Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distribution systems state estimation”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electric dipole polarizability of 58 Ni

The electric dipole strength distribution in 58 Ni between 6 and 20 MeV has been determined from proton inelastic scattering experiments at very forward angles at RCNP, Osaka. The experimental data are rather well reproduced by quasiparticle random-phase approximation calculations including vibration coupling, despite a mild dependence on the adopted Skyrme interaction. They allow an estimate of the experimentally inaccessible high-energy contribution above 20 MeV, leading to an electric dipole polarizability α D ⁡ ( 58 Ni) = 3.48 (31)⁢ fm 3 . This serves as a test case for recent extensions of coupled-cluster calculations with chiral effective field theory interactions to nuclei with two nucleons on top of a closed-shell system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Transactive Electric Water Heater Agent: Design and Performance Evaluation

Electric water heaters (EWHs) are usually equipped with inbuilt thermostats to measure water temperature near the installed positions. Most of the existing EWHs have only two thermostats and often do not have water flow sensor installed. Estimation of state of heat energy (SOHE) inside the hot water tank, which is crucial for efficient control and operation of the EWH, under such imperfect system conditions is very challenging. This paper, therefore, designs a transactive EWH agent (TEWHA) to better estimate SOHE in presence of measurement errors and imperfect system knowledge. The TEWHA, built-in Python, approximates the EWH physics using limited measurements obtained from the ground truth GridLABD model. The performance of the TEWHA is validated against ground truth system for three scenarios: a) ideal condition where TEWHA has complete knowledge of the system, b) imperfect condition where TEWHA has incomplete system information, and c) noised condition where TEWHA measurements contain random errors. Finally, an optimization problem is formulated and solved to demonstrate how TEWHA could use the estimated and measured parameters for a transactive control of EWH. Index Terms—Demand flexibility

demand flexibility, distribution system, electric ↗
DOE OSTI2019

Numerical study of groundwater flow cycling controlled by seawater/freshwater interaction in Woodville Karst Plain

Seawater intrusion due to sea level rise and climate change could significantly contaminate coastal groundwater resources, particularly in Florida, the flat low-land state in the United States. Based on the field investigation and hydrological measurements, a three-dimensional SEAWAT model is developed to evaluate the groundwater flow cycling and seawater intrusion to freshwater system in the Woodville Karst Plain (WKP), a typical karst groundwater system in the Floridan aquifer. The karst conduit network in the aquifer acts as fast flow pathway for groundwater flow and solute transport, so seawater could deeply intrude into the aquifer. Wakulla Spring, an inland spring 17 km from the coast and a coastal submarine spring, Spring Creek Spring Complex are connected through the conduit network. The flow direction between the two springs switches under various rainfall conditions in this region, thus the discharges at two karst springs are used to estimate the location of seawater/freshwater mixing interface. The SEAWAT modeling results indicate that the mixing interface, defined as 2 PSU (Practical Salinity Unit), intrudes 3 to 5 km through the subsurface karst conduit during the dry season and severely contaminates nearly 1 km width of groundwater around the conduit. The salinity distribution and the distance of seawater intrusion through the conduit system are very sensitive to precipitation variation and the sea level boundary condition. Furthermore, predictions are made for seawater intrusion to the aquifer under various sea level rise, precipitation scenarios and water pumping. The results show that the seawater intrusion could reach and contaminate inland freshwater systems if sea level rises 1.0 m or during a long-term no-precipitation season. Finally, this study provides insights for modeling and predicting the vulnerability of a coastal karst aquifer through the simulation of variable-density flow.

58 GEOSCIENCES↗
DOE OSTI2022

Batteries Included: Top 10 Findings from Berkeley Lab Research on the Growth of Hybrid Power Plants in the United States

One of the most important electric power system trends of the 2010s was the rapid deployment of wind turbines and photovoltaic arrays, but a twist for the 2020s may be the rapid deployment of ‘hybrid’ generation resources. Hybrid power plants typically combine solar or wind (or other energy sources) with co-located storage. While hybridization helps to ease the challenge of balancing variable supply and demand, its relative novelty means that research is needed to facilitate integration and promote innovation. Combining the characteristics of multiple energy, storage, and conversion technologies poses complex questions for grid operations and economics. Project developers, system operators, planners, and regulators would benefit from better data, methods, and tools to estimate the costs, values, and system impacts of hybrid projects. This publication showcases some of Berkeley Lab’s robust research program intended to support private- and public-sector decision-making about hybrid plants in the United States. Our short briefing summarizes articles that we published between 2020 and 2022, links to the in-depth reports, and provides contact details for further engagement on the specific research topics: Growth: Developer interest in hybrid power plants is strong and growing Price vs. Value: PV+storage hybrids have low PPA prices and high value in some regions Market Drivers: Solar hybridization is driven by tax credits and other benefits Configuration Choices: Market prices have incentivized shorter duration batteries with PV Capacity Value: The capacity contribution of a hybrid is less than the sum of its parts Ancillary Services: AS markets are a valuable yet fleeting option for hybrids Market Participation: Hybrids can more flexibly engage with electricity markets Operations: The power system value of hybrids depends on how they are operated Distributed Hybrids: Growth of customer-sited PV+storage hybrids offers new opportunities Future Research: Where next? Priority areas for hybrid power research.

