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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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Extracting Lessons of Resilience Using Machine Mining of the ASRS Database

NASA’s Aviation Safety Reporting System (ASRS) database is the world's largest repository of voluntary, confidential safety information provided by aviation's frontline personnel, including pilots, air traffic controllers, mechanics, flight attendants, dispatchers, and other members of the aviation community and the public. The database contains close to 2 million narratives, many of which describe everyday situations in which people saved the day. In these situations, people’s resilient behavior solved a problem, dealt with a malfunction, and maintained a safe operation despite a serious perturbation. To be able to extract lessons of such resilience from this large database, the use of machine learning algorithms is being explored. In this report, we describe a comparison between two such algorithms: Perilog and Word2Vec. An identical search using both programs was done on a database containing approximately 470,000 ASRS reports submitted between 1988 and 2022. The comparison reveals some of the strength and weaknesses of each algorithm as well as the challenges inherent in using such algorithms to extract lessons of resilience from the ASRS database.

resilience↗
NASA NTRS2023

Fighting Wildfires Using UAVs Using Autonomous Biodegradable Self-sacrificing (ABS) Drones to Combat Large Wildfires with the Assistance of Satellite Imagery

As wildfires continue to increase in number and severity due to global warming, firefighters are having a harder time combating them safely. This paper examines the application of Autonomous Biodegradable Self-sacrificing (ABS) Drones as a method of fighting wildfires that decreases the number of lives put at risk and proposes a sustainable alternative to current aerial firefighting methods. When a fire is detected or predicted through satellite imagery, ABS Drones are dispatched from firefighting stations or aerial watchtowers to fly towards designated areas and release fire retardants, preventing the fire from further spreading. The most significant feature of this drone is its ability to complete its mission without having to worry about returning safely because ABS Drones are designed to crash and release fire retardants, while not further harming the environment with water-based lithium-ion batteries and a biodegradable body. ABS Drones make it safer for firefighters as it gives firefighters one less life-threatening task to do and allows them to focus on putting out the fire. This solution aims to tackle the unpredictable nature of wildfires that often threaten the safety of firefighters and civilian communities.

ABS Drones↗
NASA NTRS2024

Recipes for Forming a Carbon–Rich Giant Planet

The exploration of carbon-to-oxygen ratios has yielded intriguing insights into the composition of close-in giant exoplanets, giving rise to a distinct classification: carbon-rich planets, characterized by a carbon–to–oxygen ratio ≥ 1 in their atmospheres, as opposed to giant planets exhibiting carbon–to–oxygen ratios close to the protosolar value. In contrast, despite numerous space missions dispatched to the outer solar system and the proximity of Jupiter, Saturn, Uranus, and Neptune, our understanding of the carbon-to-oxygen ratio in these giants remains notably deficient. Determining this ratio is crucial as it serves as a marker linking a planet’s volatile composition directly to its formation region within the disk. This article provides an overview of the current understanding of the carbon-to-oxygen ratio in the four gas giants of our solar system and explores why there is yet no definitive dismissal of the possibility that Jupiter, Saturn, Uranus, or Neptune could be considered carbon-rich planets. Additionally, we delve into the three primary formation scenarios proposed in existing literature to account for a bulk carbon-to-oxygen ratio ≥ 1 in a giant planet. A significant challenge lies in accurately inferring the bulk carbon-to-oxygen ratio of our solar system’s gas giants. Retrieval methods involve integrating in situ measurements from entry probes equipped with mass spectrometers and remote sensing observations conducted at microwave wavelengths by orbiters. However, these methods fall short of fully discerning the deep carbon-to-oxygen abundance in the gas giants due to their limited probing depth, typically within the 10–100 bar range. To complement these direct measurements, indirect determinations rely on understanding the vertical distribution of atmospheric carbon monoxide in conjunction with thermochemical models. These models aid in evaluating the deep oxygen abundance in the gas giants, providing valuable insights into their overall composition.

