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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.
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Toward a MILP Modeling Framework for Distribution System Restoration
Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, allows restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is critical to perform optimally coordinated restoration that can achieve maximal restoration performance. This work introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as a mixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder.
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning With Region-of-Interest Active Sampling
With the increasing penetration of renewable energy, frequency response and its security are of significant concerns for reliable power system operations. Frequency-constrained unit commitment (FCUC) is proposed to address this challenge. Despite existing efforts in modeling frequency characteristics in unit commitment (UC), current strategies can only handle oversimplified low-order frequency response models and do not consider wide-range operating conditions. This paper presents a generic data-driven framework for FCUC under high renewable penetration. Here, deep neural networks (DNNs) are trained to predict the frequency response using real data or high-fidelity simulation data. Next, the DNN is reformulated as a set of mixed-integer linear constraints to be incorporated into the ordinary UC formulation. In the data generation phase, all possible power injections are considered, and a region-of-interest active sampling is proposed to include power injection samples with frequency nadirs closer to the UFLC threshold, which enhances the accuracy of frequency constraints in FCUC. The proposed FCUC is investigated on the IEEE 39-bus system. Then, a full-order dynamic model simulation using PSS/E verifies the effectiveness of FCUC in frequency-secure generator commitments.
The Value of Increased HVDC Capacity Between Eastern and Western U.S. Grids: The Interconnections Seam Study
The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the worlds largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions.
A Scalable Approach to Large Scale Risk-Averse Distribution Grid Expansion Planning
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Flexible operation of batteries in power system scheduling with renewable energy
The fast growing expansion of renewable energy increases the complexities in balancing generation and demand in the power system. The energy-shifting and fast-ramping capability of energy storage has led to increasing interests in batteries to facilitate the integration of renewable resources. In this paper, we present a two-step framework to evaluate the potential value of energy storage in power systems with renewable generation. First, we formulate a stochastic unit commitment approach with wind power forecast uncertainty and energy storage. Second, the solution from the stochastic unit commitment is used to derive a flexible schedule for energy storage in economic dispatch where the look-ahead horizon is limited. Here, analysis is conducted on the IEEE 24-bus system to demonstrate the benefits of battery storage in systems with renewable resources and the effectiveness of the proposed battery operation strategy.
Accounting for spectroscopic effects in laser‐based open‐path eddy covariance flux measurements
Abstract A significant portion of the production and consumption of trace gases (e.g. CO 2 , CH 4 , N 2 O, NH 3 , etc.) by world ecosystems occurs in areas without sufficient infrastructure or easily available grid power to run traditional closed‐path flux stations. Open‐path analyzer design allows such measurements with power consumption 10–150 times below present closed‐path technologies, helping to considerably expand the global coverage and improve the estimates of gas emissions and budgets, informing the remote sensing and modeling communities and policy decisions, all the way to IPCC reports. Broad‐band nondispersive infrared devices have been used for open‐path CO 2 and H 2 O measurements since the late 1970s, but since recently, a growing number of new narrow‐band laser‐based instruments are being rapidly developed. The new design comes with its own challenges, specifically: (a) mirror contamination, and (b) uncontrolled air temperature, pressure and humidity, affecting both the gas density and the laser spectroscopy of the measurements. While the contamination can be addressed via automated cleaning, and density effects can be addressed via the Webb‐Pearman‐Leuning approach, the spectroscopic effects of the in situ temperature, pressure and humidity fluctuations on laser‐measured densities remain a standing methodological question. Here we propose a concept accounting for such effects in the same manner as Webb et al. proposed to account for respective density effects. Derivations are provided for a general case of flux of any gas, examined using a specific example of CH 4 fluxes from a commercially available analyzer, and then tested using “zero‐flux” experiment. The proposed approach helps reduce errors in open‐path, enclosed, and temperature‐ or pressure‐uncontrolled closed‐path laser‐based flux measurements due to the spectroscopic effects from few percents to multiple folds, leading to methodological advancement and geographical expansion of the use of such systems providing reliable and consistent results for process‐level studies, remote sensing and Earth modeling applications, and GHG policy decision‐making.
