Search NASA⌕ Search

SEARCH · Search NASA

Results for “networked control systems”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Impact of Blockchain Delay on Grid-Tied Solar Inverter Performance

This paper investigates the impact of the delay resulting from a blockchain, a promising security measure, for a hierarchical control system of inverters connected to the grid. The blockchain communication network is designed at the secondary control layer for resilience against cyberattacks. To represent the latency in the communication channel, a model is developed based on the complexity of the blockchain framework. Taking this model into account, this work evaluates the plant’s performance subject to communication delays, introduced by the blockchain, among the hierarchical control agents. In addition, this article considers an optimal model-based control strategy that performs the system’s internal control loop. The work shows that the blockchain’s delay size influences the convergence of the power supplied by the inverter to the reference at the point of common coupling. In the results section, real-time simulations on OPAL-RT are performed to test the resilience of two parallel inverters with increasing blockchain complexity.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Automated Realistic Testbed Synthesis for Power System Communication Networks based on Graph Metrics

Communication networks are integral to modern power grid operations and are becoming increasingly critical as grid dynamics speed up and as more controls become closed-loop in form. Focusing on the interdependence between the physical grid and the communication system, we identify several key characteristics and typical graph properties based on analysis of a real communication system for a power grid. Moreover, an automated process was provided for synthetic testbed in the NS-3 simulator for the power system test case, and its network characteristics have been further derived for power system monitoring and control applications

Graph Analysis, Synthetic Testbed, communication n↗
DOE OSTI2024

Modernizing Fermilab's Accelerator Control Hardware

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available.The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. The ACORN project is planning to replace Fermilab s obsolete CAMAC crate-and-card controls hardware with modern MicroTCA hardware. There are over 2,000 CAMAC cards and over 250 CAMAC crates serving various functions in Fermilab s control system. We will review the existing CAMAC hardware and provide updates on the status of the ACORN project, which includes the conceptual design of the MicroTCA replacement hardware and software tools for supporting the installation of hundreds of MicroTCA crates.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Experimental demonstration of a data-driven control system for subcritical nuclear facility

Here this paper presents an experimental demonstration of a data-driven control system (DCS) designed for the MIT Graphite Exponential Pile (MGEP). The DCS aims to regulate the neutron flux profile such that symmetry is preserved. Neutron flux perturbations are introduced into the MGEP to test the DCS's capabilities by the movement of an initiating control rod (ICR). To realize this functionality, a control system that relies on an artificial neural network (ANN) was developed, and then demonstrated on the MGEP. A Helium-3 ( 3 He) neutron detector and dual control rods, including their moving mechanisms, were fabricated. The perturbed flux profile was monitored by the moving neutron detector. The prediction accuracy of the neural network (NN) was examined and the DCS response was presented. Our results show that neural network regression model trained by experimental data can achieve a prediction error of less than 2.5 cm with a 95% confidence interval. The demonstration experiment also shows that a perturbation of the ICR can be captured by the control system and flux symmetry can be maintained within 1% after the response of the responding control rod (RCR).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Modernizing Fermilab s Control Hardware

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available. The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. The ACORN project is planning to replace Fermilab’s obsolete CAMAC crate-and-card controls hardware with modern MicroTCA hardware. There are over 2,000 CAMAC cards and over 250 CAMAC crates serving various functions in Fermilab’s control system. We will present an overview of the existing CAMAC hardware and the proposed MicroTCA replacement plan.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Hybrid Symbolic-Numerical Modeling and Parametric Stability Analysis of DC–AC Power Systems

Hybrid DC-AC power systems integrating diverse inverter-based resources (IBRs) and multi-terminal high-voltage direct current (MTDC) networks represent a promising architecture for future power grids, while introducing challenges for modeling, stability analysis, and control design. This paper develops a hybrid symbolic-numerical modeling framework and tool to characterize the parametric small-signal stability of DC-AC coupled power systems. The proposed approach constructs parametric state-space models to enable efficient representation of system dynamics under varying control parameters and network configurations, with target parameters retained as symbolic variables and the remainder treated numerically. The stability analysis framework covers eigenvalue, sensitivity, and stability boundary and region characterization. Enhanced linear matrix inequality (LMI) techniques are proposed to directly certify small-signal stability over regions of parameter space while also reducing the conservativeness and computational burden. The resulting tools and frameworks enable rapid parametric model construction across diverse grid conditions, thereby facilitating stability-informed control and operation in complex DC–AC power systems.

