28,647 research outputs found
An Integrated Multi-Time-Scale Modeling for Solar Irradiance Forecasting Using Deep Learning
For short-term solar irradiance forecasting, the traditional point
forecasting methods are rendered less useful due to the non-stationary
characteristic of solar power. The amount of operating reserves required to
maintain reliable operation of the electric grid rises due to the variability
of solar energy. The higher the uncertainty in the generation, the greater the
operating-reserve requirements, which translates to an increased cost of
operation. In this research work, we propose a unified architecture for
multi-time-scale predictions for intra-day solar irradiance forecasting using
recurrent neural networks (RNN) and long-short-term memory networks (LSTMs).
This paper also lays out a framework for extending this modeling approach to
intra-hour forecasting horizons thus, making it a multi-time-horizon
forecasting approach, capable of predicting intra-hour as well as intra-day
solar irradiance. We develop an end-to-end pipeline to effectuate the proposed
architecture. The performance of the prediction model is tested and validated
by the methodical implementation. The robustness of the approach is
demonstrated with case studies conducted for geographically scattered sites
across the United States. The predictions demonstrate that our proposed unified
architecture-based approach is effective for multi-time-scale solar forecasts
and achieves a lower root-mean-square prediction error when benchmarked against
the best-performing methods documented in the literature that use separate
models for each time-scale during the day. Our proposed method results in a
71.5% reduction in the mean RMSE averaged across all the test sites compared to
the ML-based best-performing method reported in the literature. Additionally,
the proposed method enables multi-time-horizon forecasts with real-time inputs,
which have a significant potential for practical industry applications in the
evolving grid.Comment: 19 pages, 12 figures, 3 tables, under review for journal submissio
The development of local solar irradiance for outdoor computer graphics rendering
Atmospheric effects are approximated by solving the light transfer equation, LTE, of a given viewing path. The resulting accumulated spectral energy (its visible band) arriving at the observer’s eyes, defines the colour of the object currently on the line of sight. Due to the convenience of using a single rendering equation to solve the LTE for daylight sky and distant objects (aerial perspective), recent methods had opt for a similar kind of approach. Alas, the burden that the real-time calculation brings to the foil had forced these methods to make simplifications that were not in line with the actual world observation. Consequently, the results of these methods are laden with visual-errors. The two most common simplifications made were: i) assuming the atmosphere as a full-scattering medium only and ii) assuming a single density atmosphere profile. This research explored the possibility of replacing the real-time calculation involved in solving the LTE with an analytical-based approach. Hence, the two simplifications made by the previous real-time methods can be avoided. The model was implemented on top of a flight simulator prototype system since the requirements of such system match the objectives of this study. Results were verified against the actual images of the daylight skies. Comparison was also made with the previous methods’ results to showcase the proposed model strengths and advantages over its peers
Full-depth Coadds of the WISE and First-year NEOWISE-Reactivation Images
The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE)
Reactivation mission released data from its first full year of observations in
2015. This data set includes ~2.5 million exposures in each of W1 and W2,
effectively doubling the amount of WISE imaging available at 3.4 and 4.6
microns relative to the AllWISE release. We have created the first ever
full-sky set of coadds combining all publicly available W1 and W2 exposures
from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We
employ an adaptation of the unWISE image coaddition framework (Lang 2014),
which preserves the native WISE angular resolution and is optimized for forced
photometry. By incorporating two additional scans of the entire sky, we not
only improve the W1/W2 depths, but also largely eliminate time-dependent
artifacts such as off-axis scattered moonlight. We anticipate that our new
coadds will have a broad range of applications, including target selection for
upcoming spectroscopic cosmology surveys, identification of distant/massive
galaxy clusters, and discovery of high-redshift quasars. In particular, our
full-depth AllWISE+NEOWISER coadds will be an important input for the Dark
Energy Spectroscopic Instrument (DESI) selection of luminous red galaxy and
quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam
Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction
pipelines. Much more work still remains in order to fully leverage NEOWISER
imaging for astrophysical applications beyond the solar system.Comment: coadds available at http://unwise.me, zoomable full-sky rendering at
http://legacysurvey.org/viewe
Optical Synoptic Telescopes: New Science Frontiers
Over the past decade, sky surveys such as the Sloan Digital Sky Survey have
proven the power of large data sets for answering fundamental astrophysical
questions. This observational progress, based on a synergy of advances in
telescope construction, detectors, and information technology, has had a
dramatic impact on nearly all fields of astronomy, and areas of fundamental
physics. The next-generation instruments, and the surveys that will be made
with them, will maintain this revolutionary progress. The hardware and
computational technical challenges and the exciting science opportunities are
attracting scientists and engineers from astronomy, optics, low-light-level
detectors, high-energy physics, statistics, and computer science. The history
of astronomy has taught us repeatedly that there are surprises whenever we view
the sky in a new way. This will be particularly true of discoveries emerging
from a new generation of sky surveys. Imaging data from large ground-based
active optics telescopes with sufficient etendue can address many scientific
missions simultaneously. These new investigations will rely on the statistical
precision obtainable with billions of objects. For the first time, the full sky
will be surveyed deep and fast, opening a new window on a universe of faint
moving and distant exploding objects as well as unraveling the mystery of dark
energy.Comment: 12 pages, 7 figure
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