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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.

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DOE OSTI2018

Enabling reliability assessments of pre-commercial perovskite photovoltaics with lessons learned from industrial standards [Enabling reliability of pre-commercial perovskite photovoltaics with lessons learned from industrial standards]

Here, photovoltaic modules are expected to operate in the field for more than 25 years, so reliability assessment is critical for the commercialization of new photovoltaic technologies. In early development stages, understanding and addressing the device degradation mechanisms are the priorities. However, any technology targeting large-scale deployment must eventually pass industry-standard qualification tests and undergo reliability testing to validate the module lifetime. In this Perspective, we review the methodologies used to assess the reliability of established photovoltaics technologies and to develop standardized qualification tests. We present the stress factors and stress levels for degradation mechanisms currently identified in pre-commercial perovskite devices, along with engineering concepts for mitigation of those degradation modes. Recommendations for complete and transparent reporting of stability tests are given, to facilitate future inter-laboratory comparisons and to further the understanding of field-relevant degradation mechanisms, which will benefit the development of accelerated stress tests.

14 SOLAR ENERGY↗

DOE OSTI2016

A Literature Review: Smart Grids Impacts on Nuclear Power Plants Task 4: Project Final Report

This report describes the results of a literature review performed to study the current state of electric power industry efforts and research work regarding Smart Grid technologies, renewable energy integration, grid reliability standards, and USNRC electric grid regulations and guidance. The information gathered in the literature review is intended to: (1) Develop a better understanding of the impacts that Smart Grid implementation and the integration of renewable energy sources can have on the availability and reliability of the electric grid as a source of offsite power, (2) Provide an understand of the present grid reliability standards and how they will address the challenges of Smart Grid implementation, (3) Identify electrical system vulnerabilities and failure modes that may result from the implementation of Smart Grid technologies and cybersecurity threats, (4) Provide an understand of the actions being taken by FERC, NERC and others to identify, understand and address potential impacts, (5) Provide an understand of existing NRC regulation and guidance addressing requirements of grid design, operation and reliability supporting NPP design requirements, and (6) Recommend any additional actions or studies that should be undertaken by the NRC to ensure compliance of NPPs to GDC 17 and any other applicable regulations and guidance as the electric grid evolves into the Smart Grid.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Reliability metrics and their management implications for open pond algae cultivation

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-to-calculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.

09 BIOMASS FUELS↗

DOE OSTI2016

Chapter 9: Reliability

This chapter describes the accumulated knowledge on CPV reliability with its fundamentals and qualification. It explains the reliability of solar cells, modules (including optics) and plants. The chapter discusses the statistical distributions, namely exponential, normal and Weibull. The reliability of solar cells includes: namely the issues in accelerated aging tests in CPV solar cells, types of failure and failures in real time operation. The chapter explores the accelerated life tests, namely qualitative life tests (mainly HALT) and quantitative accelerated life tests (QALT). It examines other well proven and experienced PV cells and/or semiconductor devices, which share similar semiconductor materials, manufacturing techniques or operating conditions, namely, III-V space solar cells and light emitting diodes (LEDs). It addresses each of the identified reliability issues and presents the current state of the art knowledge for their testing and evaluation. Finally, the chapter summarizes the CPV qualification and reliability standards.

14 SOLAR ENERGY↗

DOE OSTI2022

Quantum-Inspired Power System Reliability Assessment

To enable an in-depth study of power system operation and planning, the assessment of standard reliability indices is inevitable. The Monte Carlo Simulation (MCS) approach is a broadly used method in replacing the analytical methods in reliability indices assessment. The accuracy of MCS, however, highly depends on the sampling size, and hence, a complicated system with large number of components requires a large sampling size and daunting computational effort. To address this shortcoming, we, in this paper attempt to take advantage of potentials of the quantum computing (QC) for power system reliability assessment by realizing the following contributions: 1) an innovative quantum model designed for reliability assessment; 2) a quantum circuit that achieves the quadratic speed up compared to the classical MCS method; 3) an efficient quantum amplitude estimation (QAE) algorithm to accurately evaluate the reliability indices. The accuracy and efficacy of the quantum reliability method are extensively verified and demonstrated on both radial and mesh distribution systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Load Composition Analysis in Support of the NERC Load Modeling Task Force. 2019-2020 Field Test of the Composite Load Model

In 2015, NERC’s reliability standards were revised to require the use of dynamic load models in transmission planning studies. To comply with the standards, planners must use load models that explicitly represent the dynamic behavior of the different constituents of load at each load bus within their transmission planning models. The most important of these constituents are motor-driven and power electronics-based loads. Collectively, these representations are known as composite load models. In anticipation of the compliance date for the new standards, NERC’s Load Modeling Task Force (LMTF), in 2019, initiated a field test of composite load models involving the regional reliability planning entities. In support of the field test, DOE and BPA researchers developed region-specific composite load models that could be assigned to each non-industrial load bus in the planning models for each of the North American interconnections. Separate models were developed for each hour of a summer peak day, a winter peak day, and a spring light-load day. This report is the technical documentation for the load composition analysis that was conducted to develop these non-industrial composite load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Evaluation of Smart Grid Technologies Employed for System Reliability Improvement: Pacific Northwest Smart Grid Demonstration Experience

