile of the beam effective source. The measurements were carried out by using grating interferometry and a refractive lens with controlled vibration as a test optics. The experimental results confirm the model prediction and reveal the dependency of the measured beam spatial coherence on the acquisition time. The proposed method can be used to identify the eigenfrequency of the optical system as well as to optimize beamline operation and experimental conditions for coherence-related techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Efficient, Compact, and Smooth Variable Propulsion Motor (Final Report)

In this project, a new architecture of highly efficient hydraulic motor was developed for the propulsion of off-highway vehicles. The motor uses an adjustable linkage driving a cam to vary the displacement of the piston, resulting in a Variable Displacement Linkage Motor (VDLM). The motor uses low friction rolling element bearings to significantly reduce mechanical friction, especially in the demanding low-speed high-torque conditions experienced by off-highway vehicles. The VDLM has high torque capabilities for its size due to the radial piston packaging and use of a multi-lobe cam. A VDLM is very smooth due to the ability to tune the torque ripple through the design of the cam profile. The project was divided into three periods. During the first period, a dynamic model was constructed of the motor to predict the performance of the motor and the vehicle. During the second period, a single-cylinder learning prototype was designed, built, and tested to validate the models constructed in the first period. In the third period, a multi-cylinder prototype motor was optimized, designed, fabricated, and tested. The motor demonstrated excellent mechanical efficiency (above 92.5% across the range of displacements), but the experimentally measure volumetric efficiency was lower than expected due to higher leakage rates created by the poor tolerance control on the prototype. To validate the dynamic models developed in the first period and better understand design trade-offs. In the third period a multi-cylinder concept demonstration prototype will be designed, fabricated, and tested. The final prototype will be tested on a motor dynamometer and will be utilized in hardware-in-the-loop testing to demonstrate its efficiency and performance impacts on the overall drive train. The experimental results were used in a drive train simulation of a compact track loader operating through a drive cycle. Using the VDLM in a hydrostatic circuit yielded 17.1% reduction in fuel consumption and 36.5% reduction in a series hybrid transmission.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Numerical study to predict the effect of surface roughness on the thermal and hydraulic performance of additively manufactured heat exchangers

Heat exchangers are used in many industries to transfer thermal energy between two or more objects with an associated thermal and hydraulic performance indicated by thermal effectiveness and pressure drop respectively. Many investigations have aimed to enhance the thermal effectiveness of heat exchangers by introducing turbulent flow inducers that increase the heat transfer rate at the expense of increasing pressure drop. Flow inducers like surface roughness can be controlled with advanced manufacturing methods like additive manufacturing for heat exchanger production. Selecting and manufacturing an optimal surface roughness for heat exchangers requires a more comprehensive approach that accounts for the surface roughness effect on the thermal and hydraulic performance of a sample. Since fabricating samples with additive manufacturing to a desired surface roughness can be an extensive experimental process, this study will fundamentally investigate the effect of surface roughness on the thermal and velocity boundary layers for various surface roughness profiles with physics-based computational modeling. To accurately model the surface roughness effect on thermohydraulic performance, correlations like roughness ratio, friction factor, and Nusselt number are investigated. This study expects to indicate correlations for different flow regimes which can successfully predict the effect of surface roughness on thermohydraulic performance. Results generated from modeling surface roughness effect with unique correlations are then compared to experimental data obtained from literature for validation. The results of this study will provide insight to understand the thermal fluid physics associated with surface roughness and design guidelines for heat exchangers produced with additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of Hybrid FPOG Applications in Regulated and Deregulated Markets Using HERON

Recent changes in the U.S. energy market, such as low natural gas prices and increased electricity production for variable renewable energy (VRE) sources, have led to an economic crisis for existing light-water reactor (LWR) nuclear power plants (NPP). Many owners and operators of LWRs have elected to decommission these plants rather than continue using them as consistent sources of clean baseload power. This has led to exploration of various possibilities to increase the economic viability of these units, including market restructuring to monetize benefits LWRs already provide to the grid through ancillary markets, load following and economic dispatch, and possible integration of secondary systems directly to the NPP for production of additional products through technologies such as hydrogen electrolysis or water desalination. Previous studies have considered the technologies associated with these Integrated Energy Systems (IES) activities, and the analysis of markets for these secondary products. To analyze the economic viability of various system configurations including IES, especially given the uncertainty surrounding load demand, electricity prices, and the availability of VRE resources, the stochastic technoeconomic analysis package HERON (Heuristic Energy Resource Optimization Network) was released earlier this year as an extension of the risk analysis framework RAVEN (Risk Analysis Virtual Environment). HERON focuses foremost on making the complex uncertainty quantification analysis tools approachable for energy systems analysts, also providing general dispatch optimization algorithms for those workflows. HERON continues to be improved and tested as a significant part of the IES viability analyses performed in this work. HERON is not a capacity expansion model. To consider market and grid energy system development in a variety of scenarios, HERON is best used in coupling with modelling tools such as US-REGEN, which sacrifice some of the uncertainty analysis and resolution of HERON's modelling for the ability to efficiently predict the change in the grid energy system's profile due to economic drivers over decades. HERON can then use this information to explore the economic viability of introducing changes to the predicted outcomes, such as the introduction of an IES. In this work, experts at EPRI using US-REGEN provide six projection scenarios for use in HERON stochastic technoeconomic analysis (STEA) in considering the options available for increasing LWR economic viability through introduction of a hydrogen-centric IES using a high-temperature steam electrolysis plant (HTSE), hydrogen storage, and a constant-rate contracted hydrogen consumer. The results obtained are differential in nature; they do not report expected profits for any configuration, but rather report on the possible increase in the NPV of a configuration with respect to a baseline no-IES configuration. Due to the uncertainty captured in the variable net load of the systems, there is likewise uncertainty in the mean values reported. We consider this viability both in terms of a regulated market, where the energy producers and IES are owned and operated by single entity, as well as a deregulated market, where the IES chooses its bid for electricity generation and is then dispatched by the grid system operator. Results indicate that for deregulated markets, the inclusion of the IES is often statistically beneficial. This is especially true in policies that are not favorable towards nuclear, as nuclear is less often dispatched and is forced to deal with frequent idle capacity. In the nominal case as well as the case of carbon tax policies, inclusion of the IES clearly benefited the economic performance of the NPP. In the regulated case, however, there was a trend towards minimizing the IES, likely due to the optimal sizing performed by US-REGEN of the NPP within the system as well as the lack of penalty for idle capacity at the NPP in the regulated market analyses.

99 GENERAL AND MISCELLANEOUS↗