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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Gaseous Argon-Based Near Detector to Enhance the Physics Capabilities of DUNE

This document presents the concept and physics case for a magnetized gaseous argon-based detector system (ND-GAr) for the Deep Underground Neutrino Experiment (DUNE) Near Detector. This detector system is required in order for DUNE to reach its full physics potential in the measurement of CP violation and in delivering precision measurements of oscillation parameters. In addition to its critical role in the long-baseline oscillation program, ND-GAr will extend the overall physics program of DUNE. The LBNF high-intensity proton beam will provide a large flux of neutrinos that is sampled by ND-GAr, enabling DUNE to discover new particles and search for new interactions and symmetries beyond those predicted in the Standard Model.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

An Online Prototype Toolset for Predicting and Optimizing P&T Performance (FY23 Status Report)

A new web-based toolset is being developed to support ongoing remediation optimization efforts and implementation of an adaptive site management strategy for the 200 West Area Pump-and-Treat (P&T) system at the Hanford Site. This toolset, comprising the well performance index tool and the well optimization pre-screening tool, will offer a user-friendly interface to predict and optimize the P&T well network’s performance at a preliminary level. Efforts in fiscal year (FY) 2023 focused on three main components: updating the existing deep learning model for predicting P&T performance, designing and developing a prototype of a web-based performance index tool, and initiating the conceptual design of the well optimization pre-screening tool. The well performance index tool is based on a pre-trained deep learning model that allows users to select a target contaminant and well screen length, then visualize the predicted performance of potential new wells across the site. The well optimization pre-screening tool includes two separate modules: the pre-computed scenario viewer, which organizes and visualizes offline optimization simulation results, and the quick analysis module, which provides real-time model prediction using user-specified well locations. In FY24, the plan is to add web-based applications to SOCRATES for both the well performance prediction tool and the optimization prescreening tool, with accompanying user and theory guides. These tools are intended to enable an accessible, easily applied, and transparent approach to remedy planning and decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) - Deliverable Task 7: Risk Assessment

The “Optimizing Alabama’s CO 2 Storage in Shelby County: Project OASIS” CarbonSAFE Phase II Project seeks to build on regional data sets that demonstrate that the subsurface within Shelby County, Alabama has the potential to store commercial volumes of CO 2 safely, permanently, and economically. The primary target CO 2 Storage Complex is the deep Ketona Dolomite located within a 140 square mile area of the Valley and Ridge Region of Alabama. This deep saline reservoir is beneath a confining system encompassing at least 6,500 ft of shales and other low permeability sediments. Project OASIS drilled a deep stratigraphic test well to confirm the geological properties of the confining system and storage reservoir(s) within the Storage Complex. The geological data was incorporated into numerical models to establish the areal extent of the CO 2 plume and help design the storage site and its monitoring system. The project is managed by the Southern States Energy Board (SSEB), an interstate compact organization consisting of governors and state legislative leaders from sixteen southern states, Puerto Rico, and the U.S. Virgin Islands, as well as an appointee by the President of the United States. The organizational compact provides it with access to state government organizations and legislatures. The Board also maintains an Associate Members program comprised of energy resource companies, utilities, trade groups, academic R&D science and technology experts and energy consultants. Further, the SSEB staff is experienced in managing and coordinating complex energy and environmental programs, from research programs to full-scale design and demonstrations of new and innovative technologies. Project OASIS is a public-private partnership of six entities with multiple principal investigators (PIs). SSEB’s Lead PI and Co-PI are responsible for all aspects of project performance in accordance with the DOE-NETL Cooperative Agreement. SSEB has issued subgrants to Advanced Resources International, Inc., Alabama A&M University, Auburn University, Crescent Resource Innovation, and Oklahoma State University. Advanced Resources International, Inc., issued subgrants to Baker Hughes and Loudon Technical Services for field services