System-Level Thermal Management and Reliability of Automotive Electronics: Goals and Opportunities Using Phase-Change Materials
Abstract Electronic packaging for automotive applications are at particular risk of thermomechanical failure due to the naturally harsh conditions it is exposed to. With the rise of electric and hybrid electric vehicles (EVs and HEVs), combined with a desire to miniaturize, the challenge of removing enough heat from electronic devices in automotive vehicles is evolving. This paper closely examines the new challenges in thermal management in various driving environments and aims to classify each existing cooling method in terms of performance. Particular focus is placed upon emerging solutions regarded to hold great potential, such as phase-change materials (PCMs). PCMs have been regarded for some time as a means of transferring heat quickly away from the region with the electronic components and are widely regarded as a possible means of carrying out cooling in large scale from small areas, because of their high latent heat of fusion, high specific heat, temperature stability, and small volume change during phase change, etc. They have already been utilized as a method of passive cooling in electronics in various ways, but their adoption in automotive power electronics, such as in traction inverters, has yet to be fulfilled. A brief discussion is made on some of the potential areas of application and challenges relating to more widespread adoption of PCMs, with reference to a case study using computational model of a commercially available power module used in automotive applications.
A Phenomenological Thermal Spray Wall Interaction Modeling Framework Applied to a High Temperature Ignition Assistant Device
Airborne compression ignition engines must operate with reliable ignition systems to achieve proper ignition at every cycle, particularly at high altitudes. Glow-plug-based ignition-assistant (IA) devices can provide the necessary energy to preheat the fuel and ensure ignitability of the fuel-air mixture. Ignitability of liquid sprays can be facilitated via direct impingement onto the hot IA surface, however this comes with adverse effects on the IA durability. Therefore, optimizing an IA’s design requires detailed understanding of the physics of fuel spray impingement of superheated surfaces. While spray impingement on relatively low wall temperatures has been extensively studied and appropriate numerical models have been proposed through the years, fundamental understanding of high-speed liquid spray impingement on superheated walls is still elusive. This work aims to formulate a phenomenological thermal spray-wall interaction framework for modeling the film-boiling-induced heat transfer, atomization, and dispersion of fuel spray droplets impinging onto a superheated IA device. A qualitative comparison of the new phenomenological model is performed against optical experiments from the literature of an F-24 fuel spray injected onto an IA device located 12 mm away from the injector tip. The temperature of the IA was set at 1400 K. The fuel injection pressure was 400 bar, while the ambient gas pressure and temperature were 30 bar and 800 K, respectively. The performance of the phenomenological model is evaluated in comparison with two other state-of-art models from the literature. A qualitative analysis of the different spray and fuel-air mixture characteristics is performed to outline the differences in the predictions offered by the new phenomenological model and the two state-of-art spray-wall interaction models.
Coupled Multiphysics Modeling of Lithium-Ion Batteries for Automotive Crashworthiness Applications
Considerable advances have been made in battery safety models, but achieving predictive accuracy across a wide range of conditions continues to be challenging. Interactions between dynamically evolving mechanical, electrical, and thermal state variables make model prediction difficult during mechanical abuse scenarios. In this study, we develop a physics-based modeling approach that allows for choosing between different mechanical and electrochemical models depending on the required level of analysis. We demonstrate the use of this approach to connect cell-level abuse response to electrode-level and particle-level transport phenomena. A pseudo-two-dimensional model and simplified single-particle models are calibrated to electrical-thermal cycling data and applied to mechanically induced short-circuit scenarios to understand how the choice of electrochemical model affects the model prediction under abuse scenarios. These models are implemented using user-defined subroutines on ls-dyna finite element software and can be coupled with existing automotive crash safety models.
