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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Here, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between the distributions corresponding to different fault location hypotheses associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyber-physical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations.

42 ENGINEERING↗
DOE OSTI2018

Operational Experience With the GEM Detector Assembly Lines for the CMS Forward Muon Upgrade

The CMS Collaboration has been creating large-area triple-gas electron multiplier (GEM) detectors to be installed in the muon Endcap regions of the CMS experiment in 2019 to maintain forward muon trigger and tracking performance at the High-Luminosity upgrade of the Large Hadron Collider (LHC); 10 preproduction detectors were built at CERN to commission the first assembly line and the quality controls (QCs). These were installed in the CMS detector in early 2017 and participated in the 2017 LHC run. The collaboration has prepared several additional assembly and QC lines for distributed mass production of 160 GEM detectors at various sites worldwide. In 2017, these additional production sites have optimized construction techniques and QC procedures and validated them against common specifications by constructing additional preproduction detectors. Using the specific experience from one production site as an example, we report on how the QCs make use of independent hardware and trained personnel to ensure fast and reliable production. Preliminary results on the construction status of CMS GEM detectors are presented with details of the assembly sites involvement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

VOLTTRON/econ-dispatch

Work space for in development Economic Dispatch Application. Multi-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.

Katipamula, Srinivas↗
DOE OSTI2025

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An operation verification strategy against network attack of DCS in nuclear power plant - 323

Digital Instrumentation and control (I and C) system serves as the 'senses and nervous system' of a nuclear power plant (NPP). It plays an important role in the safe and economic operation in the NPPs. Digital I and C system has a series of advantages compared with analogue ones, but the introduction of the operation system platform, the application software, and the network communication structure are causing security risk to the power plant. Different kinds of procedures have already been adopted against these risks such as the communication isolation, but the security attacks still occur from time to time in the industrial fields around the world. This paper presents two computer security methods based on the thought of software verification and validation with step-by-step operation identification. First, three scenarios of security attack are proposed according to the structure of a distributed control system (DCS). Then a method with two network bypasses and a security computer are adopted to obtain the operation commands, the actuation signal, and the operation feedback in case of the first two scenarios by identifying the consistency of the obtained data. Furthermore, the method is optimized by combining the operation procedure and the camera shot to identify the anomaly of the information flow, thus to improve the effectiveness against the computer security issues. In the end, the influence and feasibility of this method is discussed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2018

Robust Operation of Soft Open Points in Active Distribution Networks with High Penetration of Photovoltaic Integration

Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built to tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Here, case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2014

SU-E-J-102: Separation of Metabolic Supply and Demand: From Power Grid Economics to Cancer Metabolism

