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DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗

DOE OSTI2026

CodeScribe Agent

SF-26-086 CodeScribe introduces a structured, multi-stage pipeline that combines deterministic program analysis with LLM-powered translation to enable incremental, testable Fortran-to-C++ migration. First, `code-scribe index` traverses the project directory tree and produces `scribe.yaml` metadata files recording all modules, subroutines, and functions at each level, giving the LLM accurate structural context instead of a hallucinated codebase model. Second, `code-scribe draft` performs the deterministic portion of translation — converting Fortran types to C++ equivalents, replacing `use` statements with `#include` and `using namespace` directives, and detecting constructs requiring special handling — while embedding`scribe-prompt` annotations that guide the LLM through non-trivial cases such as statement-function-to-lambda conversions and `extern "C"` wrapper generation. Third, `code-scribe translate` applies project-specific TOML-based few-shot prompt templates and submits the composed prompt to a pluggable LLM backend (OpenAI, Anthropic, Argonne ARGO, any OpenAI-compatible endpoint, or local Hugging Face checkpoints), producing a C++ source file, a header, and a Fortran-C++ interface file for each translated routine so the codebase compiles and runs correctly throughout the migration. Beyond translation, CodeScribe includes a tool-using coding agent (`code-scribe agent`) with read, bash, edit, and write capabilities, and a bounded loop mode (`code-scribe loop`) that runs repeated stateless agent sessions over a task file with restricted tool access — enabling sustained, auditable software development workflows for broader scientific computing tasks.

Dhruv, Akash [Argonne National Laboratory (ANL), A↗

DOE OSTI2021

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Insights into ENSO Diversity from an Intermediate Coupled Model. Part II: Role of Nonlinear Dynamics and Stochastic Forcing

Abstract In this study, we investigate how a single leading linear El Niño–Southern Oscillation (ENSO) mode, as studied in Part I, leads to the irregular coexistence of central Pacific (CP) and eastern Pacific (EP) ENSO, a phenomenon known as ENSO spatiotemporal diversity. This diversity is fundamentally generated by deterministic nonlinear pathways to chaos via the period-doubling route and, more prevailingly, the subharmonic resonance route with the presence of a seasonally varying basic state. When residing in the weakly nonlinear regime, the coupled system sustains a weak periodic oscillation with a mixed CP/EP pattern as captured by the linear ENSO mode. With a stronger nonlinearity effect, the ENSO behavior experiences a period-doubling bifurcation. The single ENSO orbit splits into coexisting CP-like and EP-like ENSO orbits. A sequence of period-doubling bifurcation results in an aperiodic oscillation featuring irregular CP and EP ENSO occurrences. The overlapping of subharmonic resonances between ENSO and the seasonal cycle allows this ENSO irregularity and diversity to be more readily excited. In the strongly nonlinear regime, the coupled system is dominated by regular EP ENSO. The deterministic ENSO spatiotemporal diversity is thus confined to a relatively narrow range corresponding to a moderately unstable ENSO mode. Stochastic forcing broadens this range and allows ENSO diversity to occur when the ENSO mode is weakly subcritical. A close relationship among a weakened mean zonal temperature gradient, stronger ENSO activity, and more (fewer) occurrences of EP (CP) ENSO is noted, indicating that ENSO–mean state interaction may yield ENSO regime modulations on the multidecadal time scale.

Geng, Licheng↗

DOE OSTI2019

Stochastic Parameterization of Subgrid-Scale Velocity Enhancement of Sea Surface Fluxes

Abstract Subgrid-scale (SGS) velocity variations result in gridscale sea surface flux enhancements that must be parameterized in weather and climate models. Traditional parameterizations are deterministic in that they assign a unique value of the SGS velocity flux enhancement to any given configuration of the resolved state. In this study, we assess the statistics of SGS velocity flux enhancement over a range of averaging scales (as a proxy for varying model resolution) through systematic coarse-graining of a convection-permitting atmospheric model simulation over the Indian Ocean and west Pacific warm pool. Conditioning the statistics of the SGS velocity flux enhancement on 1) the fluxes associated with the resolved winds and 2) the precipitation rate, we find that the lack of a separation between “resolved” and “unresolved” scales results in a distribution of flux enhancements for each configuration of the resolved state. That is, the SGS velocity flux enhancement should be represented stochastically rather than deterministically. The spatial and temporal statistics of the SGS velocity flux enhancement are investigated by using basic descriptive statistics and through a fit to an anisotropic space–time covariance structure. Potential spatial inhomogeneities of the statistics of the SGS velocity flux enhancement are investigated through regional analysis, although because of the relatively short duration of the simulation (9 days) distinguishing true inhomogeneity from sampling variability is difficult. Perspectives for the implementation of such a stochastic parameterization in weather and climate models are discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Improving Solution Accuracy and Convergence for Stochastic Physics Parameterizations with Colored Noise

Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. In previous studies, it has been demonstrated that a correction term, known in stochastic analysis as the Itô correction, can help improve solution accuracy for various deterministic numerical schemes and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection–diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and, hence, helps to reduce the computational cost of the numerical simulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Characterization of temporal variations and feedback timescales of exhaust gas recirculation gas properties using high-speed diode laser absorption spectroscopy for next-cycle control of cyclic variability

Dilute combustion offers efficiency gains in boosted gasoline direct injection engines both through knock-limit extension and thermodynamic advantages (i.e. the effect of γ on cycle efficiency), but is limited by cyclic variability at high dilution levels. Past studies have shown that the cycle-to-cycle dynamics are a combination of deterministic and stochastic effects. The deterministic causes of cyclic variations, which arise from feedback due to exhaust gas recirculation, imply the possibility of using active control strategies for dilution limit extension. While internal exhaust gas recirculation will largely provide a next-cycle effect (short-timescale feedback), the feedback of external exhaust gas recirculation will have an effect after a delay of several cycles (long timescale). Therefore, control strategies aiming to improve engine stability at dilution limit may have to account for both short- and long-timescale feedback pathways. This study shows the results of a study examining the extent to which variations in exhaust gas recirculation composition are preserved along the exhaust gas recirculation flow path and thus the relative importance and information content of the long-timescale feedback pathway. To characterize the filtering or retention of cycle-resolved feedback information, high-speed (1–5 kHz) CO 2 concentration measurements were performed simultaneously at three different locations along the low-pressure external exhaust gas recirculation loop of a four-cylinder General Motors gasoline direct injection engine using a multiplexed two-color diode laser absorption spectroscopy sensor system during steady-state and transient engine operation at various exhaust gas recirculation levels. It was determined that cycle-resolved feedback propagates through internal residual gases but is filtered out by the low-pressure exhaust gas recirculation flow system and do not reach the intake manifold. Intermediate variations driven by flow rate and compositional changes are also distinguished and identified.

Dilute combustion↗

DOE OSTI2017

A stochastic electricity market clearing formulation with consistent pricing properties

We argue that deterministic market clearing formulations introduce arbitrary distortions between day-ahead and expected real-time prices that bias economic incentives. We extend and analyze a previously proposed stochastic clearing formulation in which the social surplus function induces penalties between day-ahead and real-time quantities. We prove that the formulation yields price bounded price distortions, and we show that adding a similar penalty term to transmission flows and phase angles ensures boundedness throughout the network. We prove that when the price distortions are zero, day-ahead quantities equal a quantile of their real-time counterparts. The undesired effects of price distortions suggest that stochastic settings provide significant benefits over deterministic ones that go beyond social surplus improvements. Finally, we propose additional metrics to evaluate these benefits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Land productivity and land availability for growing bioenergy crop in the Contiguous US. Center for Advanced Bioenergy and Bioproducts Innovation (CABBI)

The dataset consists of two types of data: the estimate of land productivity (the maximum productivity, MP) and the estimate of land that has low productivity for any major crops planted in the Contiguous United States and then may be available for growing bioenergy crops (the marginal land, ML). All data items are in GeoTiff format, under the World Geodetic System (WGS) 84 project, and with a resolution of 0.0020810045 degree (~250 m). The MP values are calculated based on machine learning model estimated yields of major crops in the CONUS, and its expected value (MP_mean.tif), and associated uncertainty (MP_IDP.tif). The ML availability data have two versions: a deterministic version and a version with uncertainty. The deterministic MLs are determined as the land pixels with expected MP values falling in the range defined in the following criteria, and the MLs with uncertainty are determined as the probability that the MP value of a land pixel falls in the range defined in the following criteria: Criteria_____Description S1________ Current crop and pasture land with MP <= P50 S2________ Current crop and pasture land with MP <= P25 S3________ S1 + current grass and shrub land with P25 < MP < P50 S4________ S2 + current grass and shrub land with P10 < MP < P25 Economic__ Current crop and pasture land with potential profitability < 0 Here P10, P25 and P50 are the 10th, 25th and 50th percentile of crop MP values

Land productivity↗

DOE OSTI2012

Cross-section uncertainty propagation in the multigroup slowing-down equations using probability table formalism

