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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Scalable Transmission and Distribution Co-simulation Platform for IBR-heavy Power Systems

The integration of Inverter-Based Resources (IBRs) into power systems, including both transmission and distribution networks, poses challenges for studying grid dynamic behaviours under various operating conditions and system events. This paper addresses the urgent need to investigate the influence of IBRs on grid dynamics, and their potential to enhance power system reliability and resilience. We propose a flexible, scalable transmission and distribution co-simulation platform, using opensource tools only for assessing the impact of grid-following (GFL) and grid-forming (GFM) IBRs on dynamic stability at various renewable penetration levels (up to 100%). This platform enables researchers to explore different contingencies at transmission, distribution, or both, providing a comprehensive evaluation of grid status. A series of case studies, including both small and large T&D systems with varying GFL/GFM configurations and contingencies, have been conducted. The results not only robustly validate our co-simulation framework, but also provide invaluable insights for effective IBR management in the power grid.

grid management↗
DOE OSTI2025

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2021

Electric Drive Technology Trends, Challenges, and Opportunities for Future Electric Vehicles

The transition to electric road transport technologies requires electric traction drive systems to offer improved performances and capabilities, such as fuel efficiency (in terms of MPGe, i.e., miles per gallon of gasoline-equivalent), extended range, and fast-charging options. The enhanced electrification and transformed mobility are translating to a demand for higher power and more efficient electric traction drive systems that lead to better fuel economy for a given battery charge. To accelerate the mass-market adoption of electrified transportation, the U.S. Department of Energy (DOE), in collaboration with the automotive industry, has announced the technical targets for light-duty electric vehicles (EVs) for 2025. This article discusses the electric drive technology trends for passenger electric and hybrid EVs with commercially available solutions in terms of materials, electric machine and inverter designs, maximum speed, component cooling, power density, and performance. Additionally, the emerging materials and technologies for power electronics and electric motors are presented, identifying the challenges and opportunities for even more aggressive designs to meet the need for next-generation EVs. Some innovative drive and motor designs with the potential to meet the DOE 2025 targets are also discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Why Wideband Gap Needs Techno-Economics

The wideband gap community when discussing projects antidotally refers to the cost of the technology, frequently noting the higher wideband gap upfront cost in comparison to the incumbent state of art. Other technologies such as photovoltaics have embraced techno-economics analysis (TEA) as a method of analytically articulating the impacts of research advancements on system performance and lifetime costs. Our TEA shows the potential impact of research advancements on Gallium Oxide (Ga2O3) and Silicon Carbide (SiC) wafer manufacturing cost, the impact on the levelized cost of electricity (LCOE) when using a SiC based solar inverter, and lastly how the high cost of devices (SiC in this case) can be offset by other system cuts, such as the footprint and cooling reductions in a 1MW variable frequency motor drive. The specific goal is to show analytically the lifetime cost and performance benefits of adopting wideband gap technology whether it is at the device level or it is cumulative benefit though a simplified balance of system.

14 SOLAR ENERGY↗
DOE OSTI2026

A Systematic Framework for Tuning Open-Source Multifunctional IBR Models To Emulate OEM Black-Box Fault Dynamics

This paper presents a systematic framework to tune a generic IBR EMT model to match with an OEM provided balckbox inverter model based on the fault current responses. The key learnings and findings are summarized as follows: The tunable key parameters include inner control loops and current limiters to align the fault current magnitude, sequence content, and phase trajectories with the OEM models across diverse fault type and locations. The tuned model's fidelity is validated through comparative analysis with an OEM blackbox model, assessing both the fault current response and the responses of multiple relay elements. The results demonstrate the tuned generic model can trigger relay decision logic that is identical or near identical to that of the OEM model, thus generating very good match model for fault studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Blockchain-Enabled Cyber-Secure Microgrid Control Using Consensus Algorithm: Preprint

This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighboring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.

blockchain↗
DOE OSTI2024

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids: Preprint

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2023

Tailoring Crystallization Dynamics of CsPbI 3 for Scalable Production of Efficient Inorganic Perovskite Solar Cells