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1992

Design of small Stirling dynamic isotope power system for robotic space missions

Design of a multihundred-watt Dynamic Isotope Power System (DIPS) based on the U.S. Department of Energy (DOE) General Purpose Heat Source (GPHS) and small (multihundred-watt) free-piston Stirling engine (FPSE) technology is being pursued as a potential lower cost alternative to radioisotope thermoelectric generators (RTG's). The design is targeted at the power needs of future unmanned deep space and planetary surface exploration missions ranging from scientific probes to Space Exploration Initiative precursor missions. Power level for these missions is less than a kilowatt. Unlike previous DIPS designs which were based on turbomachinery conversion (e.g. Brayton), this small Stirling DIPS can be advantageously scaled down to multihundred-watt unit size while preserving size and mass competitiveness with RTG's. Preliminary characterization of units in the output power ranges 200-600 We indicate that on an electrical watt basis the GPHS/small Stirling DIPS will be roughly equivalent to an advanced RTG in size and mass but require less than a third of the isotope inventory.

Bents, D. J.↗
NASA NTRS1994

Hubble Space Telescope Medium Deep Survey. 2: Deconvolution of Wide Field Camera field galaxy images in the 13 hour + 43 deg field

We present isophotal profiles of six faint field galaxies from some of the first deep images taken for the Hubble Space Telescope (HST) Medium Deep Survey (MDS). These have redshifts in the range z = 0.126 to 0.402. The images were taken with the Wide Field Camera (WFC) in `parallel mode' and deconvolved with the Lucy method using as the point-spread function nearby stars in the image stack. The WFC deconvolutions have a dynamic range of 16 to 20 dB (4 to 5 mag) and an effective resolution approximately less than 0.2 sec (FWHM). The multiorbit HST images allow us to trace the morphology, light profiles, and color gradients of faint field galaxies down to V approximately equal to 22 to 23 mag at sub-kpc resolution, since the redshift range covered is z = 0.1 to 0.4. The goals of the MDS are to study the sub-kpc scale morphology, light profiles, and color gradients for a large samole of faint field galaxies down to V approximately equal to 23 mag, and to trace the fraction of early to late-type galaxies as function of cosmic time. In this paper we study the brighter MDS galaxies in the 13 hour + 43 deg MDS field in detail, and investigate to what extent model fits with pure exponential disks or a(exp 1/4) bulges are justified at V approximately less than 22 mag. Four of the six field galaxies have light profiles that indicate (small) inner bulges following r(exp 1/4) laws down to 0.2 sec resolution, plus a dominant surrounding exponential disk with little or no color gradients. Two occur in a group at z = 0.401, two are barred spiral galaxies at z = 0.179 and z = 0.302, and two are rather subluminous (and edge-on) disk galaxies at z = 0.126 and z = 0.179. Our deep MDS images can detect galaxies down to V, I approximately less than 25 to 26 mag, and demonstrate the impressive potential of HST--even with its pre-refurbished optics--to resolve morphological details in galaxies at cosmologically significant distances (v approximately less than 23 mag). Since the median redshift of these galaxies is approximately less than 0.4, the HST resolution allows us to study sub kpc size scales at the galaxy, which cannot be done with stable images over wide fields from the best ground-based sites.

Windhorst, R. A.↗
NASA NTRS2002

Orbit Determination Issues for Libration Point Orbits

Libration point mission designers require knowledge of orbital accuracy for a variety of analyses including station keeping control strategies, transfer trajectory design, and formation and constellation control. Past publications have detailed orbit determination (OD) results from individual libration point missions. This paper collects both published and unpublished results from four previous libration point missions (ISEE (International Sun-Earth Explorer) -3, SOHO (Solar and Heliospheric Observatory), ACE (Advanced Composition Explorer) and MAP (Microwave Anisotropy Probe)) supported by Goddard Space Flight Center's Guidance, Navigation & Control Center. The results of those missions are presented along with OD issues specific to each mission. All past missions have been limited to ground based tracking through NASA ground sites using standard range and Doppler measurement types. Advanced technology is enabling other OD options including onboard navigation using seaboard attitude sensors and the use of the Very Long Baseline Interferometry (VLBI) measurement Delta Differenced One-Way Range (DDOR). Both options potentially enable missions to reduce coherent dedicated tracking passes while maintaining orbital accuracy. With the increased projected loading of the DSN (Deep Space Network), missions must find alternatives to the standard OD scenario.

