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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Optimizing Distributed Photovoltaic System Set Points Under Uncertainty

We explore the potential for using dynamic programming (DP) and approximate dynamic programming (ADP) techniques to optimize the set points of distributed photovoltaic (DGPV) inverters under uncertainty about future DGPV deployment. We consider a case where a large (=1MW) system is installed first, and growth in deployment of small rooftop systems is anticipated, but uncertain. We find that for a real feeder (EPRI's J1 feeder), a significant reduction in the number and severity of voltage violations can be expected when DP or ADP is used compared to selecting set points based on the current conditions (the traditional myopic approach). Additionally, we find that using a simple ADP algorithm, sampled backward induction, is more than twice as fast as DP with similar outcomes.

14 SOLAR ENERGY↗
DOE OSTI2024

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases, distribution system state estimation (DSSE) and fault identification are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1 feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system↗
DOE OSTI2025

New Measurements of the Deuteron-to-Proton 𝐹 2 Structure-Function Ratio

Nucleon structure functions, as measured in lepton-nucleon scattering, have historically provided a critical observable in the study of partonic dynamics within the nucleon. However, at very large parton momenta, it is both experimentally and theoretically challenging to extract parton distributions due to the probable onset of nonperturbative contributions and the unavailability of high-precision data at critical kinematics. Extraction of the neutron structure and the d quark distribution have been further challenging because of the necessity of applying nuclear corrections when utilizing scattering data from a deuteron target to extract the free neutron structure. However, a program of experiments has been carried out recently at the energy-upgraded Jefferson Lab electron accelerator aimed at significantly reducing the nuclear correction uncertainties on the d quark distribution function at large partonic momentum. This allows leveraging the vast body of deuterium data covering a large kinematic range to be utilized for d quark parton distribution function extraction. In this Letter, we present new data from experiment E12-10-002, carried out in Jefferson Lab Experimental Hall C, on the deuteron to proton cross section ratio at large Bjorken 𝑥. These results significantly improve the precision of existing data and provide a first look at the expected impact on quark distributions extracted from parton distribution function fits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

NNSA Minority Serving Institute Partnership Program (MSIPP)— Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE) (FY22 Q1 Progress Report)

In 2016, the National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) targeting Tribal Colleges and Universities (TCUs) to offer programs that will prepare students for technical careers in NNSA’s laboratories and production plants. The MSIPP consortium’s approach is as follows: 1) align investments at the college and university level to develop a curriculum and workforce needed to support NNSA’s nuclear weapon enterprise mission, and 2) to enhance research and education at under-represented colleges and universities. The first TCU consortium that MSIPP launched was known as the Advanced Manufacturing Network Initiative (AMNI) whose purpose was to develop additive manufacturing (AM) learning opportunities. The AMNI consortium consisted of Bay Mills Community College, Cankdeska Cikana Community College, Navajo Tech University, Salish Kootenai Community College, Turtle Mountain Community College, and United Tribes Technical College. In 2016, the American Indian Higher Education Consortium (AIHEC), the AMNI consortium and the Southwestern Indian Polytechnic Institute (SIPI), in collaboration with Sandia National Labs, using a grant by NNSA hosted the first TCU Advanced Manufacturing Technology Summer Institute (TCU AMTSI). The AMNI consortium will officially end Sept. 2022. However, building on the successes of AMNI, in FY22 NNSA’s MSIPP launched three additional consortiums: (1) the Indigenous Mutual Partnership to Advanced Cybersecurity Technology (IMPACT), which focuses on STEM and cybersecurity, (2) the Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE), which focuses on STEM and the electrical and mechanical engineering skills set needed for renewable and distributed energy systems, and (3) the Partnership for Advanced Manufacturing Education and Research (PAMER), which focuses on developing and maintaining a sustainable pathway for a highly trained, next-generation additive manufacturing workforce and a corresponding community of subject matter experts for NNSA enterprises. The following report summarizes the status update during this quarter for the ASPIRE program.

42 ENGINEERING↗
DOE OSTI2021

Controlled Islanding Strategy Considering Uncertainty of Renewable Energy Sources Based on Chance-constrained Model

Controlled islanding plays an essential role in preventing the blackout of power systems. Although there are several studies on this topic in the past, not enough attention is paid to the uncertainty brought by renewable energy sources (RESs) that may cause unpredictable unbalanced power and the observability of power systems after islanding that is essential for back-up black-start measures. Therefore, a novel controlled islanding model based on mixed-integer second-order cone and chance-constrained programming (MISOCCP) is proposed to address these issues. First, the uncertainty of RESs is characterized by their possibility distribution models with chance constraints, and the requirements, e. g., system observ-ability, for rapid back-up black-start measures are also considered. Then, a law of large numbers (LLN) based method is employed for converting the chance constraints into deterministic ones and reformulating the non-convex model into convex one. Finally, case studies on the revised IEEE 39-bus and 118-bus power systems as well as the comparisons among different models are given to demonstrate the effectiveness of the proposed model. The results show that the proposed model can result in less unbalanced power and better observability after islanding compared with other models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework: Preprint

