Search NASA⌕ Search

SEARCH · Search NASA

Results for “Autonomous Power Controller”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Autonomous light management system for a window and method of controlling light transmission

An autonomous light management system for a window includes an electrochromic film stack comprising an electrochromic layer on a first transparent electrode, an ion storage layer on a second transparent electrode, and an electrolyte sandwiched between the ion storage and electrochromic layers. The electrochromic film stack exhibits a transmissive state or an absorptive state depending on charging or discharging of the electrochromic layer. The light management system further comprises an array of power units disposed on a front surface of the electrochromic film stack, where each power unit comprises at least one solar microcell. Collectively, the solar microcells cover an area no greater than about 6% of a total area of the front surface. The array of power units is configured to control the charging and discharging of the electrochromic layer, thereby manipulating light transmission through the electrochromic film stack.

Yoder, Mikayla A.↗
DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations Version 2.0

This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Segmented Energy Routing for a Modular AC/DC Hybrid System

This article presents a modular ac/dc system with both distributed and centralized power ports for energy router (ER) applications. In each module of the described system, photovoltaic (PV) power generation units, battery-type energy storage (ES) units, and critical loads are connected to the cascaded H-bridge (CHB)-organized medium-voltage (MV) dc links, with fully distributed low-voltage (LV) dc power ports. Copies of modules share the centralized load bus and interact with an MV ac grid in parallel. Hybrid power port (HPO) assigns flexibility to the system but makes energy routings a necessity for stable operation. In this article, a segmented energy management strategy for the HPO-ER is proposed. In terms of the grid-side power transferring, the system ratings are intentionally designed to match significant power imbalance. Focally, a segmented energy management strategy is proposed to realize fully autonomous energy routing involving MV ac grid, distributed PV generations, distributed battery storages, and LV load. The system is proven to be stable using the derived impedance-based model considering the interaction between power blocks. The feasibility of the topology and control strategy is also verified through software simulation, laboratorial hardware prototype experiment, and hardware-in-the-loop (HIL) emulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Real-time and Autonomous Water Quality Monitoring System Based on Remotely Operated Vehicle

Existing water quality monitoring systems near hydropower facilities are limited by the lack of mobility of the sensors’ carrier platform. Most systems use a buoy, a mounting fixture attached to a solid structure, or a human worker, which significantly limits the selection of the sampling sites and poses safety risks during data collection and equipment maintenance. To improve on this technology, we developed an autonomous water quality monitoring system that can operate in dangerous water environments near hydropower facilities for water sampling at multiple locations. The goal is to enable safe, timely, and comprehensive water-quality data collection; maximize power generation revenue with improved operational control; and reduce Federal Energy Regulatory Commission and state water quality monitoring costs for compliance. The system incorporates a remotely operated vehicle as the mobile monitoring platform, a dissolved oxygen sensor for monitoring water quality, a tether management system for automatically winding the tether, a solar mobile docking platform for suppling power to the ROV, and a web-based graphical user interface for data post-processing and visualization. In addition, preliminary field research are presented to demonstrate the system capabilities.

Salalila, Aljon L.↗
DOE OSTI2021

Precision cooking system

The present invention comprises a precision cooking oven that utilizes laser sheets to cook food, thus creating homogeneously heated and uniformly seared food bodies and surfaces. Laser sheets move back and forth evenly injecting heat into items being cooked. All food cold or hot areas can be eliminated since intersecting laser lines can be completely projected on and accommodate an item's exterior surfaces. Items with non-uniform cross-sections and properties can be cooked uniformly by controlling the exact amount of energy projected into differing sections of the food. The oven is also capable of cooking autonomously. Since laser sheets can be precisely controlled, cooking results can be very predictable once the boundary conditions for a thermal analysis are determined. The oven can detect the properties of the items to be cooked and thereafter compute the needed time and power to achieve the desired results stipulated by an oven operator.

Lee, Henry Yu-Heng↗
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Enhanced Control, Optimization, and Integration of Distributed Energy Applications (ECO-IDEA)

With support from the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy Laboratory (NREL) partnered with Xcel Energy, Schneider Electric, Varentec, and Electric Power Research Institute (EPRI) to meet the goals of the Enabling Extreme Real-Time Grid Integration of Solar Energy (ENERGISE) program. This project developed and validated an innovative data-enhanced hierarchical control architecture that enables the efficient, reliable, resilient, and secure operation of future distribution systems with a high penetration of distributed energy resources like solar energy. The architecture enables a hybrid control approach where a centralized control layer is complemented by distributed control algorithms for solar inverters and autonomous control of grid edge devices. It is fully interoperable and includes all the cybersecurity aspects necessary for reliable and secure system operation. The hybrid approach can seamlessly integrate multiple voltage-regulation technologies, both at central and grid-edge levels, which enables reliable and efficient system operation in the face of unpredictable conditions. The overarching goal of the Eco-Idea project is to develop, validate, and deploy a unique and innovative Data-Enhanced Hierarchical Control (DEHC) architecture that comprehensively addresses the formidable challenges associated with proliferation of high penetration of distributed PV such as reverse power flows, transients from variability of PV systems, feeder load balancing, and voltage stability. These issues are exposing the weaknesses of existing grid operations and controls - including, but not limited to, lack of grid situational awareness, heuristic and slow-acting control actions, latency of control for emergency situations, and points of failure in communications. The proposed architecture will comprehensively resolve the deficiencies of current operational settings - where monitoring and control solutions proposed across industry and academia may not be interoperable and may not coexist in the same system - and will enable an efficient, reliable, resilient, and secure operation of future distribution systems with penetration of solar energy well beyond current limits. The DEHC architecture was developed and validated rigorously through hardware-in-loop simulations in the laboratory environment and deployed on the field.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Control oriented model order reduction for the hydraulic system of an autonomous wheel loader