Beckman, Mark↗
NASA NTRS2005

Astrobiology and the Exploration of Gusev Crater by the Mars Exploration Rover Spirit

We assess the availability of nutrient elements, energy and liquid water on the plains surrounding Columbia Memorial Station by evaluating data from Spirit in the context of previous Mars missions, Earth-based studies of martian meteorites and studies of microbial communities on Earth that represent potential analogs of martian biota. The compositions of Gusev basalts resemble those of olivine basalts beneath the seabed on Earth that deep drilling has shown to support life. Of particular relevance to biology, phosphate abundances are much greater in Gusev basalts (0.84 +/- 0.07 wt. % P2O5) than in oceanic basalts (typically 0.06 wt. %).

DesMarais, I. David↗
NASA NTRS2015

The Use of Field Programmable Gate Arrays (FPGA) in Small Satellite Communication Systems

This paper will describe the use of digital Field Programmable Gate Arrays (FPGA) to contribute to advancing the state-of-the-art in software defined radio (SDR) transponder design for the emerging SmallSat and CubeSat industry and to provide advances for NASA as described in the TAO5 Communication and Navigation Roadmap (Ref 4). The use of software defined radios (SDR) has been around for a long time. A typical implementation of the SDR is to use a processor and write software to implement all the functions of filtering, carrier recovery, error correction, framing etc. Even with modern high speed and low power digital signal processors, high speed memories, and efficient coding, the compute intensive nature of digital filters, error correcting and other algorithms is too much for modern processors to get efficient use of the available bandwidth to the ground. By using FPGAs, these compute intensive tasks can be done in parallel, pipelined fashion and more efficiently use every clock cycle to significantly increase throughput while maintaining low power. These methods will implement digital radios with significant data rates in the X and Ka bands. Using these state-of-the-art technologies, unprecedented uplink and downlink capabilities can be achieved in a 1/2 U sized telemetry system. Additionally, modern FPGAs have embedded processing systems, such as ARM cores, integrated inside the FPGA allowing mundane tasks such as parameter commanding to occur easily and flexibly. Potential partners include other NASA centers, industry and the DOD. These assets are associated with small satellite demonstration flights, LEO and deep space applications. MSFC currently has an SDR transponder test-bed using Hardware-in-the-Loop techniques to evaluate and improve SDR technologies.

Varnavas, Kosta↗
NASA NTRS2019

New Horizons in Cosmology with Spectral Distortions of the Cosmic Microwave Background

Following the pioneering observations with COBE in the early 1990s, studies of the cosmic mi- crowave background (CMB) have primarily focused on temperature and polarization anisotropies. CMB spectral distortions – tiny departures of the CMB energy spectrum from that of a perfect blackbody – provide a second, independent probe of fundamental physics, with a reach deep into the primordial Universe. The theoretical foundation of spectral distortions has seen major advances in recent years, highlighting the immense potential of this emerging field. Spectral distortions probe a fundamental property of the Universe – its thermal history – thereby providing additional insight into processes within the cosmological standard model(I) (CSM) as well as new physics beyond. Spectral distortions are an important tool for understanding inflation and the nature of dark matter. They shed new light on the physics of recombination and reionization, both prominent stages in the evolution of our Universe, and furnish critical information on baryonic feedback processes, in addition to probing primordial correlation functions at scales inaccessible to other tracers. In principle the range of signals is vast: many orders of magnitude of discovery space can be explored by detailed observations of the CMB energy spectrum. Several CSM signals are predicted and provide clear experimental targets that are observable with present-day technology. Confirmation of these signals would extend the reach of the CSM by orders of magnitude in physical scale as the Universe evolves from the initial stages to its present form. Their absence would pose a huge theoretical challenge, immediately pointing to new physics. Here, we advocate for a dedicated effort to measure CMB spectral distortions at the largest angular scales (greater than approximately 1°) within the ESA Voyage 2050 Program. We argue that an L-class mission with a pathfinder would allow a precise measurement of all the expected CSM distortions. With an M-class mission, the primordial distortions (created at z >~ 10(exp 3)) would still be detected at modest significance, while the late-time distortions will continue to be measured to high accuracy. Building on the heritage of COBE/FIRAS, a spectrometer that consists of multiple, cooled (approximately equal to 0.1 K), absolutely-calibrated Fourier Transform Spectrometers (FTS) with wide frequency coverage (ν approximately equal to 10 GHz to a few x THz) and all-sky spectral sensitivity at the level of 0.1 0.5 Jy/sr would be the starting point for the M-class option. A scaled and further optimized version of this concept is being envisioned as the L-class option. Such measurements can only be done from space and would deliver hundreds of absolutely-calibrated maps of the Universe at large scales, opening numerous science opportunities for cosmology and astrophysics. This will provide independent probes of inflation, dark matter and particle physics, recombination and the energy output of our Universe from at late times, turning the long-standing spectral distortion limits of COBE/FIRAS into clear detections.