25 ENERGY STORAGE↗
NASA NTRS2012

TRMM Latent Heating Retrieval and Comparisons with Field Campaigns and Large-Scale Analyses

Rainfall production is a fundamental process within the Earth's hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating (LH), is one of the principal sources of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The vertical distribution of LH has a strong influence on the atmosphere, controlling large-scale tropical circulations, exciting and modulating tropical waves, maintaining the intensities of tropical cyclones, and even providing the energetics of midlatitude cyclones and other mobile midlatitude weather systems. Moreover, the processes associated with LH result in significant non-linear changes in atmospheric radiation through the creation, dissipation and modulation of clouds and precipitation. Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Yanai's paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables used in LH algorithms. This paper examines the retrieval, validation, and application of LH estimates based on rain rate quantities acquired from the Tropical Rainfall Measuring Mission satellite (TRMM). TRMM was launched in November 1997 as a joint enterprise between the American and Japanese space agencies -- with overriding goals of providing accurate four-dimensional estimates of rainfall and LH over the global Tropics and subtropics equatorward of 35o. Other literature has acknowledged the achievement of the first goal of obtaining an accurate rainfall climatology. This paper describes the second major goal of obtaining credible LH estimates as well as their applications within TRMM's zone of coverage, the standard TRMM LH products, and areas for further improvement.

latent heating↗
DOE OSTI2020

Energy impact of human health and wellness lighting recommendations for office and classroom applications

The goal of this investigation was to evaluate potential energy impacts of circadian lighting design recommendations gaining attention in a variety of common applications such as offices and classrooms. The renewed focus on health along with advances in SSL technology capabilities has underscored that there is still much to learn regarding the relationship between light and human physiology. The energy implications of designing to address these possible physiological effects are not yet fully understood. Beyond the fact that the basic metric of luminous efficacy (lumens per watt) does not cover these other effects, the emerging science seems to indicate that addressing a holistic view of the human needs in most applications may mean a need for increased light and associated energy use by electric lighting systems. Within the two applications considered, lumen output, spectral characteristics, surface reflectance distribution and desk orientation were varied to explore the magnitude of potential effects. Meeting current IES illuminance recommendations did not satisfy existing EML and CS recommendations for any of the simulations. In some cases, satisfying circadian metric recommendations required average illuminance that was more than double IES recommendations, which may negatively impact lighting quality as well. Using results from 45 unique simulation conditions, it was estimated that lighting energy use may increase between 10% and 100% due to increased luminaire light levels used to meet circadian lighting design recommendations listed in current building standards such as WELL v2 Q2 2019, UL Design Guideline 24480, and CHPS Core Criteria 3.0.

circadian lighting, lighting simulation, solid sta↗
DOE OSTI2019

Grid Impacts of Hyperloop Technology in the United States

This report provides an overview of Hyperloop technologies including the current technology developments and a brief discussion on key components of the Hyperloop system that determine the electric power requirements as a function of time. At-scale Hyperloop systems do not exist yet so a model was used to generate a set of load profiles for conceptual systems at four locations in the United States: two in California, one in Colorado, and one in Ohio. In all four cases, the modeled Hyperloop load profiles showed a pulsating characteristic in both active and reactive power. Grid modeling was performed by Pacific Northwest National Laboratory to estimate the grid impacts and to discuss grid integration challenges. This report discusses the outcomes of the grid simulations for four study cases and offers some perspective of how existing large industrial loads with similar load characteristics are treated to accommodate current grid planning guidelines. The report concludes with a discussion on how energy storage system might be used to eliminate the pulsating load characteristics or significantly reduce it.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The Role of Input Assumptions and Model Structures in Projections of Variable Renewable Energy: A Multi-Model Perspective of the U.S. Electricity System