All-inorganic perovskite cesium lead triiodide (CsPbI 3 ) with inorganic nature, low-temperature synthesis, and a suitable bandgap is desirable for high-performance photovoltaics. However, the scalable production of CsPbI 3 photovoltaics is still challenging due to a large nucleation energy barrier and slow phase transition during unassisted natural crystallization. Here, the crystallization dynamics of CsPbI 3 thin films is tailored via lead acetate (PbAc 2 ) substitution in the perovskite precursor ink, allowing the scalable fabrication of efficient all-inorganic perovskite solar cells and minimodules. Introducing PbAc 2 enlarges CsPbI 3 colloid size in the precursor and reduces the nucleation energy barrier. Additionally, reactions between acetate and dimethylammonium in the wet film accelerate the removal of dimethylammonium additives and generate solvent vapors for self-regulate internal solvent annealing, resulting in densely packed, uniform, and pinhole-free CsPbI 3 perovskite films over large areas. This strategy demonstrates inverted CsPbI 3 solar cells with 20.17% efficiency and good operational stability (retaining 95.5% of initial efficiency after continuous operation for 1800 h) and 15.1%-efficient CsPbI 3 minimodules with an active area of 26.8 cm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Projective Representations, Bogomolov Multiplier, and Their Applications in Physics

We present a pedagogical review of projective representations of finite groups and their physical applications in quantum many-body systems. Some of our physical results are new. We begin with a self-contained introduction to projective representations, highlighting the role of group cohomology, representation theory, and classification of irreducible projective representations. We then focus on a special subset of cohomology classes, known as the Bogomolov multiplier, which consists of cocycles that are symmetric on commuting pairs but remain nontrivial in group cohomology. Such cocycles have important physical implications: they characterize (1+1)D SPT phases that cannot be detected by string order parameters and give rise, upon gauging, to distinct gapped phases with completely broken non-invertible Rep(G) symmetry. We construct explicit lattice models for these phases and demonstrate how they are distinguished by the fusion rules of local order parameters. We show that a pair of completely broken Rep(G) SSB phases host nontrivial interface modes at their domain walls. As an example, we construct a lattice model where the ground state degeneracy on a ring increases from 32 without interfaces to 56 with interfaces.

Bogomolov multiplier↗
DOE OSTI2025

Molecular level insight into non-bilayer structure formation in thylakoid membranes: a molecular dynamics study

In oxygenic photosynthetic organisms, the light reactions are performed by protein complexes embedded in the lipid bilayer of thylakoid membranes (TMs). The organization of the bulk lipid molecules into bilayer structures provide optimal conditions for the build-up of the proton motive force (pmf) and its utilization for ATP synthesis. However, the lipid composition of TMs is dominated by the non-bilayer lipid species monogalactosyl diacylglycerol (MGDG), and functional plant TMs, besides the bilayer, contain large amounts of non-bilayer lipid phases. Bulk lipids have been shown to be associated with lumenal, stromal-side and marginal-region proteins and proposed to play roles in the self-assembly and photoprotection of the photosynthetic machinery. Furthermore, it has recently been pointed out that the generation and utilization of pmf for ATP synthesis according to the ‘protet’ or protonic charge transfer model Kell (Biochim Biophys Acta Bioenerg 1865(4):149504, 2024), requires high MGDG content Garab (Physiol Plant 177(2):e70230, 2025). In this study, to gain better insight into the structural and functional roles of MGDG, we employed all atom and coarse-grained molecular dynamics simulations to explore how temperature, hydration levels and varying MGDG concentrations affect the structural and dynamic properties of bilayer membranes constituted of plant thylakoid lipids. Our findings reveal that MGDG promotes increased membrane fluidity and dynamic fluctuations in membrane thickness. MGDG-rich stacked bilayers spontaneously formed inverted hexagonal phases; these transitions were enhanced at low hydration levels and at elevated but physiologically relevant temperatures. It can thus be inferred that MGDG plays important roles in heat and drought stress mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Flexible dynamic boundary microgrid operation considering network and load unbalances