SU-E-T-183: Clinical Quality Assurance Workflow for Dynamic Tumor Tracking Radiation Dose Delivery
Purpose: One of the most important aspects of implementation of new treatment modalities is an ‘end-to-end’ verification of the treatment process. Radiation treatment based on dynamic tracking of a tumor is highly patient-specific, therefore, special attention should be paid to quality assurance of the treatment delivery. Our goal was to design the clinical workflow that ensures accurate delivery of the planned dose using the Dynamic Target Tracking option of VeroTM (BrainLab,MHI) linac. Methods: A patient simulation is designed to include a pre-treatment session to verify whether the system can reliably track the motion of the implanted marker and build the 4D model of the target motion. The external surrogate and target motion patterns are recorded in the ExactracTM log files. In this work, a spectrum of custom marker and external surrogate motion trajectories closely resembling the patient specific motion patterns was used. 1mm thick/11mm long VisicoilTM marker was placed 15 and 20mm from the center of the spherical tissue equivalent target (centroid to centroid distance) in the 4D motion phantom (CIRSTM). 3D conformal (3 mm block margin) SBRT plans were delivered to 2 moving targets in the phantom: 1) 20mm diameter target that allows ion chamber dose measurement and 2) 25mm target that allows using film to measure CAX dose (GafchromicTM EBT3 used). The measured dose was compared to the iPlanTM TPS results using MonteCarlo algorithm (1% variance, Dose-to-water). Results: On average, film shows 98.9% pass using gamma criterion for 2% and 2mm DTA, 94.3% match for 2% and 1 mm DTA, 98% pass for 1% and 2 mm DTA however only 88% points passing for 1% and 1 mm DTA. Ion chamber measurements agreed with the calculation within 1.5%. Conclusion: The clinical QA workflow was designed for SBRT delivery using real-time tumor tracking on VeroTM linac.
High energy density picoliter-scale zinc-air microbatteries for colloidal robotics
The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10 −12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.
Performance portable ice-sheet modeling with MALI
High-resolution simulations of polar ice sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth system models for probabilistic sea-level projections. These simulations often require a massive amount of memory and computation from large supercomputing clusters to provide sufficient accuracy and resolution; therefore, it has become essential to ensure performance on these platforms. Many of today’s supercomputers contain a diverse set of computing architectures and require specific programming interfaces in order to obtain optimal efficiency. In an effort to avoid architecture-specific programming and maintain productivity across platforms, the ice-sheet modeling code known as MPAS-Albany Land Ice (MALI) uses high-level abstractions to integrate Trilinos libraries and the Kokkos programming model for performance portable code across a variety of different architectures. In this article, we analyze the performance portable features of MALI via a performance analysis on current CPU-based and GPU-based supercomputers. The analysis highlights not only the performance portable improvements made in finite element assembly and multigrid preconditioning within MALI with speedups between 1.26 and 1.82x across CPU and GPU architectures but also identifies the need to further improve performance in software coupling and preconditioning on GPUs. We perform a weak scalability study and show that simulations on GPU-based machines perform 1.24–1.92x faster when utilizing the GPUs. The best performance is found in finite element assembly, which achieved a speedup of up to 8.65x and a weak scaling efficiency of 82.6% with GPUs. We additionally describe an automated performance testing framework developed for this code base using a changepoint detection method. The framework is used to make actionable decisions about performance within MALI. We provide several concrete examples of scenarios in which the framework has identified performance regressions, improvements, and algorithm differences over the course of 2 years of development.
System Study: High-Pressure Safety Injection 1998-2014
This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 69 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPSI results.
System Study: Reactor Core Isolation Cooling 1998-2014
This report presents an unreliability evaluation of the reactor core isolation cooling (RCIC) system at 31 U.S. commercial boiling water reactors. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant trends were identified in the RCIC results.