In the frame of neutral-particle (neutron, gamma) transport, the uncertainty propagation calculation regarding the uncertainties on cross sections is often carried out without explicitly taking into account their probabilistic distribution. We investigate a new uncertainty propagation formalism where the cross-section uncertainty distributions are represented by probability tables. This technical note develops this approach for the steady-state slowing-down equation without up-scattering and in an infinite medium. This work is based on a deterministic multiband formalism that takes into account multilevel probability tables for cross sections. The first level represents the variation of cross sections versus lethargy (or energy) in each group of the multigroup lethargy mesh and thus corresponds to the classical cross-section probability tables. The higher levels represent the uncertainties on each step of the first-level cross-section probability table. This method is validated against a Monte Carlo calculation in a case of neutron slowing down in a {sup 238}U-hydrogen homogeneous mixture, showing fully consistent numerical results. The main interest of the deterministic multilevel multiband formalism is that it gives not only the mean value and the variance but also a probabilistic distribution of the fluxes. In the near future, we plan to investigate more deeply the robustness of this new approach in relation to high values of cross-section uncertainties and to introduce cross-section uncertainty correlations as well. Meanwhile, the promise of this work is its extension to the general transport steady-state equation solved by the discrete ordinates (S(N)) or Monte Carlo methods. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2011

Femtosecond pulse damage thresholds of dielectric coatings in vacuum

At 10-7 Torr, the multiple femtosecond pulse damage threshold, F(?), is about 10% of the single pulse damage fluence F(1) for hafnia and silica films compared to about 65% and 50%, respectively, at 630 Torr. In contrast, the single-pulse damage threshold is pressure independent. The decrease of F(?) with decreasing air pressure correlates with the water vapor and oxygen content of the ambient gas with the former having the greater effect. The decrease in F(?) is likely associated with an accumulation of defects derived from oxygen deficiency, for example vacancies. From atmospheric air pressure to pressures of {approx}3 x 10{sup -6} Torr, the damage 'crater' starts deterministically at the center of the beam and grows in diameter as the fluence increases. At pressure below 3x10-6 Torr, damage is initiated at random 'sites' within the exposed area in hafnia films, while the damage morphology remains deterministic in silica films. A possible explanation is that absorbing centers are created at predisposed sample sites in hafnia, for example at boundaries between crystallites, or crystalline and amorphous phases.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Random adaptive tool path for zonal optics fabrication

Deterministic optics fabrication using sub-aperture tools has been vital for manufacturing precision optical surfaces. The fabrication process requires the tool influence function and the tool path to calculate the dwell time that guides the tool to bring surface quality within tight design tolerances. Widely used spiral and raster paths may leave excess waviness from the tool path, and the unavoidable constant removal layer is added to obtain positive dwell time. This waviness can be removed by either using smaller tools sequentially or randomizing the tool path. However, the existing tool-path solutions can hardly adapt to different surface aperture shapes and localized surface errors. Process efficiency and accuracy are also not well considered in tool-path planning. We propose an innovative zonal Random Adaptive Path (RAP) to solve these problems in this study. Firstly, RAP can be flexibly adapted to different surface aperture shapes by introducing part boundary. Secondly, an average threshold strategy is used in the RAP planning to improve efficiency, enabling the surface errors to be selectively corrected. Finally, the threshold is performed in several passes within one processing cycle, each with its RAP, until the desired residual is achieved. The performance of the proposed RAP is studied by comparing it with the conventional tool paths. The results demonstrated that RAP takes the least processing time and achieves the best surface quality, which verifies the effectiveness of RAP in deterministic optics fabrication.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Tularosa Basin Play Fairway Analysis Data and Models

This submission includes raster datasets for each layer of evidence used for weights of evidence analysis as well as the deterministic play fairway analysis (PFA). Data representative of heat, permeability and groundwater comprises some of the raster datasets. Additionally, the final deterministic PFA model is provided along with a certainty model. All of these datasets are best used with an ArcGIS software package, specifically Spatial Data Modeler.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

ENSEMBLE KALMAN FILTERS FOR RELIABILITY ESTIMATION IN PERFUSION INFERENCE

We consider the solution of inverse problems in dynamic contrast–enhanced imaging by means of ensemble Kalman filters. Our quantity of interest is blood perfusion, i.e., blood flow rates in tissue. While existing approaches to compute blood perfusion parameters for given time series of radiological measurements mainly rely on deterministic, deconvolution–based methods, we aim at recovering probabilistic solution information for given noisy measurements. To this end, we model radiological image capturing as a sequential data assimilation process and solve it by an ensemble Kalman filter. Thereby, we recover deterministic results as an ensemble–based mean and are able to compute reliability information such as probabilities for the perfusion to be in a given range. Our target application is the inference of blood perfusion parameters in the human brain. A numerical study shows promising results for artificial measurements generated by a digital perfusion phantom.