Flexible microgrids with dynamic boundaries have recently been introduced in the literature. With the ability to reconfigure the topology of the microgrids dynamically through remotely controlled switches, flexible microgrids with dynamic boundaries can further improve the resiliency and energy efficiency of microgrids with distributed energy resources (DERs). This paper focuses on the optimal operation considering one of the predominant characteristics of microgrids and distribution systems – unbalanced networks and loads. In existing literature, balanced modeling of microgrids is more common due to its attractive simplicity. The three-phase power unbalance has not been considered as a constraint on the generation units in a microgrid. Further, negative sequence constraints have also been neglected. In this article, we propose a set of constraints that is specifically related to the capabilities of inverter interfaced resources to supply unbalanced current/power when the microgrid is islanded from the main distribution grid. We incorporate the new set of constraints into two optimization formulations leveraging two convex relaxations of the three-phase power flow equations: mixed-integer linear programming (MILP) and mixed-integer semidefinite programming (MISDP) that optimize the dispatch of controllable switches and DERs in the microgrid. The algorithms are then extended to networked microgrids with grid-forming sources. We test the algorithms on a realistic community microgrid model in Puerto Rico as well as standardized IEEE distribution test feeders. The testing results demonstrate the performance of the proposed algorithms. The MILP is fast and scalable, and the MISDP enforces the negative sequence voltage constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗
DOE OSTI2024

An Open-Source Parallel EMT Simulation Framework

As the integration level of inverter-based resources (IBRs) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗
DOE OSTI2026

Analytical small-signal stability analysis of low-inertia power system frequency response considering secondary frequency regulation

Modern power systems are increasingly vulnerable to frequency instability as inverter-based resources (IBRs) replace synchronous machines and reduce system rotational inertia. Existing small-signal frequency stability assessment methods are either computationally intensive, relying on simulation-driven approaches, or lack analytical stability regions that explicitly account for secondary frequency response (SFR). This paper introduces new analytical frameworks that enable evaluation small-signal frequency stability while explicitly incorporating tunable IBR and SFR parameters. Using Kharitonov’s theorem with an overbounding approach, explicit small-signal stability criteria are derived. In addition, based on Białas’ criterion and Hurwitz matrix, analytical stability regions are established to reveal feasible design spaces for SFR and IBR parameters tuning. Extensive Matlab/Simulink-based simulations validate the accuracy and computational efficiency of the proposed methods, demonstrating that coordinated tuning of SFR and IBR parameters can substantially enhance system resilience. By bridging analytical rigor with practical tunability, this work provides an analytical framework for assessing small-signal frequency stability in low-inertia grids, supporting the real-time, scalable, and resilient operation of sustainable power systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2024

Validation of Phasor-Domain Transmission and Distribution Co-simulation Against Electromagnetic Transient Simulation

The rapid deployment of renewable energy resources has led to the widespread use of power electronics in modern power systems. As these systems transition from being dominated by large synchronous machines to increasingly incorporating inverter-based resources (IBRs), traditional methods are becoming inadequate. Addressing this challenge, this paper introduces a scalable phasor-domain T\&D co-simulation framework based on open-source software. It focuses on the framework's validation against the PSCAD Electromagnetic Transient (EMT) analysis tool. The validation results demonstrate the framework's high-fidelity and a computational time speed-up of 60 to 100 times, marking a pioneering validation effort in T\&D co-simulation research.

Inverter-based resources, co-simulation, Electroma↗
DOE OSTI2026

Polariton Control of Molecular Charge Transfer in Perylene Diimide Semiconductors

We report the modulation of molecular charge transfer in a bay-substituted perylene diimide derivative embedded in a planar distributed Bragg reflector microcavity. Angle-resolved reflectance spectra confirm the formation of upper and lower polaritons with clear Rabi splitting, indicating strong coupling between the cavity mode and molecular excitons. Using broadband transient absorption spectroscopy, we compare the ultrafast dynamics of cavity and non-cavity films. While excited-state absorption and stimulated emission pathways remain largely unchanged, kinetic modeling reveals a moderate increase in the charge transfer rate and yield under strong coupling. This enhancement is attributed to a reduction in the effective driving force via the formation of the lower polariton, placing the system deeper into the Marcus inverted regime. Our results demonstrate a promising non-chemical method leveraging cavity quantum electrodynamics to modulate charge separation processes in molecular semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