Impact of Clean Energy R&D on the U.S. Power Sector
The U.S. government, along with other governments, private corporations and organizations, invests significantly in research, development, demonstration and deployment (RDD&D) activities in clean energy technologies, in part to achieve the goal of a clean, secure, and reliable energy system. While specific outcomes and breakthroughs resulting from RDD&D investment are unpredictable, it can be instructive to explore the potential impacts of clean energy RDD&D activities in the power sector and to place those impacts in the context of current and anticipated market trends. This analysis builds on and leverages analysis by the U.S. Department of Energy (DOE) titled “Energy CO 2 Emissions Impacts of Clean Energy Technology Innovation and Policy” (DOE 2017). Similar to DOE (2017), we explore how additional improvements in cost and performance of clean energy technologies could impact the future U.S. energy system; however, unlike the economy-wide modeling used in DOE (2017) our analysis is focused solely on the electricity sector and applies a different and more highly spatially-resolved electric sector model. More specifically, we apply a scenario analysis approach to explore how assumed further advancements in clean electricity technologies would impact power sector generation mix, electricity system costs, and power sector carbon dioxide (CO 2 ) emissions.
Geothermal System Extensions
This material is based upon work supported by the Department of Energy under Award Number DE-EE0000318. The City of Boise operates and maintains the nation’s largest geothermal heating district. Today, 91 buildings are connected, providing space heating to over 5.5 million square feet, domestic water heating, laundry and pool heating, sidewalk snowmelt and other related uses. Approximately 300 million gallons of 177°F geothermal water is pumped annually to buildings and institutions located in downtown Boise. The closed loop system returns all used geothermal water back into the aquifer after heat has been removed via an Injection Well. Water injected back into the aquifer has an average temperature of 115°F. This project expanded the Boise Geothermal Heating District (Geothermal System) to bring geothermal energy to the campus of Boise State University and to the Central Addition Eco-District. In addition, this project also improved the overall system’s reliability and increased the hydraulic capacity.
Regulatory Incentives and Disincentives for Utility Investments in Grid Modernization
Electric power is America's most capital-intensive industry, with more than $100 billion invested each year in energy infrastructure. Investment needs are likely to grow as electric utilities make power systems more reliable and resilient, deploy advanced digital technologies, and facilitate new services to meet some consumers' expectations for greater choice and control. But do current regulatory approaches provide the appropriate incentives for grid modernization investments? This report presents three perspectives: -Financial analyst Steve Kihm begins by explaining that any major investor-owned electric utility that wants to raise capital today can do so at a reasonable cost. The question is whether utility managers want to raise capital for grid modernization. Specifically, they look for investments that create the most value for their existing shareholders. In cases where grid modernization investments are not the best choice in terms of shareholder value, Kihm describes shareholder incentive mechanisms that regulators could consider to encourage such investments when they are in the public interest. -From an institutional perspective, Dr. Janice Beecher finds that the traditional rate-base/rate of return regulatory model provides powerful incentives for utilities to pursue investments, cost control, efficiency and even innovation, and it is well suited to the policy objectives of grid modernization. Prudence of grid modernization investments (fair returns) depends on careful evaluation of the specific asset, and any special incentives (bonus returns) should be used only if they promote economic efficiency consistent with the core goals of economic regulation. According to Beecher, realizing the promises of grid modernization depends on effective implementation of the traditional regulatory model and ratemaking tools to serve the public interest. -Conversely, former commissioner and clean energy consultant Ron Lehr says that rapid electric industry changes require a better alignment of utility investment incentives with changes challenging the electricity sector, emerging grid modernization options and benefits, and public policies. For example, investor-owned utilities typically have an incentive to make capital investments, but rarely to employ expense-based solutions, since utilities do not earn profits on expenses. Further, Lehr cites a variety of factors that stand in the way of creating well targeted and well aligned utility incentives, including litigated regulatory processes. These may be a poor choice for finding the right balance among competing interests, establishing rules of prospective application, justifying demonstrations of new technologies and approaches to meeting emerging consumer demands, and keeping pace with rapid change.