Control design for an autonomous wheel loader requires a high-fidelity and low-order dynamics model. The objective of order reduction is to decrease the number of states in the model while maintaining performance comparable to the original model. Of all the power components in a wheel loader, the model order reduction for steering and working hydraulic systems is most demanding due to its nonlinear and stiff dynamical nature. This paper describes a physics-inspired model order reduction method that can reduce the model order by close to thirty percent. It is achieved by discarding orders with fast dynamics and consolidating multiple states into less new states. Furthermore, this method can also be extended to other types of off-road vehicles such as excavators, bulldozers, etc. Simulation results demonstrate that the reduced-order model exhibits very similar performance to the full-order model under typical operating conditions of wheel loaders, with an output error of less than six percent.

42 ENGINEERING↗
DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Future Vision for Autonomous Ocean Observations

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass; and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as EGO for the emerging glider operations should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Stability and Performance of an Undersea Kite Operating in a Turbulent Flow Field

In this paper, we examine the effects of flow disturbances resulting from turbulence on the dynamic behavior of an underwater energy-harvesting kite system that executes periodic figure-8 flight. Due to the periodic nature of the kite’s operation, we begin by assessing orbital stability using the Floquet analysis and stroboscopic intersection analysis of a Poincaré section, with the former analysis performed on a simplified “unifoil” model and the latter performed on a six-degree-of-freedom (6-DOF)/flexible tether model. With periodic stability established, a frequency-domain analysis based on a linearization about the kite’s path is used to predict the quality of flight path tracking as a function of the turbulence frequency. To validate the accuracy of these simulation-based predictions under flow disturbances, we compare the predictions of the kite’s behavior against the results of small-scale tow testing experiments performed in a controlled pool environment.

13 HYDRO ENERGY↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. The effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2024

Polarimetry-Enhanced Imaging towards Autonomous Solar Field and Receiver Inspections

During the typical operation of a Concentrating Solar Power (CSP) plant, a large portion of the energy (~45%) can be lost due to various imperfect conditions, such as blocking, shading, mirror soiling, tracking and canting errors, etc. It is necessary to develop efficient and effective field inspection technology to optically survey and characterize a CSP field, which can be used as an input for autonomous control, maintenance scheduling and spot repair whenever necessary to maximize the overall efficiency of the plant. In this project, We aim to apply polarimetric imaging for CSP collector and receiver inspection and develop polarimetric drone cameras (via integrating polarimetric imagers onto drones) for autonomous field inspection in CSP plants.

14 SOLAR ENERGY↗
DOE OSTI2022

Regulatory Considerations for Nuclear Energy Applications of Digital Twin Technologies

Digital twins (DTs) in complex industrial and engineering applications have potential benefits that include increased operational efficiencies, enhanced safety and reliability, improved security engineering, reduced errors, faster information sharing, and better predictions. The interest in DT technologies continues to grow, and many of these advanced technologies are expected to experience rapid and wide industry adoption in the near future. Some of the potential application areas for DTs in the nuclear industry are design, licensing, plant construction, training simulators, predictive operations and maintenance, autonomous operation and control, failure and degradation prediction, physical protection modeling and simulation, and safety and reliability analyses. The Office of Nuclear Regulatory Research at the U.S. Nuclear Regulatory Commission (NRC) has initiated a future-focused research project to assess the regulatory viability of DTs for nuclear power plants and other NRC-regulated activities, such as fuel cycle facilities and operations. This report explores the potential impact of DT technologies in nuclear applications on NRC-regulated activities of interest. This report describes a nuclear DT system and its capabilities for nuclear power plant applications, followed by identification and discussion of some regulated activities that merit special consideration and present opportunities in implementing DT-enabling technologies and capabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

The Future of Renewable Energy Transmission: An Autonomous Energy Grid

The drastic price reduction in variable renewable energy, such as wind and solar, coupled with the ease of use of smart technologies at the consumer level, is driving dramatic changes to the power system that will significantly transform how power is made, delivered, and used. Distributed energy resources (DERs)—which can include solar photovoltaic (PV), fuel cells, microturbines, gensets, distributed energy storage (e.g., batteries, ice storage), and new loads (e.g., electric vehicles (EVs), light-emitting diode (LED) lighting, smart appliances, and electric heat pumps)—are being added to electric grids and causing bidirectional power flows and voltage fluctuations that can impact optimal control and system operation. Residential solar installations, customer battery systems, and EVs are all seeing rapid increases in deployments. With DER seeing such increased use, it is not unreasonable to imagine a residential electricity customer having at least five controllable DERs. In future electric grids, as more DERs are integrated, the number of active control points will be too much for current control approaches to effectively manage.

30 DIRECT ENERGY CONVERSION↗