Recent wind and solar deployment in the United States has grown at unprecedented rates, but the extent to which this growth will continue is a key question. Energy-economic planning models are often used to develop future projections of these technologies, and although it is well-understood that model outcomes are sensitive to assumptions about technology developments and market conditions, it is less clear how underlying model structures might impact outcomes. For wind and solar technologies, model structures might be an even larger driver due to the complexity required to represent their variability, uncertainty, and location-dependence. Here, we apply three state-of-the-art electric sector planning models to evaluate variable renewable generation under different conditions with both harmonized and native input assumptions to isolate the impact that model structures might have on deployment outcomes. We find growth in wind and solar deployment in all models under a business-as-usual scenario (without new policies), where the median value for variable renewable energy generation share is found to be 27% by 2050 - but with a wide range of estimates (18-43%), types of renewable technologies deployed, and regional distributions across models. With harmonized assumptions about technology costs and market conditions the range narrows slightly, but a large range in penetration outcomes remains (24-41% by 2050) suggesting that model representations play significant roles in projections of future wind and solar deployment. We also assess the implications of achieving 55% wind and solar penetration by 2050 - to assess potential challenges at higher penetration levels - and the magnitude of variable generation under a carbon-constrained future. Finally, we identify research needs to better assess the future deployment of variable renewable energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Development and Implementation of an Automatic Continuous Online Monitoring and Control Platform for Polymerization Reactions to Sharply Boost Energy and Resource Efficiency in Polymer Manufacturing