DC–AC power systems↗
DOE OSTI2021

Electricity and Gas IDS Dataset

The following dataset was collected from a set of cybersecurity experiments conducted in an Electricity and Natural Gas environment. The architecture was instantiated within the powerNET testbed at Pacific Northwest National Laboratory, and is comprised of both simulated components and hardware-in-the-loop devices. The test environment consisted of a substation and control center network representative of electrical systems. In addition, it also contained a compressor station, and an odorizer and pressure regulation station representative of oil and natural gas systems. The various devices on the electrical and gas systems were organized into multiple networks to mimic real-world deployments. There were 14 testing scenarios overall that covered a wide variety of cybersecurity and infrastructure events.

Industrial Control↗
DOE OSTI2021

Electricity and Gas IDS Dataset

The following dataset was collected from a set of cybersecurity experiments conducted in an Electricity and Natural Gas environment. The architecture was instantiated within the powerNET testbed at Pacific Northwest National Laboratory, and is comprised of both simulated components and hardware-in-the-loop devices. The test environment consisted of a substation and control center network representative of electrical systems. In addition, it also contained a compressor station, and an odorizer and pressure regulation station representative of oil and natural gas systems. The various devices on the electrical and gas systems were organized into multiple networks to mimic real-world deployments. There were 14 testing scenarios overall that covered a wide variety of cybersecurity and infrastructure events.

Industrial Control↗
DOE OSTI2020

Considerations for AMI-Based Operations for Distribution Feeders

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

AI-Science for Performance Optimization and Diagnosis of Science Instrument Federations

Next generation of science workflows are expected to be executed over complex federations composed of supercomputers, science instruments, storage systems and networks, with new additions of the edge and cloud systems and services. The sheer complexity of these multi-domain federations makes it hard to manage them and optimize their performance, as small impedance mismatches (that can dynamically develop between systems) could drastically degrade the entire federation performance. Recent proliferation of Software Defined Everything (SDX) technologies combined with containerization frameworks provide custom instruments that can monitor and collect critical measurements at various levels to support diagnoses and performance optimization; but their data too enormous for human operators and analysts to process and generate decisions. Machine Learning (ML) methods that extract critical parameters, relationships and trends from the data offer general solutions. Artificial Intelligence (AI) and ML methods must be custom-developed for these problems based on solid, rigorous foundations, since black-box approaches are often ineffective and unsound.We propose to develop comprehensive AI-Science for the performance of science federations to (i) monitor and control storage, networks, experiments, and computing systems across multiple domains via softwarization layers, at speeds and scales orders of magnitude superior to current practice, (ii) optimally realize and orchestrate complex workflows with high performance by using dynamic state and performance estimation methods, and (iii) aggregate measurements across sites and time to develop infrastructure-level profiles, optimizations and diagnoses using AI-Science based on foundational principles from ML, game theory, and information fusion areas.

Rao, Nageswara↗
DOE OSTI2020

Grid-Forming Frequency Shaping Control for Low-Inertia Power Systems

As power systems transit to a state of high renewable penetration, little or no presence of synchronous generators makes the prerequisite of well-regulated frequency for grid-following inverters unrealistic. As such, there is a trend to resort to grid-forming inverters which set frequency directly. We propose a novel grid-forming frequency shaping control that is able to shape the aggregate system frequency dynamics into a first-order one with the desired steady-state frequency deviation and Rate of Change of Frequency (RoCoF) after a sudden power imbalance. The no overshoot property resulting from the first-order dynamics allows the system frequency to monotonically move towards its new steady-state without experiencing frequency Nadir, which largely improves frequency security. We prove that our grid-forming frequency-shaping control renders the system internally stable under mild assumptions. The performance of the proposed control is verified via numerical simulations on a modified Icelandic Power Network test case.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Sliding Mode Network Perimeter Control