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb and observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. The proposed DERMS online platform is generalizable to deal with various types of distributed energy resources (DERs), including distributed photovoltaics (PVs), energy storage, electric vehicles, demand response, etc. Comparison results with other control methods on a realistic distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resources management↗
DOE OSTI2020

Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles

With the intermittency that comes with electricity generation from renewables, utilizing dynamic pricing will encourage the demand-side to respond in a smart way that would minimize the electricity costs and flatten the net electricity demand curve. Determining the optimal dynamic pricing profile that would leverage distributed storage to flatten the curve is a novel idea that needs to be studied. Moreover, the economic feasibility of utilizing distributed electrical energy storage is still not given in the literature. Therefore, in this paper, a novel way of solving a citywide dynamic model using a bilevel programming algorithm is introduced. The problem is developed as a novel non-cooperative Stackelberg game that utilizes air-conditioning systems and electrical storage through the end-users to determine the optimal dynamic pricing profile. The results show that the combined effect of utilizing demand-side air-conditioning systems and distributed storage together can flatten the curve while employing the optimal dynamic pricing profile. An economic study is performed to determine the economic feasibility of 20 different cases with different battery designs and the level of solar penetration. Three metrics were used to evaluate the economic performance of each case: the levelized cost of storage, the levelized cost of energy, and the simple payback period. Most cases had levelized cost of storage values lower than 0.457 $/kWh, which is the lower bound available in the literature. Seven out of 16 cases have a simple payback period shorter than the lifetime of the system (25 years). The case with a 100 MW PV power plant and a battery storage of size 597 MWh, was found to be the most promising case with a simple payback period of 12.71 years for the photovoltaic plant and 19.86 years for the demand-side investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Power-Hardware-in-the-Loop (PHIL) Evaluation of Service Restoration With Networked Microgrids

This paper describes the power-hardware-in-the- loop (PHIL) evaluation of the feasibility of service restoration solutions determined by the PowerModelsONM.jl tool. This tool incorporates microgrids and the networking of microgrids into its determination of an optimal service restoration solution. The paper presents PHIL simulation results for a case study based on a real distribution feeder with multiple microgrids, showcas- ing the effectiveness of networked microgrids in aiding system restoration after an outage. The study leverages high-fidelity, real- time electromagnetic transient models to ensure accuracy in the simulation results. This work is the final output from the Resilient Operation of Networked Microgrids (RONM) project funded by the U.S. Department of Energy Office of Electricity Microgrid Program and led by Los Alamos National Laboratory. RONM focused on the application of PowerModelsONM.jl to enhance the resilience of distribution systems.

fault location isolation and service restoration (↗
DOE OSTI2020

Utility Combined Heat and Power (CHP) Programs

This issue brief provides an overview of energy efficiency portfolios offered by electric and gas utilities that include CHP incentive programs, with examples of program drivers, structures, and eligibility criteria. The document discusses best practices for designing and administering a utility CHP incentive program, including cost-effectiveness tests and market outreach strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

DER Planning with Resilience Analysis Using REopt Lite: A Behind-the-Meter Techno-Economic Analysis Tool

REopt Lite is a techno-economic decision support model for behind-the-meter energy systems design and dispatch modeling. REopt Lite is used to optimize energy systems for buildings, campuses, communities, and microgrids. It is based on a Mixed Integer Linear Programming (MILP) optimization model. It is a fully automated and streamlined energy modeling tool that can be used off-the-shelf for a wide variety of distributed generation integration analyses and at the same time is architected to be extensible for user-specific customizations for advanced users and subject matter experts. It is publicly available as a webtool as well as has an Application Programming Interface (API). The API functionality enables programmatic access to the model facilitating smooth integration with other distribution systems modeling tools, and automated multiple scenarios/sensitivity studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Operational experience and R&D results using the Google Cloud for High-Energy Physics in the ATLAS experiment

The ATLAS experiment at CERN relies on a Worldwide Distributed Computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and operation, elasticity and availability of diverse infrastructures. Here this paper examines the seamless integration of cloud computing services as a conventional Grid site within the ATLAS workflow management and data management systems, while also offering new setups for interactive, parallel analysis. It underscores pivotal results that enhance the on-site computing model and outlines several R&D projects that have benefited from large-scale, elastic resource provisioning models. Furthermore, this study discusses the impact of cloud-enabled R&D projects in three domains: accelerators and AI/ML, ARM CPUs and columnar data analysis techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Physical Security Model Development of an Electrochemical Facility