The project goal was to create an energy saving paradigm shift in how polymers are manufactured in the 21st century. It used Automatic Continuous Online Monitoring of Polymerization reactions (ACOMP) integrated for the first time with automatic active control to create the innovative ‘ACOMP/Control Interface’, or ‘ACOMP/CI’. ACOMP/CI will begin the transformation from old, inefficient processes into highly evolved, energy and resource efficient ones. The ACOMP platform is broadly applicable to many types of reactions and processes throughout the vast polymer industry. The industry provides materials for sectors such as automotive, aerospace, oil recovery, agriculture, paints, resins, adhesives, pharmaceuticals and therapeutic proteins, optics, electronics, lightweight building materials, and many more. The U.S. chemical industry is one of the last major sectors in which the U.S. has top global stature. It consumes 24% of all U.S. manufacturing energy, produces over $800B of product annually, supports 25% of the U.S. GDP and employs over 6 million people. It is also a major source of GHG emissions. Polymers make up approximately 30% of this sector. It is estimated that annually 60 TBtu of energy could be saved and 3 million tons less of GHG emissions produced by optimizing production in the polyolefin manufacturing sector alone. The project scope included first time design and prototyping of an ACOMP/CI, creation of active reaction controllers, and demonstration of control capabilities on ideal, low concentration polymerization reactions. All these elements of the scope were met, including advances and findings not originally anticipated. Extensions to more complex reactions, beyond the reactor capabilities of the current project ACOMP/CI, such as polyolefins and other high pressure/high temperature reactions, are being proposed in Fall 2017 to CESMII, a DoE based NNMI. The initial proposal was for a three year funded project, but this was reduced to a two year project and budget due to funding constraints. Hence, some of the original plans, such as adaptation of the ACOMP/CI to more relevant industrial processes, such as emulsion and dispersion technologies, could not be carried out. A third year of funding was requested at the end of the project, but DoE did not have resources to grant this. The sub-contractor Fluence Analytics (previously Advanced Polymer Monitoring Technologies, Inc) designed, prototyped, and commissioned a working ACOMP/CI by June 2015. The reaction characteristics to be automatically controlled were i) conversion kinetics, ii) molecular weight, iii) copolymer composition, and iv) simultaneous molecular weight and composition. A two pronged control strategy was used. The Tulane/Fluence group took a basic principles approach that did not rely on kinetic models. The LSU group took a more complex, non-linear model-oriented approach involving complete kinetic descriptions of the reaction system Each of these approaches proved successful in their own way. By April 2016 fully automatic control of conversion and weight average molecular weight, Mw, trajectories was achieved using the Tulane/Fluence (TF) basic principles controller. Similar results were obtained by the LSU non-linear model controller by August 2016. The demonstration system was aqueous free radical polymerization of acrylamide, Am. The control variables were temperature and semi-batch feed to the reactor of Am monomer and initiator. A demonstration of active manual conversion control in an industrial process using high solids in inverse emulsion polymerization of Am was achieved. During Summer 2016 the TF controller was used in conjunction with a chain transfer agent, another control variable, to automatically produce multi-modal molecular weight distributions, MWD, in a single reactor. Industrially, multi-modal MWD are produced by mixing products made in separate reactors, requiring significant extra time, energy, and reactor resources. Recognizing the industrial potential a patent on automatic production of multi-modal polymers was filed, and DoE acknowledged. In Fall 2016 the TF team developed a basic principles controller for copolymer composition and demonstrated it on aqueous free radical copolymerization of comonomers Am and styrene sulfonate, SS. TF then fused the Mw and composition controllers to achieve simultaneous control of both Mw and copolymer composition trajectories. Numerous simultaneous trajectories were demonstrated, including a trimodal composition distribution with constant Mw. Meanwhile, the LSU group developed a Kalman filter to improve the results of their automatic Mw and conversion controller and successful tests were made. During the project the TF team developed a means of computing full MWD during polymer synthesis without need for any chromatographic separation, based on model distributions. This means the polymer product is ‘born characterized’ and this can eliminate post-manufacture analytical laboratory quality control. TF filed a joint patent application on this new approach to chromatography-free determination of MWD with acknowledgment to DoE. The Tulane group obtained a 60MHz NMR during the project and recently completed the first work on separating three comonomers, Am, SS, and Na-acrylate, with a first demonstration of terpolymer composition control with the TF basic principles controller. Widespread dissemination of ACOMP/CI in the polymer manufacturing sector will bolster DoE goals of energy efficiency and reduced GHG emissions: The ability to monitor and actively control polymerization reactions will lead to more efficient use of energy and non-renewable resources, plant and labor time, increase the safety of manufacturing personnel, and will enhance product quality and lead to feasibility of manufacturing of polymers currently too complex for industrial scale production, while leading to less GHG emissions per kilo of product, and allowing for increased U.S. competitiveness in this enormous manufacturing sector. When ACOMP/CI is expanded to the polyolefin industry it is estimated that 60 TeraBTU/year of energy can be saved. Much of this saving is anticipated to come from optimized control of grade changeovers in steady state reactors and maintenance of steady states. Conclusions: ACOMP’s ability to provide continuous realtime data streams of measured polymer and reaction characteristics made it possible, for the first time, to directly and automatically control free radical polymerization reactions. An industrial client of Fluence Analytics has requisitioned the first ACOMP/CI which uses the TF basic principles controller. This sets the stage for FA to add control features to the ACOMP systems it has begun to install on the industrial scale beginning in 2014. Recommendations: This successful project was mainly limited to ideal polymerizations not of an industrial sort. The most energy intensive portion of polymer manufacturing is polyolefins. Adoption of ACOMP/CI to this enormous industrial sector faces the enormous challenges of high temperature, high pressure continuous sampling and high temperature sensor operation to obtain the continuous data needed for direct reaction control. The project team has a strategy for achieving this ambitious goal and will present it in Fall 2017 as a proposal to CESMII/DoE. It is recommended that this upcoming proposal be funded in order to make full use of the achievements of this just ended DoE project as the next step towards making polyolefin ACOMP/CI an energy saving reality. It is projected that ACOMP/CI can have its first polyolefin testbed demonstrations within two years of beginning the proposed project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Atomic Iron and Nickel in the Coma of C/1996 B2 (Hyakutake): Production Rates, Emission Mechanisms, and Possible Parents

Abstract Two papers recently reported the detection of gaseous nickel and iron in the comae of over 20 comets from observations collected over two decades, including interstellar comet 2I/Borisov. To evaluate the state of the laboratory data in support of these identifications, we reanalyzed archived spectra of comet C/1996 B2 (Hyakutake), one of the nearest and brightest comets of the past century, using a combined experimental and computational approach. We developed a new, many-level fluorescence model that indicates that the fluorescence emissions of Fe I and Ni I vary greatly with heliocentric velocity. Combining this model with laboratory spectra of an Fe-Ni plasma, we identified 22 lines of Fe I and 14 lines of Ni I in the spectrum of Hyakutake. Using Haser models, we estimate the nickel and iron production rates as Q Ni = (2.6–4.1) × 10 22 s −1 and Q Fe = (0.4–2.8) × 10 23 s −1 . From derived column densities, the Ni/Fe abundance ratio log 10 [Ni/Fe] = −0.15 ± 0.07 deviates significantly from solar abundance ratios, and it is consistent with the ratios observed in solar system comets. Possible production and emission mechanisms are analyzed in the context of existing laboratory measurements. Based on the observed spatial distributions, excellent fluorescence model agreement, and Ni/Fe ratio, our findings support an origin consisting of a short-lived unknown parent followed by fluorescence emission. Our models suggest that the strong heliocentric velocity dependence of the fluorescence efficiencies can provide a meaningful test of the physical process responsible for the Fe I and Ni I emission.

