Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “assets”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53

Anticipating water distribution service outages from increasing temperatures

With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.

54 ENVIRONMENTAL SCIENCES↗

Techno-economic analysis of synthetic fuel production from existing nuclear power plants across the United States

Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.

Garrouste, Marisol (ORCID:0000000168388644)↗

Studying Type II supernovae as cosmological standard candles using the Dark Energy Survey

ABSTRACT Despite vast improvements in the measurement of the cosmological parameters, the nature of dark energy and an accurate value of the Hubble constant (H0) in the Hubble–Lemaître law remain unknown. To break the current impasse, it is necessary to develop as many independent techniques as possible, such as the use of Type II supernovae (SNe II). The goal of this paper is to demonstrate the utility of SNe II for deriving accurate extragalactic distances, which will be an asset for the next generation of telescopes where more-distant SNe II will be discovered. More specifically, we present a sample from the Dark Energy Survey Supernova Program (DES-SN) consisting of 15 SNe II with photometric and spectroscopic information spanning a redshift range up to 0.35. Combining our DES SNe with publicly available samples, and using the standard candle method (SCM), we construct the largest available Hubble diagram with SNe II in the Hubble flow (70 SNe II) and find an observed dispersion of 0.27 mag. We demonstrate that adding a colour term to the SN II standardization does not reduce the scatter in the Hubble diagram. Although SNe II are viable as distance indicators, this work points out important issues for improving their utility as independent extragalactic beacons: find new correlations, define a more standard subclass of SNe II, construct new SN II templates, and dedicate more observing time to high-redshift SNe II. Finally, for the first time, we perform simulations to estimate the redshift-dependent distance-modulus bias due to selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗

Two-Photon Spontaneous Emission in Atomically Thin Plasmonic Nanostructures

The ability to harness light-matter interactions at the few-photon level plays a pivotal role in quantum technologies. Single photons—the most elementary states of light—can be generated on demand in atomic and solid state emitters. Two-photon states are also key quantum assets, but achieving them in individual emitters is challenging because their generation rate is much slower than competing one-photon processes. We demonstrate that atomically thin plasmonic nanostructures can harness two-photon spontaneous emission, resulting in giant far field two-photon production, a wealth of resonant modes enabling tailored photonic and plasmonic entangled states, and plasmon-assisted single-photon creation orders of magnitude more efficient than standard one-photon emission. We unravel the two-photon spontaneous emission channels and show that their spectral line shapes emerge from an intricate interplay between Fano and Lorentzian resonances. Enhanced two-photon spontaneous emission in two-dimensional nanostructures paves the way to an alternative efficient source of light-matter entanglement for on-chip quantum information processing and free-space quantum communications.

36 MATERIALS SCIENCE↗

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

Digital Twin of an ANPC inverter with integrated Design-For-Trust

Reducing costs and increasing manufacturing output while creating reliable products are three essential components needed to keep a business competitive. In the past, having an asset that could address these three challenges at the same time would be challenging. However, recent advances in computer processing capabilities coupled with increases to network speeds allowed such a system to become possible; and this is known as a Digital Twin (DT), which represents a virtual copy of a production system or a product. Here, this work exhibits a DT application of an Active Neutral Point Clamped (ANPC) inverter using a controller. The controller emulates the ANPC responses of a new Digital Signal Processing (DSP) firmware and validates this new firmware by using Design-For-Trust (DFTr) characteristics. If the new firmware is malicious, then it should be rejected, thus adding preemptive protection measures for inverter based distributed energy resources.

cybersecurity↗

Field Testing of a Hierarchical Model-Free Transactive Control Strategy in a Residential House

Demand response plays an important role in addressing the uncertain, intermittent, and variable nature of renewable energy sources. However, to be effective, it requires a significant amount of demand load flexibility, in which buildings are important flexible assets for electricity systems. In this regard, many transactive control tools have been developed to harness this demand flexibility. Yet, such tools are mostly simulation-based or deal with a single load, which may not be sufficient to demonstrate their effectiveness. Towards this end, this paper presents a field implementation and testing of a hierarchical model-free transactive control strategy using residential building thermostatically controlled loads. The transactive control implementation incorporates elements of virtual battery, game theory, and model-free control mechanisms. Experimental field-testing results are provided to demonstrate the effectiveness of the proposed transactive control strategy.