Urban traffic congestion is a chronic problem faced by many cities in the US and worldwide. It results in inefficient infrastructure use as well as increased vehicle fuel consumption and emission levels. Congestion is intertwined with delay, as road users waste precious hours on the road, which in turn reduces productivity. Researchers have developed, and continue to design, tools and systems to alleviate this problem. Network perimeter control is one such tool that has been studied extensively. It attempts to control the flow of vehicles entering a protected area to ensure that the congested regime predetermined by the Network Fundamental Diagram (NFD) is not reached. In this paper, a method derived from sliding mode control theory is presented. Its main advantages over proportional-integral controllers include (1) minimal tuning, (2) no linearization of the governing equations, (3) no assumptions with regard to the shape of the NFD, and (4) ability to handle various demand profiles without the need to retune the controller. A sliding mode controller was implemented and tested on a congested grid network. The results show that the proposed controller produces network-wide delay savings and disperses congestion effectively.

42 ENGINEERING↗
DOE OSTI2020

Cyber-Physical Smart Light Control System Integration with Smart Grid using Zigbee

This paper presents a hardware-in-the-loop cyber-physical system architecture design to monitor and control smart lights connected to the active distribution grid. The architecture uses Zigbee-based (IEEE 802.15.4) wireless sensor networks and publish-subscribe architecture to exchange monitoring and control signals between smart-light actuators (SLAs) and a smart-light central controller (SLCC). Each SLA integrated into a smart light consists of a Zigbee-based endpoint module to send and receive signals to and from the SLCC. The SLCC consists of a Zigbee-based coordinator module, which further exchanges the monitoring and control signals with the active distribution management system over the TCP/IP communication network. The monitoring signals from the SLAs include light status, brightness level, voltage, current, and power data, whereas, the control signals to the SLAs include light intensity, turn ON, turn OFF, standby, and default settings. We have used our existing hardware-in-the-loop (HIL) cyber-physical system (CPS) security SCADA testbed to process signals received from the SLCC and respond suitable control signals based on the smart light schedule requirements, system operation, and active distribution grid dynamic characteristics. We have integrated the proposed cyber-physical smart light control system (CPSLCS) testbed to our existing HIL CPS SCADA testbed. We use the integrated testbed to demonstrate the efficacy of the proposed algorithm by real-time performance and latency between the SLCC and SLAs. The experiments demonstrated significant results by 100% realtime performance and low latency while exchanging data between the SLCC and SLAs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Performance Evaluation of Distributed Energy Resource Management Algorithm in Large Distribution Networks

This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale distribution system of 11,000 nodes, the DERMS software controller, and 90 power hardware photovoltaics (PVs) and battery inverters. The applied DERMS algorithm is designed based on a realtime optimal power flow algorithm and implemented with acceleration design that performs fast dispatch of simulated PVs and real physical hardware DER devices every 4 seconds.

DERMS↗
DOE OSTI2023

Tuning Phase Lock Loop Controller of Grid Following Inverters by Reinforcement Learning to Support Networked Microgrid Operations

The dynamic operation of networked microgrids leads to varying topological configurations and generator commitments and dispatches. These variations correspond to systems with different electrical characteristics. The fixed control gains of high-speed power electronic devices may result in undesirable system performance when the electrical characteristics change significantly. As such, it is necessary to tune the control gains of power electronics devices to adapt to the changing system characteristics. This paper uses observer-based reinforcement learning to automatically tune the proportional-integral (PI) gains of phase lock loop (PLL) controller of grid-following (GFL) inverters to adapt to the changing system strengths, that would be seen in networked microgrid operations. Simulation results using an operational electric distribution system, modeled as networked microgrids, are presented to demonstrate the need and effectiveness of the proposed adaptive controls.

networked microgrids, reinforcement learning, grid↗
DOE OSTI2022

Strategy for Modernizing a 40-Year-Old Accelerator Control System

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available and software that uses obsolete frameworks. The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. The project team is evaluating three design concepts, and the future deployment of artificial intelligence capabilities for accelerator operations is an important consideration. An overview of the ACORN Project will be presented, including R&D used for evaluating the conceptual designs in the context of requirements for future accelerator operations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Introduction and Status of Fermilab's ACORN Project

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available and software that uses obsolete frameworks. The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. An overview of the ACORN Project and a summary of recent research and development activities will be presented.

43 PARTICLE ACCELERATORS↗