Chluba, J.↗
NASA NTRSDate not supplied

An Open-Science Approach to Address Individual Response to Simulated GCR In Genetically Diverse Populations of Mice and Humans

This project addresses the challenge of understanding and predicting individual radiation sensitivity by integrating genetics, demographics and biomarker characteristics across species (mice and humans). We hypothesize that ex vivo DNA repair response to GCR components is a central determinant of cancer risk from space radiation and can serve as a biomarker of radiation risk in combination with genetics. Automated image quantification of 53BP1+ radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET in non-immortalized primary skin fibroblasts derived from 76 mice across 15 strains (5 inbred reference strains and 10 collaborative-cross strains) exposed to X rays (0.1, 1 and 4 Gy), 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm), as well as in peripheral blood mononuclear cells (PBMCs) from 768 healthy donors (matched ethnicity, 50/50 male/female, 18-70 years old) exposed to gamma rays (0.1 and 1 Gy), 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm). A genome-wide association study (GWAS) was performed on the mouse strains between DNA damage responses to space radiation and single nucleotide polymorphisms (SNPs). We found SNPs, which were significantly associated to the RIF phenotype, mapped to genes and pathways that are functionally linked to health hazards for deep space exploration (e.g. carcinogenesis, nervous system damage and immune dysfunction). Some of these SNPs were located within protein coding regions, potentially interfering with protein functions and providing promising genetic targets for countermeasures. We also found correlations between both spontaneous and radiation-induced DNA damage and SNPs mapped to pathways associated with cellular metabolism. GWAS is undergoing for the human data. All data have been made available via the NASA Space Biology Open-Science database (genelab.nasa.gov) and we will discuss how various genomic and transcriptomic datasets can be accessed for modeling and integrated using machine learning methods for discovering new radiation biology.

Sylvain V Costes↗
NASA NTRSDate not supplied

Sex differences and deep space stressors: effects of 5-ion gcrsim, simulated microgravityand social isolation on immune function, brain, and behavior in mice

This project is testing the hypothesis that Ionizing Radiation (IR), microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure/function, and neurobehavioral/cognitive performance. Specific Aims for this project are to: (1) Determine dose-response curves for acute ‘Five-Ion GCR Simulation’ exposure for immune, brain and performance responses in crew age-matched adult male and female mice; (2) Determine effects of acute ‘Five-Ion GCR Simulation’ exposure singly and in combination with simulated microgravity and social isolation, on immune, brain and performance responses in crew age-matched male and female mice mimicking deep space missions; and (3) Determine efficacy of the dietary antioxidant, Nicotinamide Mononucleotide (NMN), a key intermediate in nicotinamide adenine dinucleotide (NAD+) biosynthesis. Here we report findings from our studies of mature (24-week-old) male and female mice exposed to simulated 5-Ion GCRsim (0, 5, 15, or 50cGy) at the NASA Space Radiation Laboratory (NSRL) followed by combinatorial exposures to 15cGy, simulated microgravity via head-down tilt (hindlimb unloading) and social isolation. Immune, brain and behavioral (sensorimotor, risk-taking & cognitive) measures were acquired at ‘Acute’ (IR+24hrs, IR+72hrs), ‘Intermediate’ (IR+14 days) and ‘Delayed’ (IR+28 to IR+124 days) to inform biological responses anticipated during a transit to Mars. This project addresses NASA’s efforts to characterize risks and identify appropriate countermeasures in both women and men in anticipation of future deep space missions. Ensuring crew health and performance during extended transits necessitates that sensorimotor and cognitive abilities remain strong to avoid potentially catastrophic health and safety outcomes. Supported by the NASA Human Research Program (HRP) Human Factors Behavioral Performance Element Grant 18 18FLAG 2 0028.