Protosolar nebula↗
DOE OSTI2017

Capacity Expansion Modeling for Storage Technologies

The Resource Planning Model (RPM) is a capacity expansion model designed for regional power systems and high levels of renewable generation. Recent extensions capture value-stacking for storage technologies, including batteries and concentrating solar power with storage. After estimating per-unit capacity value and curtailment reduction potential, RPM co-optimizes investment decisions and reduced-form dispatch, accounting for planning reserves; energy value, including arbitrage and curtailment reduction; and three types of operating reserves. Multiple technology cost scenarios are analyzed to determine level of deployment in the Western Interconnection under various conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

The Eastern Renewable Generation Integration Study: Insights on System Stress: Preprint

The Eastern Renewable Generation Integration Study (ERGIS) explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in North America's Eastern and Quebec Interconnections. We explore the impact of large scale adoption of wind and solar generation on the unit commitment and economic dispatch of the largest coordinated power system in the world by simulating hourly and five-minute operations. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the modeled system, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and solar PV at a five-minute level under a variety of conditions. Our simulations achieve instantaneous penetrations that exceed 50% of load while meeting an annual penetration of 30% on an energy basis. The system meets balanced load and supply in all intervals, with modest curtailment, using technologies and practices that are widely available today. However, a variety of the conditions present in these simulations deviate substantially from historical practice. In this work, we analyze potentially stressful system conditions that occur in the simulations and identify opportunities for innovation, regulatory reform, and changes in operating practices that require further analysis to enable the transition to a system with more wind and solar PV.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

8760-Based Method for Representing Variable Generation Capacity Value in Capacity Expansion Models: Preprint

Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve demand over the evolution of many years or decades. Various CEM formulations are used to evaluate systems ranging in scale from states or utility service territories to national or multi-national systems. CEMs can be computationally complex, and to achieve acceptable solve times, key parameters are often estimated using simplified methods. In this paper, we focus on two of these key parameters associated with the integration of variable generation (VG) resources: capacity value and curtailment. We first discuss common modeling simplifications used in CEMs to estimate capacity value and curtailment, many of which are based on a representative subset of hours that can miss important tail events or which require assumptions about the load and resource distributions that may not match actual distributions. We then present an alternate approach that captures key elements of chronological operation over all hours of the year without the computationally intensive economic dispatch optimization typically employed within more detailed operational models. The updated methodology characterizes the (1) contribution of VG to system capacity during high load and net load hours, (2) the curtailment level of VG, and (3) the potential reductions in curtailments enabled through deployment of storage and more flexible operation of select thermal generators. We apply this alternate methodology to an existing CEM, the Regional Energy Deployment System (ReEDS). Results demonstrate that this alternate approach provides more accurate estimates of capacity value and curtailments by explicitly capturing system interactions across all hours of the year. This approach could be applied more broadly to CEMs at many different scales where hourly resource and load data is available, greatly improving the representation of challenges associate with integration of variable generation resources.

14 SOLAR ENERGY↗
DOE OSTI2017

Novel Control Strategy for Multiple Run-of-the-River Hydro Power Plants to Provide Grid Ancillary Services

Electricity generated by Hydropower Plants (HPPs) contributes a considerable portion of bulk electricity generation and delivers it with a low carbon footprint. In fact, HPP electricity generation provides the largest share from renewable energy resources, which includes solar and wind energy. The increasing penetration of wind and solar penetration leads to a lowered inertia in the grid and hence poses stability challenges. In recent years, breakthrough in energy storage technologies have demonstrated the economic and technical feasibility of extensive deployments in power grids. Multiple ROR HPPs if integrated with scalable, multi time-step energy storage so that the total output can be controlled. Although, the size of a single energy storage is far smaller than that of a typical reservoir, cohesively managing multiple sets of energy storage distributed in different locations is proposed. The ratings of storages and multiple ROR HPPs approximately equals the rating of a large, conventional HPP. The challenges associated with the system architecture and operation are described. Energy storage technologies such as supercapacitors, flywheels, batteries etc. can function as a dispatchable synthetic reservoir with a scalable size of energy storage will be integrated. Supercapacitors, flywheels, and battery are chosen to provide fast, medium, and slow responses to support grid requirements. Various dynamic and transient power grid conditions are simulated and performances of integrated ROR HPPs with energy storage is provided. The end goal of this research is to investigate the inertial equivalence of a large, conventional HPP with a unique set of multiple ROR HPPs and optimally rated energy storage systems.