Purpose: To study a new model of glucose metabolism which is primarily governed by the timescale of the energetic demand and not by the oxygen level, and its implication on cancer metabolism (Warburg effect) Methods: 1) Metabolic profiling of membrane transporters activity in several cell lines, which represent the spectrum from normal breast epithelium to aggressive, metastatic cancer, using Seahorse XF reader.2) Spatial localization of oxidative and non-oxidative metabolic components using immunocytochemical imaging of the glycolytic ATP-producing enzyme, pyruvate kinase and mitochondria. 3) Finite element simulations of coupled partial differential equations using COMSOL and MATLAB. Results: Inhibition or activation of pumps on the cell membrane led to reduction or increase in aerobic glycolysis, respectively, while oxidative phosphorylation remained unchanged. These results were consistent with computational simulations of changes in short-timescale demand for energy by cell membrane processes. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. These predictions were confirmed experimentally. Conclusion: The results in this work support a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Similar to power grid economics, optimal metabolic control requires the two pathways, even in normoxic conditions, to match two different types of energy demands. Cells use aerobic metabolism to meet baseline, steady energy demand and glycolytic metabolism to meet short-timescale energy demands, mainly from membrane transport activities, even in the presence of oxygen. This model provides a mechanism for the origin of the Warburg effect in cancer cells. Here, the Warburg effect emerges during carcinogenesis is a physiological response to an increase in energy demands from membrane transporters, required for cell division, growth, and migration. This work is supported by the NIH Physical Sciences in Oncology Center grant 1U54CA143970-03 and NIH R01 CA077575-10.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. Furthermore, there is still a lack of in-depth quantitative studies on their approximation levels to the true optimality, especially in the building energy domain. To fill in the gap, this paper provides a numerical framework that enables the evaluation of the optimality levels of different controllers for building energy systems. This framework is then used to comprehensively compare the optimal control performance of both MPC and DRL controllers with given computation budgets for a single zone fan coil unit system. Note the optimality is estimated based on a user-specific selection of trade-off weights among energy costs, thermal comfort and control slew rates. Compared with the best optimality we can find through expensive optimization simulations, the best DRL agent can maximally approximate the optimality by 96.54%, which outperforms the best MPC whose optimality level is 90.11%. However, due to the stochasticity, the DRL agent is only expected to approximate the optimality by 90.42%, which is almost equivalent to the best MPC. Except for Proximal Policy Optimization (PPO), all DRL agents can have a better approximation to the optimality than the best MPC, and are expected to have better approximation than the MPC with a prediction horizon of 32 steps (15 min per step). In terms of reducing energy cost and thermal discomfort, MPC can outperform the rule-based control (RBC) by 18.47%–25.44%. DRL can be expected to outperform RBC by 18.95%–25.65% ,and the best DRL control policy can outperform RBC by 20.29%–29.72%. Although the comparison of the optimality level is performed in a perfect setting, e.g., MPC assumes perfect models, and DRL assumes a perfect offline training process and online deployment process, this can shed insight on their capabilities of approximating to the original dynamic programming problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2011

ANALYSIS TOOLS FOR SIZING AND PLACEMENT OF ENERGY STORAGE IN GRID APPLICATIONS

The purpose of this report was to review pertinent literature and studies to identify current state-of-the-art models and analytical tools that optimize the siting, sizing, and economic value of energy storage in a smart grid infrastructure. In recent decades, research and development has significantly improved the cost and reliability of energy storage systems. However, a relatively small percentage of that work has focused on engineering tools for integrating energy storage into existing or future electric grids. This literature review revealed that only a small number of software tools exist, and that those tools only partially address the needs for placement, sizing, and overall control strategies of stationary energy storage within a smart grid infrastructure. None of the tools comprehensively captures the benefits of energy storage, which would reveal all of the potential values. None of the tools or models provides optimization features that identify optimal placement and sizing options within a transmission or distribution system context. This review identifies a need for tool development to fill the gap in the grid analytics and provides some recommendations of guiding principles for advancing the analytical capabilities needed for the engineering and grid planning communities.

energy storage↗
DOE OSTI2025

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗
DOE OSTI2017

Kokhanok Mini-grid Business Case

A business case analysis was performed for the Village of Kokhanok. The business case analysis evaluated the optimal case from the technical analysis performed by the National Renewable Energy. The optimal case provided for repairing the two Vestas 17 (90 kW) wind turbine controllers and added electric thermal stoves and a battery. The project cost 0.5 million. The direct cost of electricity would likely decline from 0.69/kWh to 0.39/kWh. The direct costs don’t include administrative and distribution costs. The repair of controller and the addition of electric stoves reduced fuel consumption by 63% or approximately 22,000 gallons. The reduction in cost provides an opportunity for the Kokhanok Village Council to obtain financing through grants and loans to install renewable energy and reduce diesel fuel consumption to the cooperative

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Effects of Pore Size on Na/Ca Ion Selectivity Using Flow Through Electrode Capacitive Deionization