The Pacific Northwest Smart Grid Demonstration (PNWSGD) was a smart grid technology performance evaluation project that included multiple U.S. states and cooperation from multiple electric utilities in the northwest region. One of the local objectives for the project was to achieve improved distribution system reliability. Toward this end, some PNWSGD utilities automated their distribution systems, including the application of fault detection, isolation, and restoration and advanced metering infrastructure. In light of this investment, a major challenge was to establish a correlation between implementation of these smart grid technologies and actual improvements of distribution system reliability. This paper proposes using Welch’s t-test to objectively determine and quantify whether distribution system reliability is improving over time. The proposed methodology is generic, and it can be implemented by any utility after calculation of the standard reliability indices. The effectiveness of the proposed hypothesis testing approach is demonstrated through comprehensive practical results. It is believed that wider adoption of the proposed approach can help utilities to evaluate a realistic long-term performance of smart grid technologies.

Agalgaonkar, Yashodhan P. (ORCID:0000000290061848)↗

DOE OSTI2017

Microprobe Analysis of Pu-Ga Standards

In order to obtain quantitative analysis using an Electron Scanning Microprobe it is essential to have a standard of known composition. Most elemental and multi-elemental standards can be easily obtained from places like Elemental Scientific or other standards organizations that are NIST (National Institute of Standards and Technology) traceable. It is, however, more challenging to find standards for plutonium. Past work performed in our group has typically involved using the plutonium sample to be analysed as its own standard as long as all other known components of the sample have standards to be compared to [1,2,3]. Finally, this method works well enough, but this experiment was performed in order to develop a more reliable standard for plutonium using five samples of known chemistry of a plutonium gallium mix that could then be used as the main plutonium and gallium standards for future experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Regulatory Implications of Embedded Grid Energy Storage

Electricity is unique among commodities in that its supply chain was developed without a storage component. Every other resource commodity has the ability to store excess quantities built into its supply chain – in the form of granaries, warehouses, reservoirs, etc. This embedded storage creates a buffer for mismatches between supply and demand, stabilizing prices and protecting customers. Recent technological advances in cost-competitive energy storage technologies that are scalable and flexible have made the concept of embedded electrical storage feasible, but several regulatory questions remain. This paper summarizes energy regulatory structures in the U.S. and the implications that they would have for embedded storage on the electric grid. Regulatory challenges for embedded storage include the lack of underlying standards, inclusion in planning processes, ownership models, compensation, and metrics. Two possible pathways forward are explored: an incremental one including regulatory guidance regarding the evaluation of embedded storage in existing planning processes, and a complex one involving the revision of existing reliability standards or the development of a new standard specific to embedded storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Efficient Reliability Analysis using Generalized Multifidelity Modeling and Explainable Active Learning

To assess the reliability of critical technologies like nuclear plants and infrastructure systems and improve the robustness of design, engineers have to quantify the uncertainties surrounding the system behavior accurately. However, the complexity of the problem can make standard reliability analysis algorithms prohibitively expensive, primarily due to the high computational cost of estimating the system response at each iteration. This cost can be greatly reduced by using multi-fidelity modeling and machine learning to build a surrogate model to replace the expensive response function. We propose a general and robust method for building surrogates from multiple Low Fidelity (LF) models coupled with machine learning to retain accuracy. Our framework first constructs “Corrected Low Fidelity models” (CLFs) by coupling a High Fidelity (HF) model inferred Gaussian Process correction term with each of the LF models. It then uses the correction terms to assign model probabilities to each of these CLFs in an explainable way before using them to assemble the final surrogate. No assumptions are made about the type of the LF models or their correlation with the HF model. The proposed surrogate modeling framework is used within the subset simulation algorithm (a variance-reduced MCMC-based reliability analysis algorithm) for enhanced efficiency. Additionally, an active learning step is added to the algorithm to adaptively decide when the surrogate is not sufficiently accurate, at which point the HF model is called and used to refine the surrogate. Through a frame buckling example, our method is shown to be highly efficient at reducing the expensive HF model calls while accurately estimating the failure probability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Revenue Sufficiency and Reliability in a Zero Marginal Cost Future: Preprint

Features of existing wholesale electricity markets, such as administrative pricing rules and policy-based reliability standards, can distort market incentives from allowing generators sufficient opportunities to recover both fixed and variable costs. Moreover, these challenges can be amplified by other factors, including (1) inelastic demand resulting from a lack of price signal clarity, (2) low- or near-zero marginal cost generation, particularly arising from low natural gas fuel prices and variable generation (VG), such as wind and solar, and (3) the variability and uncertainty of this VG. As power systems begin to incorporate higher shares of VG, many questions arise about the suitability of the existing marginal-cost-based price formation, primarily within an energy-only market structure, to ensure the economic viability of resources that might be needed to provide system reliability. This article discusses these questions and provides a summary of completed and ongoing modelling-based work at the National Renewable Energy Laboratory to better understand the impacts of evolving power systems on reliability and revenue sufficiency.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Revenue Sufficiency and Reliability in a Zero Marginal Cost Future