13 HYDRO ENERGY↗
DOE OSTI2017

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

17 WIND ENERGY↗
DOE OSTI2017

Distributed hierarchical control architecture for integrating smart grid assets during normal and disrupted operations

Disclosed herein are representative embodiments of methods, apparatus, and systems for facilitating operation and control of a resource distribution system (such as a power grid). Among the disclosed embodiments is a distributed hierarchical control architecture (DHCA) that enables smart grid assets to effectively contribute to grid operations in a controllable manner, while helping to ensure system stability and equitably rewarding their contribution. Embodiments of the disclosed architecture can help unify the dispatch of these resources to provide both market-based and balancing services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Western Region

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Southern Region

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: to better anticipate, understand, and mitigate system constraints that could affect RE integration; and to provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Preliminary Findings of the South Africa Power System Capacity Expansion and Operational Modelling Study: Preprint

Wind and solar power contract prices have recently become cheaper than many conventional new-build alternatives in South Africa and trends suggest a continued increase in the share of variable renewable energy (vRE) on South Africa's power system with coal technology seeing the greatest reduction in capacity, see 'Figure 6: Percentage share by Installed Capacity (MW)' in [1]. Hence it is essential to perform a state-of-the-art grid integration study examining the effects of these high penetrations of vRE on South Africa's power system. Under the 21st Century Power Partnership (21CPP), funded by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has significantly augmented existing models of the South African power system to investigate future vRE scenarios. NREL, in collaboration with Eskom's Planning Department, further developed, tested and ran a combined capacity expansion and operational model of the South African power system including spatially disaggregated detail and geographical representation of system resources. New software to visualize and interpret modelling outputs has been developed, and scenario analysis of stepwise vRE build targets reveals new insight into associated planning and operational impacts and costs. The model, built using PLEXOS, is split into two components, firstly a capacity expansion model and secondly a unit commitment and economic dispatch model. The capacity expansion model optimizes new generation decisions to achieve the lowest cost, with a full understanding of capital cost and an approximated understanding of operational costs. The operational model has a greater set of detailed operational constraints and is run at daily resolutions. Both are run from 2017 through 2050. This investigation suggests that running both models in tandem may be the most effective means to plan the least cost South African power system as build plans seen to be more expensive than optimal by the capacity expansion model can produce greater operational cost savings seen only in the operational model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

REopt Lite Web Tool

NREL developed a free, publicly available web version of the REopt (TM) renewable energy integration and optimization platform called REopt Lite. REopt Lite recommends the optimal size and dispatch strategy for grid-connected photovoltaics (PV) and battery storage at a site. It also allows users to explore how PV and storage can increase a site's resiliency during a grid outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Retrofitting a Geothermal Plant with Solar and Storage to Increase Power Generation

Solar hybridization using concentrating solar power (CSP) can be an effective approach to augment the power generation and power cycle efficiency of a geothermal power plant with a declining resource. Thermal storage can further increase the dispatchability of a geothermal/solar hybrid system, which is particularly valued for a national grid with high renewable penetration. In this paper, a hybrid plant design with thermal storage is proposed based on the requirements of the Coso geothermal field in China Lake, California. The objective is to increase the power production by 4 MWe. In this system, a portion of the injection brine is recirculated through a heat exchanger with the solar heat transfer fluid, before being mixed with the production well brine. In the solar heating loop the brine should be heated to at least 155 degrees C to increase the net power. The solar field and storage were sized based on solar data for China Lake. Thermal storage is used to store excess power at the high-solar-irradiation hours and generate additional power during the evenings. The solar field size, the type and capacity of thermal storage and the operating temperatures are critical factors in determining the most economic hybrid system. Further investigations are required to optimize the hybrid system and evaluate its economic feasibility.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Distributed Energy Resources Customer Adoption Model - Graphical User Interface, Version 2.1.8