In flow through electrode capacitive deionization (fte-CDI), low salinity brackish water flows through two porous carbon electrodes. When an electrical potential difference is applied over the electrodes, ions migrate towards micropores, cleaning the water. Ion selectivity can be controlled by taking advantage of charge and ionic radius differences as well as the applied potential and pore size of the electrodes. The research outlined in this paper consists primarily of running fte-CDI cells with electrodes of varying pore size distributions to experimentally determine the parameters for optimal total salt removal and sodium/calcium ion selectivity. Five fte-CDI cells of different activation were fabricated using microporous hierarchical carbon aerogel materials (HCAMs) as electrodes. For each cell, cyclic voltammetry using 20 mM NaCl solution and 10 mM CaCl2 solution was performed at a scan rate of 0.5, 0.75, and 1 mV/s with a potential window from -0.8 V to +0.8 V. The same pure salts were desalinated in hourly charge/discharge cycles at ±1 V. A mixture of 5 mM NaCl and 2.5 mM CaCl2 was desalinated at 0.6, 0.8, 1.0, and 1.2 V. The collected charge and discharge streams were analyzed with ion chromatography (IC). The IC data for the two least activated cells showed minimal calcium adsorption compared to sodium. All cells adsorbed sodium, regardless of activation, while only highly activated cells removed calcium. This data indicates a tradeoff between more total salt removed at high voltages and selectivity of sodium over calcium at low voltages. Future research with nitrogen porosimetry could provide a quantitative value for the optimal pore size distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multiphase Optimal and Non-Singular Power Flow by Successive Linear Approximations: Preprint

We propose an optimal power flow method for multiphase power systems. The method works for both radial and meshed networks, and is able to accommodate different types of load/source connections such as wye, delta, etc. Moreover, the method generates a sequence of non-singular points in the electrical state space and a corresponding sequence of power injections, which can be used in real-time control settings. Under certain conditions, the sequences attain the local minimum. The method has been tested using several typical networks, including the IEEE 37-bus and 123-bus test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Southwest Wind Power R&D Test Site Development at the National Wind Technology Center (CRADA CRD-12-00472 Final Report)

Southwest Windpower, Inc. (SWWP) has been designing and distributing small wind turbines for more than 22 years and is the recognized global leader in the design, manufacturing and distribution of small wind systems (400-3000 watts). The company has been a pioneer in the development of wind technology and has built and shipped more than 170,000 wind turbines to over 120 countries worldwide. Headquartered in Flagstaff AZ, SWWP has sales representatives in over 88 countries. Applications for SWWP systems include residential homes, commercial properties, micro grids, remote cabins, telecom transmitters, offshore platforms, water pumping and sailboats. In addition, U.S. Department of Defense uses SWWP’s products in Forward Operating Bases (FOB’s), USGS uses them for remote monitoring of glacier movements and the CIA uses them to provide power seismic monitoring. Today, SWWP plans development of new technologies to address distributed energy market needs and become even more aggressive in international markets. This strategy includes extensive Research, Development, Demonstration & Deployment (RDD&D) activities to improve existing production line into more simple, reliable, and cost-effective wind turbine systems. Important part of such activities is the field testing of the new systems, which should provide: (i) validation of the reliable operation of hardware and software; (ii) validation of numerical models of the system and its components; (iii) field comparison of various control and optimization strategies; (iv) customized reliability testing; (v) customized monitoring and analysis testing; and (vi) IEC certification testing (vii) filed demonstration of system performance and reliability. Such field testing facility should encompass multiple towers and appropriate data acquisition systems. SWWP is exploring to move part of the engineering department to Colorado, and execute its RDD&D strategies in this new location. Partnership with NREL will provide great insights into SWWP’s RDD&D processes and more efficient commercialization by utilizing NWTC as the field testing site, and working close with NREL personnel. NWTC is ideally suited to strain the design. NREL is very experienced with customized and IEC testing. During this project, Southwest Windpower aims to improve the value proposition of distributed renewable energy, and make it a competitive choice in the energy markets. As of today, more then 170,000 small wind turbines, manufactured in the U.S., are installed in more then 180 countries. With the improved value proposition, Southwest Windpower wants to create and address new market needs, substantially increase its sales domestically and internationally, which should have positive impact on the creation of American jobs, competitiveness of U.S. economy, export or U.S. products, and the use of renewable energy.

