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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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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probabilistic Assessment of High-Renewables Power Systems: Current Work and Future Directions

In a future with higher penetrations of variable and energy-limited resources, the dominant sources of resource adequacy risk begin to shift from (assumed) independent thermal unit outages to spatially- and temporally-correlated weather-driven phenomena. Traditional resource adequacy assessment and planning methods can be ill-suited to such scenarios. This presentation will highlight aspects of NREL's work in adapting and developing new probabilistic methods and tools in anticipation of the needs of the power system planning exercises of tomorrow.

17 WIND ENERGY↗
DOE OSTI2016

Assessment of high enthalpy geothermal resources and promising areas of Chile

This work aims to assess geothermal power potential in identified high enthalpy geothermal areas in the Chilean Andes, based on reservoir temperature and volume. In addition, we present a set of highly favorable geothermal areas, but without enough data in order to quantify the resource. Information regarding geothermal systems was gathered and ranked to assess Indicated or Inferred resources, depending on the degree of confidence that a resource may exist as indicated by the geoscientific information available to review. Resources were estimated through the USGS Heat in Place method. A Monte Carlo approach is used to quantify variability in boundary conditions. Estimates of total Indicated resource are confined to 3 geothermal systems; Apacheta, El Tatio and Tolhuaca, yielding a total value of 228 ± 154. MWe. The estimates of the total Inferred resources for Chile include 6 geothermal systems and yield a total value of 431 ± 321. MWe. Standard deviation reflects the high variability of reservoir specific parameters for each system. A set of 65 favorable geothermal areas are proposed as the most likely future development targets. Finally, eight of them have initial exploration results that suggest they are highly favorable targets as potential geothermal resources.

58 GEOSCIENCES↗
DOE OSTI2014

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application’s throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based look-ahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from public and private IaaS clouds. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Commercial and Industrial Base Intermittent Resource Management Pilot

This scoping study summarizes the challenges with integrating wind and solar generation into the California's electricity grid. These challenges include: Smoothing intra-hour variability; - Absorbing excess renewable energy during over-generation periods; - Addressing morning and evening ramping periods. In addition, there are technical challenges to integrating retail demand response (DR) triggered by the wholesale conditions into the CAISO markets. The study describes the DR programs available to the consumers through the utilities in California and CAISO's ancillary services market because an integration of the wholesale and retail DR requires an understanding of these different offerings and the costs associated with acquiring them. Demand-side active and passive storage systems are proposed as technologies that may be used to mitigate the effects of intermittence due to renewable generation. Commercial building technologies as well as industrial facilities with storage capability are identified as targets for the field tests. Two systems used for ancillary services communications are identified as providing the triggers for DR enablement. Through the field tests, issues related to communication, automation and flexibility of demand-side resources will be explored and the performance of technologies that participate in the field tests will be evaluated. The major outcome of this research is identifying and defining flexibility of DR resources and optimized use of these resources to respond to grid conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Long-Term Resource Adequacy, Long-Term Flexibility Requirements, and Revenue Sufficiency

Variable generation (VG) can reduce market prices over time and also the energy that other suppliers can sell in the market. The suppliers that are needed to provide capacity and flexibility to meet the long-term reliability requirements may, therefore, earn less revenue. This chapter discusses the topics of resource adequacy and revenue sufficiency - that is, determining and acquiring the quantity of capacity that will be needed at some future date and ensuring that those suppliers that offer the capacity receive sufficient revenue to recover their costs. The focus is on the investment time horizon and the installation of sufficient generation capability. First, the chapter discusses resource adequacy, including newer methods of determining adequacy metrics. The chapter then focuses on revenue sufficiency and how suppliers have sufficient opportunity to recover their total costs. The chapter closes with a description of the mechanisms traditionally adopted by electricity markets to mitigate the issues of resource adequacy and revenue sufficiency and discusses the most recent market design changes to address these issues.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Drivers of the Resource Adequacy Contribution of Solar and Storage for Florida Municipal Utilities