Bromley, S. J. (ORCID:0000000321108152)↗
NASA NTRS1999

Applications of Constituent Data Assimilation Systems

Organizations in Europe, Australia, and the United States have recently broadened constituent assimilation activities beyond that water vapor, which has been assimilated for years in the numerical weather prediction community. Many of these activities have focused on ozone, with some efforts focused on the entire suite of reactive constituents that control the ozone distribution. This talk will draw from results from the near real-time ozone data assimilation system being run by NASA's Data Assimilation Office. This system utilizes ozone observations from both the TOMS and the SBUV instrument to generate global synoptic maps of ozone. The initial application of this product is to provide ozone fields to assist in the atmospheric corrections' that are necessary for the retrieval of information from other NASA instruments. The validation of the ozone assimilation system shows that the assimilated product agrees well with independent HALOE and ozonesonde observations. This suggests that the product is of sufficient quality to be extended to other applications. This talk will enumerate these other applications and present initial results from exploratory research. The applications being considered include estimates of tropospheric ozone, provision of ozone fields for interactive retrievals, use of analysis increments from the assimilation to evaluate model performance, and development of long-term consistent three-dimensional global ozone fields. The results from the exploratory studies are promising, and help demonstrate how assumptions made in the p development of the ozone assimilation impact the other applications. For instance, RMS errors in the current product are large near the tropopause, which is sensitive to the specification of vertical correlation functions, which in turns impacts the amount of ozone analyzed to be in the troposphere. How these sensitivities impact the different applications will also be discussed.

Rood, Richard B.↗
NASA NTRS2008

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗
DOE OSTI2025

Uncertainty estimation of bifurcated solutions in the Rayleigh–Bénard problem for advanced nuclear reactors applications

Multiphysics models of nuclear reactors frequently comprise nonlinear systems of equations. The nonlinear nature of these models could lead to solution bifurcations, where a small change in a certain parameter, e.g., the thermophysical properties of the coolant, can lead to a sudden change in the system’s behavior. At the point in parameter space where this happens, called a critical point, the Jacobian matrix of the model’s nonlinear operator becomes singular potentially permitting multiple solutions to coexist. In this paper, we perform uncertainty estimation (UE) in a parameter range that includes bifurcated solutions within the context of Rayleigh–Bénard problem. We perform this analysis assuming uncertain temperature difference, and tilt angle for the iterative solution algorithm with a unit Prandtl number (Pr = 1). Also, we perform this analysis under uncertain thermophysical properties for both FLiBe molten salt and liquid sodium as working fluid. We deploy two approaches to compute statistical moments for the resulting distributions of selected flow-field variables. The first approach is the blind computation of the mean and the standard deviation without any consideration of solution bifurcation, while the second approach utilizes k-means clustering to cluster each branch’s solutions together and compute separate statistical moments for each branch. The statistical distributions are obtained by perturbing the selected parameters about nominal values that correspond to a solution on one of the valid branches, and that solution is used as initial guess for the iterative solution algorithm. We found that perturbation of any parameter when its nominal value is close to its critical point always leads to branch jumping, i.e., the iterations converge to a solution on a branch different from the branch of the initial guess. This produces a statistical ensemble comprised of fundamentally different solutions leading to wrong mean values and uncertainty estimates, whereas clustering provides an efficient way to deal with this type of computation. This work is important for developing Gen IV nuclear systems because many of these systems rely on natural convection for cooling especially in accident conditions.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

High-Performance Integrated Window and Façade Solutions for California

The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real Time Effective Impedance Estimation for Power System State Estimation

Here, we introduce two tools-the Effective Impedance State Estimator (EISE), and the Real Time Effective Impedance Estimator (RTEIE). The EISE is novel in that it is an entirely data-driven state estimator, and does not require a network model. Thus, the EISE is well suited for applications in which an accurate network model is not available. Instead of using a network impedance model, the EISE uses an effective impedance network model that is learned online by the RTEIE. The RTEIE recursively estimates the effective impedance network model using phasor measurement unit (PMU) measurements. The mathematical reasoning for using an effective impedance model, rather than a full network impedance model, is given. The recursive estimation framework allows the RTEIE to take the entire history of phasor measurements into account to produce a model estimate, while still adjusting to changes in the network impedance due to external factors such as topology changes and temperature. The merits of the RTEIE and EISE are demonstrated by comparing the accuracy of the EISE with a conventional state estimator on a toy network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.

Active-layer thickness↗