behavioral sciences↗
NASA NTRSDate not supplied

Performance Analysis of Magnetohydrodynamic Drag Modulation for Actively Controlled Aerocapture at Neptune

Missions to the Ice Giants are a top priority for flagship missions this coming decade. However, a fully propulsive orbital insertion into these planets requires an immense amount of fuel, taking a significant portion of the spacecraft mass and restricting the scientific payload. To mitigate this, aerocapture has been heavily investigated. Although simulations have shown that aerodynamically controlled aerocapture can successfully insert into an orbit around both Ice Giants, the deep atmospheric pass required necessitates a complex, mass expensive, and sometimes prohibitive thermal protection system. Magnetohydrodynamic drag modulation serves as a potential alternative control method for aerocapture which could not only save propellant mass compared to fully propulsive orbital insertion, but also save thermal protection system mass compared to conventional aerocapture methods. Both aerodynamically controlled and magnetohydrodynamically controlled aerocapture methodologies were simulated in NASA Langley’s high-fidelity six degree-of-freedom flight dynamics code, the Program to Optimize Simulated Trajectories II. Each method was simulated to identical missions to Neptune using a numerical predictor-corrector algorithm to optimize the control towards the target orbit. The results concluded that magnetohydrodynamic drag modulation can successfully capture and performs on par with aerodynamic drag modulation while significantly reducing the heatflux and aeroshell complexity.

Danny N Nguyen↗
DOE OSTI2017

Semiconductor Reliability Testing Data Management

iT2 Technologies is a startup developing analytical software and creating automated workflow environment in the area of big data in IC reliability. The main beneficiaries of the iT2 software will be the semiconductor companies as they will see significant savings in terms of time and cost. They will be able to efficiently perform the analysis of large amount of reliability data. A better standard of reliability and quality will also lead to the improvement in public safety in consumer, automotive, medical, and military applications. Smarter and thorough testing will reduce the risk of faulty hardware getting into the hands of the end users. The software is being developed and designed within the United States and will help keep the prominence of US in the cutting edge of high tech space. iT2 is establishing strong relations with its potential customers thanks to its key players being involved in this industry for the past several years and, thus, having a deep understanding of the market. The target clients will be all major semiconductor suppliers such as Intel, Qualcomm, Texas Instruments, OnSemi, and Broadcom and their customers including Apple, Cisco, IBM, HP, and Dell. The iT2 software will be used in a business-to-business environment for sharing engineering data and communicating results between these two classes of customers - some of which are participating in the beta testing of the iT2 software.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Capacity Density Considerations for Floating Offshore Wind Farms in Ultradeep Waters

Capacity density describes the concentration of wind energy development in an area and is often specified in terms of megawatts-per-square-kilometer (MW/km2). Understanding capacity density trends in wind energy projects helps to inform both energy system and spatial planning efforts. Borrman et al. (2018) and Mulas Hernando et al. (2023) analyze capacity density trends for fixed-bottom offshore wind farms in Europe and the United States, respectively, and Cooperman et al. (2022) explores how floating offshore wind mooring technology choices may impact wind plant layout through setbacks from lease area boundaries in waters up to 1,300 m deep. Technical challenges facing floating offshore wind development in ultradeep waters (beyond 1,300 m) could impact achievable capacity densities, with potential implications to marine spatial planning and project economics. When compared to fixed-bottom commercial-scale wind farms, mooring system footprints from floating offshore wind systems can constrain capacity density in some circumstances. In this study, we conduct an initial investigation of how taut mooring configurations may constrain floating offshore wind turbine placement and estimate capacity density for representative floating wind plants in generic lease areas. In addition, we explore floating wind plant capacity density drivers in ultradeep waters by characterizing area utilization for a range of lease area characteristics. This analysis highlights the primary challenges that floating offshore wind systems may encounter in achieving capacity densities comparable to commercial-scale fixed-bottom projects at ultradeep water depths, from a technical standpoint.

