SEARCH · Engineering Papers

Results for “uncertain systems”

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.

SourceResearch connectionFrom yearThrough year

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

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods

We report home energy management systems (HEMS) have been shown to reduce energy bills and to provide grid services including peak demand reduction and demand flexibility. However, uncertainty in residential energy systems is a significant issue and can reduce the benefits of a HEMS to the homeowner or grid operator. Sources of uncertainty include weather forecasts, predictions of energy-related occupant activities (e.g., hot water draws), and parameter estimation for the building envelope and energy-consuming equipment. This paper tackles the problem of uncertainty by developing a framework that simulates HEMS in uncertain conditions and evaluates the performance of multiple control strategies. A linear, reduced-order residential building model for model predictive control applications is derived and compared to a full-order model. Stochastic model predictive control is shown to perform better than deterministic and heuristic methods when considering realistic forecasts with uncertainty. The framework can evaluate the performance of HEMS in real-world applications, which can help de-risk HEMS deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1994

An analysis code for the Rapid Engineering Estimation of Momentum and Energy Losses (REMEL)

Nonideal behavior has traditionally been modeled by defining efficiency (a comparison between actual and isentropic processes), and subsequent specification by empirical or heuristic methods. With the increasing complexity of aeropropulsion system designs, the reliability of these more traditional methods is uncertain. Computational fluid dynamics (CFD) and experimental methods can provide this information but are expensive in terms of human resources, cost, and time. This report discusses an alternative to empirical and CFD methods by applying classical analytical techniques and a simplified flow model to provide rapid engineering estimates of these losses based on steady, quasi-one-dimensional governing equations including viscous and heat transfer terms (estimated by Reynold's analogy). A preliminary verification of REMEL has been compared with full Navier-Stokes (FNS) and CFD boundary layer computations for several high-speed inlet and forebody designs. Current methods compare quite well with more complex method results and solutions compare very well with simple degenerate and asymptotic results such as Fanno flow, isentropic variable area flow, and a newly developed, combined variable area duct with friction flow solution. These solution comparisons may offer an alternative to transitional and CFD-intense methods for the rapid estimation of viscous and heat transfer losses in aeropropulsion systems.

Dechant, Lawrence J.↗

DOE OSTI2021

Representing DC-Coupled PV+Battery Hybrids in a Capacity Expansion Model

Recent technology cost and performance improvements and the federal investment tax credit (ITC) have driven growing interest in coupling solar photovoltaic (PV) and battery systems. Combining these technologies into co-located or hybridized PV+battery systems has the potential to lower costs and increase energy output relative to multiple independent systems. In this work, we provide an overview of PV+battery systems and demonstrate methods for incorporating them into NREL’s Regional Energy Deployment System (ReEDS) capacity expansion model. Although the methods are applied to a specific model, we anticipate that the approaches used here can be useful for informing PV+battery method development for other capacity expansion models. The implemented method relies heavily on the native representations of PV and battery technologies; therefore, the focus of this work is on capturing and parameterizing the interactions between them for a configuration in which the PV and battery technologies share a single bi-directional inverter. This work also demonstrates the impacts of including PV+battery systems in the ReEDS optimization for the conterminous United States through 2050. In particular, we perform parametric sensitivities for input assumptions that are uncertain and expected to influence PV+battery deployment levels, including (a) the cost of PV+battery systems relative to independent PV and battery systems, (b) the battery component’s qualification for the ITC, and (c) future cost trajectories for PV and battery systems. We find that PV+battery deployment could occur throughout the conterminous United States if there are cost savings associated with DC coupling PV and battery technologies. If even modest (5%) cost savings can be achieved (through a shared inverter and balance-of-system costs), then approximately one-third of utility-scale PV deployment through 2050 adopts the DC-coupled hybrid configuration, resulting in total PV+battery deployment that exceeds the magnitude of PV+battery projects in U.S. interconnection queues in 2020. If greater cost savings can be achieved through DC coupling (e.g., due to a growing amount of shared balance-of-system costs, reduced financial risk, or modularity) or more rapid cost and performance improvements are realized for PV and battery technologies, then total PV+battery deployment and the share of PV and battery deployment that adopts the hybrid configuration grows (to >50%). In all cases, growing PV+battery deployment primarily displaces independent PV and battery technologies, indicating the strong competition between the hybrid and independent configurations comprising technologies with similar performance characteristics.