Olama, Mohammed M.↗

A Networked Microgrid Framework and Testbed for Communication, Controls, and Optimization Testing

This paper presents the development and experimental results of a networked AC microgrid testbed located at Oak Ridge National Laboratory. The testbed comprises two, 480V three-phase, four wire microgrids designed to operate standalone, grid-tied, or as a network of microgrids. This testbed represents both the state of the industry, by incorporating grid-assets commonly found in real microgrids, and the state of the art, as it is a platform to evaluate advanced controllers. The main elements of this networked microgrid testbed are presented in this paper including a Scenario Manager, local microgrid controls, and a networked microgrid control. The Scenario Manager has the objective of emulating real-world conditions. The local microgrid controller oversees standalone, grid-tied, or islanded operation. The microgrid control is a higher-level control that coordinates interaction between islanded microgrids. This paper delves into these controllers and validates their operation in the networked microgrid testbed showcasing the operational flexibility and advance control capabilities.

Ferrari Maglia, Max↗

Hybrid Energy Management with Real-Time Control of a High-Power EV Charging Site

Decarbonization of transportation systems is driving higher capacity energy storage and faster charging power requirements in electric vehicles (EVs). Given the potential advantages - such as increased efficiency, reduced inverter capacity, and less total cable mass - there is a demand in the industry for more DC distribution for high-power charging (HPC) hubs. However, the cost-effective, adaptive, and robust operation of the DC-coupled HPC hub necessitates a robust site energy management system (SEMS). Validating SEMS operation using a digital twin of an HPC hub in a real-time simulator (RTS) platform is crucial before field deployment. In this study, we propose a hybrid energy management site controller designed to achieve high-level, long-term operational objectives while managing low-level power sharing control between hub assets. We develop a centralized model predictive controller (MPC) to optimize hub operating points and use these points to update the droop parameters of the site energy storage system (ESS). This approach ensures the hub follows an optimal operating point while maintaining the flexibility to respond to load surges. We tested and verified our proposed approach both offline and on a Controller Hardware-in-the-loop (C-HIL) simulation platform integrated with a SEMS framework, demonstrating real-time site operation and validating a cost-effective and robust site controller.

ADVANCED PROPULSION SYSTEMS↗

Hydro-battery Hybrids – A Case for Holistic Assessment of Hybrid Energy Systems

With increasing penetration of renewable energy resources like solar and wind, the flexibility offered by the hydropower generation facilities would be instrumental in providing grid reliability. However, hydropower’s capabilities are often constrained to meet asset management targets and environmental flow requirements. To meet these necessary requisites while simultaneously being able to utilize hydropower’s full potential, hydro plus battery hybrids offer a logical solution. However it is often challenging to make the case for economic feasibility of hydro-battery hybrids at the required scale of battery storage. To that end, this paper proposes a multi-objective optimization framework to maximize advantages of hydro-battery hybrid systems from three different avenues: new market opportunities, environmental benefits and machine wear and fatigue. Using an illustrative case study of a peaking plant, we simulate hydropower operations for with and without 120 MWh of battery storage for four different simulated flow patterns ranging from peaking operations to run-of-the-river operations and two intermediate flow patterns in between. The results demonstrate that hybridizing the hydropower plant can potentially generate additional revenue while simultaneously enable more environmental friendly operations and reduce the overall machine wear and tear.

Chalishazar, Vishvas H.↗

Pathways and Insights from Community Solar: A Guide to Community Energy Storage Success

Community energy assets bring the benefits of renewables to all energy system stakeholders, not just those with sufficient capital, land ownership, and resources. As the price of energy storage continues to decline and energy equity and justice principles are incorporated into policies and planning activities, Community Energy Storage (CES) is poised to follow in the footsteps of Community Solar’s (CS) success. Though CES is in its early stages and faces many unique challenges, it is an invaluable tool on the pathway to decarbonization, with the potential to increase renewable access, energy affordability, resilience, energy independence, wealth creation, and community empowerment. This paper provides a brief review of the history of CS, comparing the market and regulatory advances of CS to the current state of CES. The lessons learned from the rise of CS are then adapted to support those working to increase CES adoption in pursuit of a more equitable and sustainable energy system for all.

community energy planning, community solar, commun↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Disruptive Photovoltaic Technologies Can Accelerate Global Decarbonization