Nuclear facilities in the U.S. and around the world face increasing challenges in meeting evolving physical security requirements while keeping costs reasonable. The addition of security features after a facility has been designed and without attention to optimization (the approach of the past) can easily lead to cost overruns. Instead, security should be considered at the beginning of the design process in order to provide robust, yet efficient physical security designs. The purpose of this work is to demonstrate how modeling and simulation can be used to optimize the design of physical protection systems. A suite of tools, including Scribe3D and Blender, were used to model a generic electrochemical reprocessing facility. Physical protection elements such as sensors, portal monitors, barriers, and guard forces were added to the model based on best practices for physical security. Two theft scenarios (an outsider attack and insider diversion) as well as a sabotage scenario were examined in order to optimize the security design. Security metrics are presented. This work fits into a larger Virtual Facility Distributed Test Bed 2020 Milestone in the Material Protection, Accounting, and Control Technologies (MPACT) program through the Department of Energy (DOE). The purpose of the milestone is to demonstrate how a series of experimental and modeling capabilities across the DOE complex provide the capabilities to demonstrate complete Safeguards and Security by Design (SSBD) for nuclear facilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Sabathani Community Center Solar + Battery Resilience Hub

To meet south Minneapolis, Minnesota's clean energy goals, the community exploring opportunities to transition Sabathani Community Center into a resilience hub to provide critical community services during power outages, including shelter and warmth or cooling, continued food distribution services, and more. The National Renewable Energy Laboratory, through the U.S. Department of Energy's Communities LEAP (Local Energy Action Program) pilot, worked with Sabathani to quantify the costs and benefits of installing stand-alone solar photovoltaics (PV) and PV paired with battery systems to reduce energy costs, avoid emissions, and improve resilience.

battery energy storage system↗
DOE OSTI2024

Minneapolis American Indian Center Solar + Battery Resilience Hub

To meet south Minneapolis, Minnesota's clean energy goals, the community exploring opportunities to transition Minneapolis American Indian Center (MAIC) into a resilience hub to provide critical community services during power outages, including shelter and warmth or cooling, continued food distribution services, and more. The National Renewable Energy Laboratory, through the U.S. Department of Energy's Communities LEAP (Local Energy Action Program) pilot, worked with MAIC to quantify the costs and benefits of installing stand-alone solar photovoltaics (PV) and PV paired with battery systems to reduce energy costs, avoid emissions, and improve resilience.

BESS↗
DOE OSTI2021

An Integrated Paradigm for the Management of Delivery Risk in Electricity Markets: From Batteries to Insurance and Beyond [Slides]

In wholesale electricity markets today, flexibility from a limited number of distributed energy resources (DERs) is offered daily, and the value of flexibility is not yet recognized for economic hedging of delivery risk. Under a three-year project funded by the ARPA-E PERFORM program, a collaborative team is working towards developing an integrated risk management framework that will leverage flexibility from distributed and bulk resources to cost-effectively and reliably manage delivery risk of intermittent resources. Two concepts are at the core of the proposed integrated risk management framework: (A) flexibility options, which are a novel type of options and enable wholesale electricity market participants to hedge uncertainty by buying flexibility. (B) DER flexibility scores, which provide a way for utilities or aggregators to classify assets in groups with different likelihood of delivering contracted flexibility. This report presentation will focus on the proposed ISO-product "flexibility options," which is complementary to ramp and other products being introduced by ISOs/RTOs to manage net load uncertainties. Participating resources with imbalance risk can buy flexibility options to hedge their production, whereas grid-connected resources that can provide physical flexibility can offer flexibility options. We will present basics of the formulation for a day-ahead ISO market that matches buyers and sellers of this hedge in coordination with existing capabilities to schedule energy and ancillary services, and outline how their settlements mitigate the impact of imbalance risk.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗
DOE OSTI2023

Convex Q-Learning in Continuous Time with Application to Dispatch of Distributed Energy Resources

Convex Q-learning is a recent approach to reinforcement learning, motivated by the possibility of a firmer theory for convergence, and the possibility of making use of greater a priori knowledge regarding policy or value function structure. This paper explores algorithm design in the continuous time domain, with a finite-horizon optimal control objective. The main contributions are (i) The new Q-ODE: a model-free characterization of the Hamilton-Jacobi-Bellman equation. (ii) A formulation of Convex Q-learning that avoids approximations appearing in prior work. The Bellman error used in the algorithm is defined by filtered measurements, which is necessary in the presence of measurement noise. (iii) Convex Q-learning with linear function approximation is a convex program. It is shown that the constraint region is bounded, subject to an exploration condition on the training input. (iv) The theory is illustrated in application to resource allocation for distributed energy resources, for which the theory is ideally suited.

Lu, Fan↗