14 SOLAR ENERGY↗

DOE OSTI2020

The domestic and international implications of future climate for U.S. agriculture in GCAM

Agriculture yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally (via international commodity markets). How important to U.S. agriculture are domestic changes due to climate compared to those occurring externally? Here we show that potential direct impacts to United States agriculture have financial impacts on U.S. producers that are roughly similar in magnitude but opposite in sign to impacts on U.S. producers due to changes in other parts of the world. This finding is robust across application of a wide range of potential future crop yield impacts applied to a multi-sector global integrated assessment model. Therefore, when examining country-specific impacts, it is necessary to model both the domestic and international impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Impacts of Climate Change on Energy Systems in Global and Regional Scenarios

A growing number of studies report the impact of climate change on the supply, demand, transport, and cost of energy. However, there is lack of comprehensive overview and understanding of climate change impacts on energy across technologies and scales. Here, we conduct a systematic assessment of results from 186 papers on potential impacts of climate change on energy. Results show that increased cooling demand and decreased heating demand is anticipated globally. Similarly, increases in bio-energy and hydro power and a possible decrease in thermal electricity supply is projected. Overall changes in heating and cooling demand, increased thermal cooling, and reduced hydropower supply in Europe, India and Latin America are projected 35 at the regional scale. Furthermore, our review revealed that studies use a wide range of inconsistent methods and data sources. To move forward, the study proposes a consistent multi-model assessment framework for a comprehensive understanding of climate impacts on energy.

Yalew, Seleshi G.↗

DOE OSTI2021

Land Surface Modeling 2.0 for agricultural climate change impact assessments

Focus Area: This white paper addresses DOE AI4ESP focus area #2 by providing a sketch blueprint for a next generation, hybrid AI/process-based global Land Surface Modeling (LSM) framework to improve projections of climate change impacts on the land surface system including agriculture and the hydrological cycle. Science Challenge: Climate change impacts on agriculture are highly uncertain: -50% to +150% global production changes for major grains under high-end climate change, for example. The core challenge in land surface system predictability is the large gap between the scale at which the relevant biological processes act and the scale at which the risks need to be assessed. Conventional empirical and process-based modeling approaches are insufficient. A new multi-scale modeling paradigm which employs AI/ML to learn from new streams of remote sensing data and targeted ’gene-to-global’ simulations is needed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive online grid emergency control

Electric overloading conditions and contingencies put modern power systems at risk of voltage collapse and blackouts. Load shedding is crucial to maintain voltage stability for grid emergency control. However, the rule- or model-based schemes rely on accurate dynamic system models and face considerable challenges in adapting to various operating conditions and uncertain event occurrences. Here, to address these issues, this paper proposes a novel deep reinforcement learning (DRL)-based voltage stability control algorithm with automatic entropy adjustment (AEA) for grid emergency control. Various dynamic network components for complex system operations are modeled to construct the DRL environment. An off-policy soft actor-critic architecture is developed to maximize the expected reward and policy entropy simultaneously. The AEA mechanism is proposed to facilitate the policy maximum entropy procedure, and the proposed method can automatically provide effective discrete and continuous actions against various fault scenarios. Our approach accomplishes high sampling efficiency, scalability, and auto-adaptivity of the control policies under high uncertainties. Comparative studies with the existing DRL-based control methods in IEEE benchmarks indicate salient performance improvement of the proposed method for dynamic system emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