This contribution explores PV manufacturing capacity expansion trajectories needed to achieve the goal of global decarbonization assuming that investors make financially rational decisions avoiding stranded production assets while still effectively exploiting experience curve benefits in both manufacturing process and product design. Substantial production cost savings and timely decarbonization risk mitigation could accrue by adoption and scaling of high efficiency multijunction device architectures and thin film direct bandgap semiconductor technologies that provide lower manufacturing capital intensity. We demonstrate that there is a $1-2 trillion market opportunity for such disruptive technologies while also providing hundreds of billions of dollars of cost savings to reach total decarbonization.

decarbonization↗

The Effect of Clean Energy Generation Targets on the Portfolio of Electric Grid Generation Technologies

A least-cost generation and transmission expansion planning model is used to optimize the U.S. generation portfolio in 2030 under a range of Clean Energy Generation Target (CEGT) policy goals. As reference cases for comparison, the model is used to optimize the generation portfolio for the future electric grid with and without the Investment and Production Tax Credits (ITC and PTC). Next, the model is used to optimize the generation portfolio with a CEGT ranging from 10% to 70%. The results show that due to the ITC and PTC extensions by the 2022 Inflation Reduction Act, there is little additional investment in renewable energy generation assets at low CEGT levels. Significant additional installations of both renewable energy generation and energy storage systems – both batteries and pumped storage hydro – become important at CEGT levels above approximately 30%.

Aldeman, Matthew↗

High-Penetration Microgrids Providing Grid Stability Using Frequency Watt Control

The U.S. grid is rapidly transitioning towards utilizing inverter-based renewable energy resources such as solar, wind, and batteries, reducing the carbon emission footprint. Inverter-based microgrid control architectures remain a critical focus to address power system stability issues in future high penetration markets lacking spinning generation assets. Idaho National Laboratory (INL) is researching an active layered inverter based frequency-Watt control scheme that provides distribution level stability in high-penetration markets where grid inertia is lacking. Hardware in the loop case study was implemented using INL’s Microgrid Testbed to combat scalable frequency deviations ranging from 60 Hz down to 50 Hz initialized by a hydropower model implementing step loads using a 540-kW grid emulator. Our research findings demonstrate the importance of distribution level, inverter-based active frequency-Watt controls utilizing a battery energy storage system (BESS) to provide adequate frequency support at the point of common coupling without major power infrastructure upgrades.

14 SOLAR ENERGY↗

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Scalable Wind Turbine Generator Bearing Fault Prediction Using Machine Learning: A Case Study

Operation and maintenance (O&M) costs for wind turbines pose a risk to competitiveness and asset owners. With machine-learning technologies and digitalization rapidly maturing, the wind industry is actively investigating these new technologies to optimize O&M practices and reduce costs. This paper reviews recent work on machine-learning approaches to generator bearing failure prediction and presents a relevant real-world case study through a collaboration between the National Renewable Energy Laboratory and Envision Digital Corporation. In the case study, we evaluate the performance of representative machine-learning algorithms for predicting wind turbine generator bearing failures. Operational supervisory control and data acquisition data from one wind power plant was used to train and test the machine-learning models. The investigated data channels are chosen based on whether physically they reflect the failed generator bearing conditions and the component historical usage, including both environmental and operational conditions. Benefits and drawbacks of different methods are identified.

generator bearing failures↗

An Alternative Timing and Synchronization Approach for Situational Awareness and Predictive Analytics

Accurate and synchronized timing information is required by power system operators for controlling the grid infrastructure (relays, Phasor Measurement Units (PMUs), etc.) and determining asset positions. Satellite-based global positioning system (GPS) is the primary source of timing information. However, GPS disruptions today (both intentional and unintentional) can significantly compromise the reliability and security of our electric grids. A robust alternate source for accurate timing is critical to serve both as a deterrent against malicious attacks and as a redundant system in enhancing the resilience against extreme events that could disrupt the GPS network. To achieve this, we rely on the highly accurate, terrestrial atomic clock-based network for alternative timing and synchronization. In this paper, we discuss an experimental setup for an alternative timing approach. The data obtained from this experimental setup is continuously monitored and analyzed using various time deviation metrics. We also use these metrics to compute deviations of our clock with respect to the National Institute of Standards and Technologys (NIST) GPS data. The results obtained from these metric computations are elaborately discussed. Finally, we discuss the integration of the procedures involved, like real-time data ingestion, metric computation, and result visualization, in a novel microservices-based architecture for situational awareness.

Chinthavali, Supriya↗