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Operationalizing Synchrophasors for Enhanced Grid Reliability and Asset Utilization

The report discusses the development of production-grade synchrophasor software applications. The objective is to improve system reliability and asset utilization for offline as well as real-time considerations, as per the Department of Energy (DOE) guidelines specified by Funding Opportunity Announcement (FOA) DE-FOA-0001492. On the one hand, we have developed grid management applications on how to transform synchrophasor-based monitoring into operator guidance, and commercial grade tools addressing industry needs such as NERC Reliability Standards (MOD 26, MOD 27 and MOD 33). On the other hand, with the wide industrial adoption in mind, the developed applications have been fully discussed with utility partners and installed in the utility partners site including 6 field tests. The Model Validation and Calibration software module has been integrated into GE’s PhasorAnalyticsTM. The first commercial contract has been signed even before the close date of this project. The Angle-based Grid Management (AGM), Fast Voltage Security Assessment (FastVSA), Enhanced Islanding Monitoring(EIM) and Enhanced Disturbance Management (EDM) have been integrated into GE’s Grid Stability Assessment line of applications in e-terra Suite of EMS product.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Clusters of Monoisotopic Elements for Calibration in (TOF) Mass Spectrometry

Precise calibration in TOF MS requires suitable and reliable standards, which are not always available for high masses. We evaluated inorganic clusters of the monoisotopic elements gold and phosphorus (Au{sub n}{sup +}/Au{sub n}{sup -} and P{sub n}{sup +}/P{sub n}{sup -}) as an alternative to peptides or proteins for the external and internal calibration of mass spectra in various experimental and instrumental scenarios. Monoisotopic gold or phosphorus clusters can be easily generated in situ from suitable precursors by laser desorption/ionization (LDI) or matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Their use offers numerous advantages, including simplicity of preparation, biological inertness, and exact mass determination even at lower mass resolution. We used citrate-stabilized gold nanoparticles to generate gold calibration clusters, and red phosphorus powder to generate phosphorus clusters. Both elements can be added to samples to perform internal calibration up to mass-to-charge (m/z) 10–15,000 without significantly interfering with the analyte. We demonstrated the use of the gold and phosphorous clusters in the MS analysis of complex biological samples, including microbial standards and total extracts of mouse embryonic fibroblasts. We believe that clusters of monoisotopic elements could be used as generally applicable calibrants for complex biological samples. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Palladium at high pressure and high temperature: A combined experimental and theoretical study

Palladium is one of the most important technological materials, yet its phase diagram remains poorly understood. At ambient conditions, its solid phase is face-centered cubic (fcc). However, another solid phase of Pd, body-centered cubic (bcc), was very recently predicted in two independent theoretical studies to occur at high pressures and temperatures. In this work, we report an experimental study on the room-temperature equation of state (EOS) of Pd to a pressure of 80 GPa, as well as a theoretical study on the phase diagram of Pd including both fcc-Pd and bcc-Pd. Our theoretical approach consists in ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid–solid phase transition boundaries. We obtain the melting curves of both fcc-Pd and bcc-Pd and an equation for the fcc–bcc solid–solid phase transition boundary as well as the thermal EOS of Pd which is in agreement with experimental data and QMD simulations. We uncover the presence of another solid phase of Pd on its phase diagram, namely, random hexagonal close-packed (rhcp), and estimate the location of the rhcp-bcc solid–solid phase transition boundary and the rhcp–fcc–bcc triple point. We also discuss the topological similarity of the phase diagrams of palladium and silver, the neighbor of Pd in the periodic table. We argue that Pd is a reliable standard for shock-compression studies and present the analytic model of its principal Hugoniot in a wide pressure range.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Operating Dynamic Reserve Dimensioning Using Probabilistic Forecasts

The rapid integration of variable energy sources (VRES) into power grids increases variability and uncertainty of the net demand, making the power system operation challenging. Operating reserve is used by system operators to manage and hedge against such variability and uncertainty. Traditionally, reserve requirements are determined by rules-of-thumb (static reserve requirements, e.g., NERC Reliability Standards), and more recently, dynamic reserve requirements from tools and methods which are in the adoption process (e.g., DynADOR, DRD, and RESERVE, among others). While these methods/tools significantly improve the static rule-of-thumb approaches, they rely exclusively on deterministic data (i.e., best guess only). Consequently, these methods disregard the probabilistic uncertainty thresholds associated with specific days and their weather conditions (i.e., best guess plus probabilistic uncertainty). This work presents practical approaches to determine the operating reserve requirements leveraging the wealth information from probabilistic forecasts. Proposed approaches are validated and tested using actual data from the CAISO system. Furthermore, results show the benefits in terms of risk reduction of considering the probabilistic forecast information into the dimensioning process of operating reserve requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Resilient off-grid microgrids: Capacity planning and N-1 security

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include N-1 security and other practical modeling features like AC power flow physics, component efficiencies and thermal limits. Lastly, we demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.

24 POWER TRANSMISSION AND DISTRIBUTION↗