An Observational Evaluation of RKW Theory over the U.S. Southern Great Plains

The theory of Rotunno et al. (“RKW” theory) addresses the behavior of squall-line cold pools in vertically sheared flows. It predicts that, within a given thermodynamic environment, a balance between baroclinic vorticity generation by the cold pool and low-level environmental vertical wind shear induces an upright updraft along the gust front that maximizes the initiation of new convective cells. Although this theory has been evaluated numerically, its applicability to observed systems remains unclear and is limited by a lack of critical measurements, including high-frequency thermodynamic and wind profiles across the gust front. Herein, observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM-SGP) observatory near Lamont, Oklahoma, are used to evaluate RKW theory for 10 well-observed squall lines over a 11-yr period. For this evaluation, RKW parameters including cold-pool intensity (c), low-level ambient, line-normal vertical shear (ΔV n ), subcloud and cloud-layer updraft tilts, and multiple measures of system intensity are estimated. Furthermore, the c estimates rely on thermodynamic retrievals from the Atmosphere Emitted Radiance Interferometer (AERI), which are uncertain but verify reasonably well against independent observations. As predicted by the theory, for c/ΔV n ≥ 1, c/ΔV n correlates positively with updraft tilt and negatively with system intensity, but these results are not always statistically significant and are also sensitive to the method by which ΔV n is evaluated. Specifically, ΔV n evaluations that extend above the cold-pool top yield greater consistency with RKW predictions. Also, some measures of intensity correlate more strongly with standard moist instability metrics than with RKW parameters.

Cold pools↗

NASA NTRSDate not supplied

ICESat-2 Mission: Status, Outlook, and Contributions to Polar Science

The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission carries the Advanced Topographic Laser Altimeter System (ATLAS) lidar to measure the changing height of Earth surface. After more than 3 years of science data collection, ATLAS has emitted well over a trillion laser pulses and continues to operate nominally. The ICESat-2 data products were initially released in May 2019, and have been used in over 150 peer-reviewed publications to date. Recent community white papers have noted the importance of ice elevation measurements for the coming decades, and as CryoSat-2 has entered it’s second decade and future missions are uncertain, ICESat-2 will be a critical part of the Earth System Observatory for the 2020s. In the polar regions, ICESat-2 has enabled year-round sea ice freeboard measurements as well as ice sheet elevation changes on seasonal, annual, and decadal time scales when combined with other missions. These data enable measurement of change at fine spatial and temporal scales to help understand or characterize the processes driving these observations. As of this presentation, Release 005 is the current version of the along-track data products, including surface-specific products for sea ice, land ice, ground and canopy height, ocean, and inland water heights. In addition, first versions of gridded data products for land ice, sea ice, and ocean are all available. Data spans the start of the mission (14 October 2018) through early 2022. The ICESat-2 project has also begun to produce and distribute QuickLook products with a nominal 3-day latency (as opposed to the ~45-day latency of the final data products). Initial versions of these QuickLook products have elevation accuracy of ~3 meters, and geolocation accuracy of ~50 meters. All products are available through the National Snow and Ice Data Center (nsidc.org). This presentation will summarize the current state and health of the observatory, current state of the ICESat-2 data products, data product quality assessment, and outlook for the future.

ICESat-2↗

DOE OSTI2022

Scalable Energy System Expansion Under Uncertainty Using Multi-Stage Stochastic Optimization

The intermittent nature of renewable energy sources poses challenges for electrical grids. This is due to the variable and uncertain nature of the power output from these resources. These features of renewable generation are more relevant to energy system planning as grids reach higher penetration levels of renewable energy. We present approaches for energy system planning based on scalable computational approaches which enable explicit consideration of operational uncertainties in the planning process. Using multi-stage stochastic programming and the progressive hedging algorithm, we compute energy system expansion decisions on modified versions of the RTS-GMLC test system.

electrical↗

NASA NTRSDate not supplied

Implementation of the Lifetime Method in Unsteady Pressure Sensitive Paint Measurements

At NASA Ames Research Center, unsteady pressure-sensitive paint (uPSP) measurements are obtained using the ‘intensity method’ which measures paint luminescence in response to a continuous, constant excitation. These measurements are obtained using high-speed cameras and are processed into fluctuating components of pressure. However, the nature of the intensity method also requires a separate steady state (time mean) pressure measurement to be obtained. This steady state measurement has typically been obtained using a separate set of PSP equipment that uses the ‘lifetime method’, which uses pulsed excitation to measure paint decay lifetime. If the lifetime method were implemented in the high-speed uPSP system, both the fluctuating and mean components of pressure could be obtained with a single system. This would greatly streamline setup, operations, and processing. In this paper, we describe work performed at the Fluid Mechanics Laboratory at NASA Ames to implement the lifetime method in our uPSP system. The uPSP acquisition system uses Phantom v2512 high-speed cameras, and it was initially uncertain if results of adequate quality could be obtained - their high framerate comes at the cost of several undesirable characteristics, which are explored in this paper. It was also uncertain if illumination using LED lamps, rather than a stronger source such as lasers, would be adequate. The data acquisition and data processing are discussed and the results analyzed. It was found that satisfactory lifetime method results can indeed be obtained using these high-speed cameras and LED lamps. This will allow the uPSP system to be greatly simplified and will have a large operational impact on how uPSP data is acquired in future wind tunnel tests.