Solar’s variable generation limits its contribution to reliably meeting peak demand, or its resource adequacy contribution. Energy storage is a leading option to increase solar’s resource adequacy contribution, yet the contribution from different configurations of solar and storage is not widely understood. We develop methods for exploring the primary drivers of an estimate of the resource adequacy contribution of solar and storage, and we apply the methods to a case study in Florida, where demand peaks in winter and summer. We find that the portion of solar nameplate capacity that contributes to resource adequacy—its capacity credit—is less than 50% and that it declines with increasing solar penetration. The capacity credit of storage, even though it is fully controllable by the system operator, strongly depends on the duration of storage. The capacity credit of 1 hour of storage can be less than the capacity credit of solar. Achieving a 90% capacity credit requires at least 4–5 hours of storage when storage capacity is small relative to the system peak. As storage deployment increases to 20% of the peak demand, 9 hours—and sometimes more than 10 hours—of storage are needed to achieve a 90% capacity credit. Increased solar deployment at the system level can increase storage’s capacity credit. Directly pairing solar and storage can also impact the capacity credit. Storage with a power rating similar to the solar inverter rating loses capacity credit when coupled with solar if its duration is more than 1–2 hours, because storage competes with solar for use of the inverter. On the other hand, there is no reduction in capacity credit when the storage is small relative to the solar inverter. The approach and tools developed here for exploratory analysis can be useful for many other utilities and regions grappling with similar preliminary questions, prior to evaluation of specific cases using more detailed and resource-intensive modeling.

14 SOLAR ENERGY↗
DOE OSTI2017

Evaluation of the FIR Example using Xilinx Vivado High-Level Synthesis Compiler

Compared to central processing units (CPUs) and graphics processing units (GPUs), field programmable gate arrays (FPGAs) have major advantages in reconfigurability and performance achieved per watt. This development flow has been augmented with high-level synthesis (HLS) flow that can convert programs written in a high-level programming language to Hardware Description Language (HDL). Using high-level programming languages such as C, C++, and OpenCL for FPGA-based development could allow software developers, who have little FPGA knowledge, to take advantage of the FPGA-based application acceleration. This improves developer productivity and makes the FPGA-based acceleration accessible to hardware and software developers. Xilinx Vivado HLS compiler is a high-level synthesis tool that enables C, C++ and System C specification to be directly targeted into Xilinx FPGAs without the need to create RTL manually. The white paper [1] published recently by Xilinx uses a finite impulse response (FIR) example to demonstrate the variable-precision features in the Vivado HLS compiler and the resource and power benefits of converting floating point to fixed point for a design. To get a better understanding of variable-precision features in terms of resource usage and performance, this report presents the experimental results of evaluating the FIR example using Vivado HLS 2017.1 and a Kintex Ultrascale FPGA. In addition, we evaluated the half-precision floating-point data type against the double-precision and single-precision data type and present the detailed results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Statistical Characterization of Solar Photovoltaic Power Variability at Small Timescales: Preprint

Integrating large amounts of variable and uncertain solar photovoltaic power into the electricity grid is a growing concern for power system operators in a number of different regions. Power system operators typically accommodate variability, whether from load, wind, or solar, by carrying reserves that can quickly change their output to match the changes in the solar resource. At timescales in the seconds-to-minutes range, this is known as regulation reserve. Previous studies have shown that increasing the geographic diversity of solar resources can reduce the short term-variability of the power output. As the price of solar has decreased, the emergence of very large PV plants (greater than 10 MW) has become more common. These plants present an interesting case because they are large enough to exhibit some spatial smoothing by themselves. This work examines the variability of solar PV output among different arrays in a large ({approx}50 MW) PV plant in the western United States, including the correlation in power output changes between different arrays, as well as the aggregated plant output, at timescales ranging from one second to five minutes.

14 SOLAR ENERGY↗
DOE OSTI2012

Statistical Characterization of Solar Photovoltaic Power Variability at Small Timescales: Preprint

Integrating large amounts of variable and uncertain solar photovoltaic power into the electricity grid is a growing concern for power system operators in a number of different regions. Power system operators typically accommodate variability, whether from load, wind, or solar, by carrying reserves that can quickly change their output to match the changes in the solar resource. At timescales inthe seconds-to-minutes range, this is known as regulation reserve. Previous studies have shown that increasing the geographic diversity of solar resources can reduce the short term-variability of the power output. As the price of solar has decreased, the emergence of very large PV plants (greater than 10 MW) has become more common. These plants present an interesting case because they are largeenough to exhibit some spatial smoothing by themselves. This work examines the variability of solar PV output among different arrays in a large (50 MW) PV plant in the western United States, including the correlation in power output changes between different arrays, as well as the aggregated plant output, at timescales ranging from one second to five minutes.