The DER-CAM Graphical User Interface has been redesigned to consist of a dynamic tree structure on the left side of the application window to allow users to quickly navigate between different data categories and views. Views can either be tables with model parameters and input data, the optimization results, or a graphical interface to draw circuit topology and visualize investment results. The model parameters and input data consist of tables where values are assigned to specific keys. The aggregation of all model parameters and input data amounts to the data required to build a DER-CAM model, and is passed to the GAMS solver when users initiate the DER-CAM optimization process. Passing data to the GAMS solver relies on the use of a Java server that handles DER-CAM requests, queuing, and results delivery. This component of the DER-CAM GUI can be deployed either locally or remotely, and constitutes an intermediate step between the user data input and manipulation, and the execution of a DER-CAM optimization in the GAMS engine. The results view shows the results of the DER-CAM optimization and distinguishes between a single and a multi-objective process. The single optimization runs the DER-CAM optimization once and presents the results as a combination of summary charts and hourly dispatch profiles. The multi-objective optimization process consists of a sequence of runs initiated by the GUI, including: 1) CO2 minimization, 2) cost minimization, 3) a user defined number of points in-between objectives 1) and 2). The multi-objective results view includes both access to the detailed results of each point generated by the process as well as the generation of a Pareto Frontier graph to illustrate the trade-off between objectives. DER-CAM GUI 2.1.8 also introduces the ability to graphically generate circuit topologies, enabling support to DER-CAM 5.0.0. This feature consists of: 1) The drawing area, where users can manually create nodes and define their properties (e.g. point of common coupling, slack bus, load) and connect them through edges representing either power lines, transformers, or heat pipes, all with user defined characteristics (e.g., length, ampacity, inductance, or heat loss); 2) The tables, which display the user-defined topology in the final numerical form that will be passed to the DER-CAM optimization. Finally, the DER-CAM GUI is also deployed with a database schema that allows users to provide different energy load profiles, solar irradiance profiles, and tariff data, that can be stored locally and later used in any DER-CAM model. However, no real data will be delivered with this version.

Ewald, Friedrich↗
DOE OSTI2018

NREL's Resource Planning Model

The Resource Planning Model (RPM) is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. Designed from the ground up to include nodal detail, hourly chronological dispatch, and high spatial resolution for renewable resources, recent work has focused on inclusion of storage and other flexible technologies of interest for future power systems with more variable generation (e.g., wind and solar). This slide deck gives an overview of RPM modeling methods, provides example outputs, and briefly summarizes completed analysis projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Economic Sizing of Batteries for the Smart Home: Preprint

This paper presents a methodology to economically size a home battery based on parametric analysis using home energy management system (HEMS) software to optimally dispatch the battery along with controllable loads under several use cases. We account for connected equipment, controls, renewable resources, and other factors such as building characteristics and utility tariffs. The paper defines an analytical pathway for such a sizing tool, develops initial sizing guidance, and clarifies technical and market opportunities for home batteries in the context of existing and emerging equipment and control technologies. A parametric analysis that included 132 scenarios has been performed based on different combinations of pertinent parameters. Results indicate that four variables dominate the decision-making process: application scenarios (new construction or retrofit), utility tariffs, existence of HEMS, and the anticipated payback time. Life-cycle cost analysis indicated that in the absence of utility incentives, batteries plus HEMS have a payback time of longer than 10 years for new construction under a time-of-use rate structure and feed-in tariff; larger batteries have a longer payback time but may provide more benefits to utilities on reducing power backfeed under certain circumstances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