Pressure Sensitive Paint↗

NASA NTRSDate not supplied

Implementation of the Lifetime Method in uPSP Measurements

Pressure Sensitive Paint↗

NASA NTRS2016

Impacts of Groundwater Pumping on Regional and Global Water Resources

Except frozen water in ice and glaciers (68%), groundwater is the world's largest distributed store of freshwater (30%), and has strategic importance to global food and water security. In this chapter, the most recent advances assessing human impact on regional and global groundwater resources are reviewed. This chapter critically evaluates the recently advanced modeling approaches quantifying the effect of groundwater pumping in regional and global groundwater resources and the evidence of feedback to the Earth system including sea‐level rise associated with groundwater use. At last, critical challenges and opportunities are identified in the use of groundwater to adapt to growing food demand and uncertain climate.

groundwater↗

DOE OSTI2021

Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in real-world power systems under contingencies. However, existing emergency control schemes are rule-based and cannot be adaptively applied to uncertain and floating operating conditions. Here, we propose an adaptive UVLS algorithm for emergency control via deep reinforcement learning (DRL) and expert systems. We first construct dynamic components for picturing the power system operation as the environment. The transient voltage recovery criteria, which poses time-varying requirements to UVLS, is integrated into the states and reward function to advise the learning of deep neural networks. The proposed method has no tuning issue of coefficients in reward functions, and this issue was regarded as a deficiency in the existing DRL-based algorithms. Case studies illustrate that the proposed method outperforms the traditional UVLS relay in both the timeliness and efficacy for emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Impact of dipolar molecules on the reliability of organic photovoltaic cells

Blending two non-fullerene acceptors (NFAs) to form bulk heterojunctions (BHJs) in ternary organic photovoltaics (OPVs) has been shown to lead to an end-capping exchange reaction that results in the generation of several new dipolar species whose impact on OPV operational stability remains uncertain. Here, we investigate the reliability of a ternary OPV system intentionally blended with dipolar NFA molecules. We reveal that an intrinsic contribution to OPV degradation is the reorganization and reorientation of the dipolar molecules during operation, which leads to an increased dielectric constant (ε r ) of the BHJ. Consequently, the electric field across the BHJ with dipolar molecules decreases compared with that of a non-dipolar BHJ under the same applied voltage, leading to a larger reduction in charge collection efficiency over time. This result has implications on the stability of a range of organic electronic devices containing dipolar molecules.

14 SOLAR ENERGY↗

DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

JobQueue-PG: A Task Queue for Coordinating Varied Tasks Across Multiple HPC Resources and HPC Jobs

The software allows for queueing and dispatch of tasks of small, varied, or uncertain runtimes across multiple HPC jobs, resources, and other computing systems. The software was designed to allow scientists to enqueue, run, and accumulate results from computational experiments in an efficient, manageable manner. For example, the software can be used to enqueue many small computational experiments and run them using several long-running multi-node HPC jobs that may or may not run simultaneously.

Tripp, Charles↗

NASA NTRS1987

Reasoning and planning in dynamic domains: An experiment with a mobile robot

Progress made toward having an autonomous mobile robot reason and plan complex tasks in real-world environments is described. To cope with the dynamic and uncertain nature of the world, researchers use a highly reactive system to which is attributed attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the system need only be partly elaborated before it decides to act. This allows the system to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of over-commitment common to previous planners. In addition, the system is continuously reactive and has the ability to change its goals and intentions as situations warrant. Thus, while the system architecture allows for reasoning about means and ends in much the same way as traditional planners, it also posseses the reactivity required for survival in complex real-world domains. The system was tested using SRI's autonomous robot (Flakey) in a scenario involving navigation and the performance of an emergency task in a space station scenario.

Georgeff, M. P.↗