17 WIND ENERGY↗
DOE OSTI2019

Coordinated Model Predictive Control on Multi-Lane Roads

There are significant economic, environmental, energy, and other societal costs incurred by the road transportation sector. With the advent and penetration of connected and autonomous vehicles there are vast opportunities to optimize the control of individual vehicles for reducing energy consumption and increasing traffic flow. Model predictive control is a useful tool to achieve such goals, while accommodating ego-centric objectives typical of heterogeneous traffic and explicitly enforcing collision and other constraints. In this paper, we describe a multi-agent distributed maneuver planning and lane selection model predictive controller that includes an information sharing and coordination scheme. The energy saving potential of the proposed coordination scheme is then evaluated via large scale microscopic traffic simulations considering different penetration levels of connected and automated vehicles.

Goulet, Nathan↗
DOE OSTI2015

Paddle-based rotating-shield brachytherapy

Purpose: The authors present a novel paddle-based rotating-shield brachytherapy (P-RSBT) method, whose radiation-attenuating shields are formed with a multileaf collimator (MLC), consisting of retractable paddles, to achieve intensity modulation in high-dose-rate brachytherapy. Methods: Five cervical cancer patients using an intrauterine tandem applicator were considered to assess the potential benefit of the P-RSBT method. The P-RSBT source used was a 50 kV electronic brachytherapy source (Xoft Axxent™). The paddles can be retracted independently to form multiple emission windows around the source for radiation delivery. The MLC was assumed to be rotatable. P-RSBT treatment plans were generated using the asymmetric dose–volume optimization with smoothness control method [Liu et al., Med. Phys. 41(11), 111709 (11pp.) (2014)] with a delivery time constraint, different paddle sizes, and different rotation strides. The number of treatment fractions (fx) was assumed to be five. As brachytherapy is delivered as a boost for cervical cancer, the dose distribution for each case includes the dose from external beam radiotherapy as well, which is 45 Gy in 25 fx. The high-risk clinical target volume (HR-CTV) doses were escalated until the minimum dose to the hottest 2 cm{sup 3} (D{sub 2cm{sup 3}}) of either the rectum, sigmoid colon, or bladder reached their tolerance doses of 75, 75, and 90 Gy{sub 3}, respectively, expressed as equivalent doses in 2 Gy fractions (EQD2 with α/β = 3 Gy). Results: P-RSBT outperformed the two other RSBT delivery techniques, single-shield RSBT (S-RSBT) and dynamic-shield RSBT (D-RSBT), with a properly selected paddle size. If the paddle size was angled at 60°, the average D{sub 90} increases for the delivery plans by P-RSBT on the five cases, compared to S-RSBT, were 2.2, 8.3, 12.6, 11.9, and 9.1 Gy{sub 10}, respectively, with delivery times of 10, 15, 20, 25, and 30 min/fx. The increases in HR-CTV D{sub 90}, compared to D-RSBT, were 16.6, 12.9, 7.2, 3.7, and 1.7 Gy{sub 10}, respectively. P-RSBT HR-CTV D{sub 90}-values were insensitive to the paddle size for paddles angled at less than 60°. Increasing the paddle angle from 5° to 60° resulted in only a 0.6 Gy{sub 10} decrease in HR-CTV D{sub 90} on average for five cases when the delivery times were set to 15 min/fx. The HR-CTV D{sub 90} decreased to 2.5 and 11.9 Gy{sub 10} with paddle angles of 90° and 120°, respectively. Conclusions: P-RSBT produces treatment plans that are dosimetrically and temporally superior to those of S-RSBT and D-RSBT, although P-RSBT systems may be more mechanically challenging to develop than S-RSBT or D-RSBT. A P-RSBT implementation with 4–6 shield paddles would be sufficient to outperform S-RSBT and D-RSBT if delivery times are constrained to less than 15 min/fx.

60 APPLIED LIFE SCIENCES↗