14 SOLAR ENERGY↗
DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.

14 SOLAR ENERGY↗
DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.

14 SOLAR ENERGY↗
DOE OSTI2021

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Oil and gas produced water as a growth medium for microalgae cultivation: A review and feasibility analysis

Scale-up of microalgal biotechnology to provide large quantities of biofuel, lipids, and coproducts is not fully developed because of the large needs for nutrients, water, land, solar insolation, and CO 2 /carbon supplies. Wastewaters, including oil and gas produced water (PW), may supply a portion of these needs in regions with insufficient fresh water resources. PW is a challenging water resource for this use because of variable salinity, geochemical complexity, and the presence of biologically toxic components. In this paper we review PW volumes, quality, and use in media for microalgae production in the southwestern US, Australia, and Oman. We also include data from the southwestern US, referencing previously unpublished results from the National Alliance for Biofuels and Bioproducts (NAABB) consortium research project. We include a Supplementary Information section that explores cultivation of multiple microalgae species in PW and examines the carbon utilization process, all work performed in support of the NAABB field program. Strains of algae tested in the reviewed papers include Nannochloropsis , Dunalliella , Scenedesmus , and several mixed or unknown cultures. We conclude that the use of PW in algae cultivation is feasible, if the additional complexity of the water resource is accounted for in developing media formulations and in understanding metals uptake by the algae. We recommend additional work to standardize growth testing in PW, better and more thorough chemical analysis, and geochemical modeling of the PW used in media. As a result, expanded strain testing in PW media will identify improved strains tolerant of PW in algae cultivation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Enabling Power System Transformation Globally: A System Operator Research Agenda for Bulk Power System Issues

The primary objective of a power system is to safely provide reliable energy services to society at an affordable cost. In many countries, this objective has been supplemented by another: meeting the energy demand with sustainable resources, which has culminated in the energy transition to low-carbon and zero-carbon energy systems. This transition, occurring rapidly around the world, is characterized by the increasing penetration of variable renewable energy (VRE), inverter-based resources (IBRs), and distributed energy resources (DERs).

costs↗
DOE OSTI2024

Identifying Hydropower Operational Flexibilities in Presence of Streamflow and Net-load Uncertainty (Final Technical report)

In the existing operations, hydropower contributions to future system flexibility are generally modeled while maintaining traditional operating rules and constraints in supporting grid operation, such as the balancing of variable renewable energy production. Moreover, operation of large scale hydropower systems on major rivers has been investigated for decades, utilizing various systems engineering approaches, with the evolving electric grid, as the result of renewable resources integration, compounded by the changing climate (variability of river flows, intensification of hydrologic cycle resulting in more frequent extreme events) affecting water availability, the need for more advanced stochastic modeling and effective uncertainty analysis approaches have become necessary. The research results supported by this funding and presented in this report provide a new look at hydropower operational flexibility enforced by the changes identified above. Understanding how hydropower operates in response to the underlying uncertainties with respect to the system constraints is crucial in identifying its operational flexibility potentials. In this project, the flexibility of the operating hydropower facility is described by capturing uncertainties in both water and power system and formulating the operations as a multistage stochastic optimization problem. The proposed approach supports short- to seasonal-term operations and planning decision horizons.

13 HYDRO ENERGY↗
DOE OSTI2018

Tree cover shows strong sensitivity to precipitation variability across the global tropics

Abstract Aim Vegetation is sensitive to mean annual precipitation (MAP), but the sensitivity of vegetation to precipitation variability (PV) is less clear. Tropical ecosystems are likely to experience increased PV in the future. Here we assessed the importance, magnitude and mechanism of PV effects on tree cover in the context of covarying environmental drivers such as fire, temperature and soil properties. Location Tropical land. Time period 2000–2010. Major taxa studied Trees. Methods We compiled climate, soil and remotely‐sensed tree cover data over tropical land. We then comprehensively assessed the contribution of PV at different time‐scales to tropical tree cover variations and estimated the sensitivity of tree cover to PV changes by conducting rolling‐window regression and variance decomposition analyses. We further adopted a mechanistic modelling approach to test whether water competition between trees and grasses can explain the observed effect of PV. Results We find that PV contributes 33–56% to the total explained spatial variation (65–79%) in tree cover. The contribution of PV depends on MAP and is highest under intermediate MAP (500–1,500 mm). Tree cover generally increases with rainy day frequency and wet season length but shows mixed responses to inter‐annual PV. Based on the estimated sensitivity, tropical tree cover can decrease by 3–5% overall and by up to 20% in Amazonia under a 20% decrease in rainy days. Mechanistic modelling analysis reproduced the continental differences in tree cover along an MAP gradient. Main conclusions Under intermediate rainfall regimes (500–1,500 mm), PV can be a more important determinant of tropical tree cover than conventionally proposed drivers such as MAP and fire. The effect of PV likely results from the sensitivity of tree–grass competition to the temporal distribution of water resources. These results show that climate variability can strongly shape the biosphere.

Xu, Xiangtao↗