Engineering↗

DOE OSTI2025

APOLLO: a facility-scale differentiable virtual accelerator at Fermilab FAST/IOTA

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or yield additional insights like gradients. The FAST/IOTA facility has been working on implementing and experimentally validating an end-to-end digital twin that is both fast and gradient-aware, allowing for rapid prototyping of new software and experiments with minimal beam time costs. Our framework integrates physics and ML codes for linac and ring simulation through a set of generic interfaces between surrogate and physics-based sections. To reproduce device inputs and outputs, system state is exposed as a deterministic event loop in a specialized discrete event simulator architecture. Because Fermilab is undergoing control system transition, several APIs were implemented as final user interfaces - a fully asynchronous EPICS soft IOC, a gRPC-based Data Pool Manager (DPM), and legacy ACNET protocols. We discuss implementation details as well as challenges handling live data assimilation and future plans to extend modelling to main complex proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

DOE OSTI1993

Nuclear Safety [Vol. 34, No. 1, January-March 1993]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 An Integrated Regional Approach To Risk Management of Industrial Systems, S. Chakraborty and R. Stratton; 9 Annual Technical Meeting of the NRC Cooperative Severe Accident Research Program, E. G. Silver; ACCIDENT ANALYSIS: 13 Deterministic Severe Accident Criteria as Severe Accident Design Criteria and Policy for the New Production Reactor-Heavy Water Reactor, P. T. Rhoads; 20 Proposed Deterministic Severe Accident Criteria for the Heavy Water Reactor-New Production Reactor Containment, K. D. Bergeron, S. E. Slezak, and C. E. Leach; 33 Quasi-Static Core Liquid Level Depression and Long-Term Core Uncovery During a PWR LOCA, Y. Kukita, R. R. Schultz, H. Nakamura, and J. Katayama; 49 LIRA: An Advanced Containment System to Minimize the Accidental Radioactivity Releases, A. Turricchia; 63 Errata to “A Review of Hydrogen Production During Melt/Water Interaction in LWRs,” Vol. 33, No. 4; CONTROL AND INSTRUMENTATION: 64 The Nuplex 80+™ Advanced Control Complex from ABB Combustion Engineering, F. Ridolfo, D. Harmon, and K. Scarola; DESIGN FEATURES: 76 A Scheme for Passive Isolation of the Containment of a Reactor, A. K. Ghosh, V. V. Raj, and K. Kakodkar; 84 Utility Requirements for Safety in the Passive Advanced Light-Water Reactor, T. U. Marston, W. H. Layman, and G. Bockhold, Jr.; WASTE AND SPENT FUEL MANAGEMENT: 91 Activities Related to Waste and Spent Fuel Management, Compiled by M. D. Muhlheim and E. G. Silver; OPERATING EXPERIENCES: 103 Testing Deficiencies in Auxiliary Systems Feedwater Systems, J. D. Kueck; 110 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 113 Selected Safety-Related Events, Compiled by G. A. Murphy; 115 Operating U.S. Power Reactors, Compiled by M. D. Muhlheim and E. G. Silver; RECENT DEVELOPMENTS: 133 General Administrative Activities, Compiled by M. D. Muhlheim and E. G. Silver; 145 Reports, Standards, and Safety Guides, D. S. Queener; 150 Proposed Rule Changes as of Sept. 30, 1992; ANNOUNCEMENTS: 75 Harvard Short Course on Risk: Science, Assessment, and Management; 102 International Conference on Reactor Physics and Reactor Computations; 102 The Fourth International Conference on Nuclear Waste Reprocessing and Waste Management [RECOD ’94]; 132 International Symposium on the Radiological Exposure of the Population of the European Community from Radioactivity in the Mediterranean Sea [MARINA-MED]; 162 International High-Level Radioactive Waste Conference ‘Technology Integration—Above and Below”; 154 The Authors; 158 Indexes to Nuclear Safety, Volume 33.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

SAE2.py : a python script to automate parameter studies using SCREAMER with application to magnetic switching on Z.

The SCREAMER simulation code is widely used at Sandia National Laboratories for designing and simulating pulsed power accelerator experiments on super power accelerators. A preliminary parameter study of Z with a magnetic switching retrofit illustrates the utility of the automating script for optimizing pulsed power designs. SCREAMER is a circuit based code commonly used in pulsed-power design and requires numerous iterations to find optimal configurations. System optimization using simulations like SCREAMER is by nature inefficient and incomplete when done manually. This is especially the case when the system has many interactive elements whose emergent effects may be unforeseeable and complicated. For increased completeness, efficiency and robustness, investigators should probe a suitably confined parameter space using deterministic, genetic, cultural, ant-colony algorithms or other computational intelligence methods. I have developed SAE2 - a user-friendly, deterministic script that automates the search for optima of pulsed-power designs with SCREAMER. This manual demonstrates how to make input decks for SAE2 and optimize any pulsed-power design that can be modeled using SCREAMER. Application of SAE2 to magnetic switching on model of a potential Z refurbishment illustrates the power of SAE2. With respect to the manual optimization, the automated optimization resulted in 5% greater peak current (10% greater energy) and a 25% increase in safety factor for the most highly stressed element.

43 PARTICLE ACCELERATORS↗

DOE OSTI2011

Development and testing of improved statistical wind power forecasting methods.

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

17 WIND ENERGY↗