capacity density↗
DOE OSTI2012

Iodine Sorbent Performance in FY 2012 Deep Bed Tests

Nuclear fission results in the production of fission products and activation products, some of which tend to be volatile during used fuel reprocessing and evolve in gaseous species into the reprocessing facility off-gas systems. Analyses have shown that I-129, due to its radioactivity, high potential mobility in the environment, and high longevity (half life of 15.7 million years), can require control efficiencies of up to 1,000x or higher to meet regulatory emission limits. Iodine capture is an important aspect of the Separations and Waste Forms Campaign Off-gas Sigma Team (Jubin 2011, Pantano 2011). Deep-bed iodine sorption tests for both silver-functionalized Aerogel and silver zeolite sorbents were performed during Fiscal Year 2012. These tests showed that: • Decontamination factors were achieved that exceed reasonably conservative estimates for DFs needed for used fuel reprocessing facilities in the U.S. to meet regulatory requirements for I-129 capture. • Silver utilizations approached or exceeded 100% for high inlet gas iodine concentrations, but test durations were not long enough to approach 100% silver utilization for lower iodine concentrations. • The depth of the mass transfer zone was determined for both low iodine concentrations (under 10 ppmv) and for higher iodine concentrations (between 10-50 ppmv); the depth increases over time as iodine is sorbed. • These sorbents capture iodine by chemisorption, where the sorbed iodine reacts with the silver to form very non-volatile AgI. Any sorbed iodine that is physisorbed but not chemically reacted with silver to form AgI might not be tightly held by the sorbent. The portion of sorbed iodine that tends to desorb because it is not chemisorbed (reacted to form AgI) is small, under 1%, for the AgZ tests, and even smaller, under 0.01%, for the silver-functionalized Aerogel.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Synchrophasor Measurements-based Events Detection Using Deep Learning

Deep learning algorithms have been developed for phasor measurement units (PMUs) analysis aiming at providing grid operators to observe and react to significant real-time changes in the grid associated with multiple factors (e.g., power generation and load variations, different type of faults, and equipment mailfunction), or for offline post-event system diagnostics. In this study, a Long Short-Term Memory (LSTM)-based deep neural network (DNN) is adopted and evaluated to identify the most appropriate model configurations for event detection and longer-term anomalous pattern extraction. The proposed DNN model shows the potential on long-term predictions with the ability to capture nonlinear and nonstationary mixture complex patterns in PMU datasets. Real-world PMU in the WECC system were used for model development and validation.

deep learning↗
DOE OSTI2023

Advances in solar forecasting: Computer vision with deep learning

Renewable energy forecasting is crucial for integrating variable energy sources into the grid. It allows power systems to address the intermittency of the energy supply at different spatiotemporal scales. To anticipate the future impact of cloud displacements on the energy generated by solar facilities, conventional modeling methods rely on numerical weather prediction or physical models, which have difficulties in assimilating cloud information and learning systematic biases. Augmenting computer vision with machine learning overcomes some of these limitations by fusing real-time cloud cover observations with surface measurements acquired from multiple sources. This Review summarizes recent progress in solar forecasting from multisensor Earth observations with a focus on deep learning, which provides the necessary theoretical framework to develop architectures capable of extracting relevant information from data generated by ground-level sky cameras, satellites, weather stations, and sensor networks. Overall, machine learning has the potential to significantly improve the accuracy and robustness of solar energy meteorology; however, more research is necessary to realize this potential and address its limitations.

14 SOLAR ENERGY↗