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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Computerized scheme for evaluating mammographic phantom images

Purpose: The authors developed a computer algorithm to automatically evaluate images of the American College of Radiology (ACR) mammography accreditation phantom. Methods: The developed algorithm consist of the edge detection of wax insert, nonuniformity correction of background, and correction for magnification and also calculate the cross-correlation coefficient by image matching technique. The algorithm additionally evaluates target shape for fibers, target contrast for speck groups, and target circularity for masses. To obtain an ideal template image without noise and spatial resolution loss, the wax insert containing the embedded test pattern was extracted from the phantom and radiographed. Two template images and ten test phantom images were prepared for this study. The results of evaluation using the algorithm outputs were compared with the averaged results of observer studies by six skilled observers. Results: In comparing the results from the algorithm outputs with the results of observers, the authors found that the computer outputs were well correlated with the evaluations by observers, and they indicate the quality of the phantom image. The correlation coefficients between results of observer studies and two outputs of computer algorithm, i.e., the cross-correlation coefficient by template matching and indices of target shape for fibers, were 0.89 (95% confidence interval, 0.82-0.93; hereinafter the same) and 0.85 (0.76-0.91). The correlation coefficients between observer's results and two outputs: the cross-correlation coefficient and indices of target contrast for speck groups, were 0.83 (0.79-0.86) and 0.85 (0.81-0.88) and between observer's results and two outputs: the cross-correlation coefficient and indices of target circularity for masses, were 0.90 (0.84-0.94) and 0.87 (0.77-0.92). Conclusions: Image evaluation using the ACR phantom is indispensable in quality control of a mammography system. The proposed algorithm is useful for quality control and image evaluation of mammography units.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration

This paper focuses on the critical load restoration problem in distribution systems following major outages. To provide fast online response and optimal sequential decision-making support, a reinforcement learning (RL) based approach is proposed to optimize the restoration. Due to the complexities stemming from the large policy search space, renewable uncertainty, and nonlinearity in a complex grid control problem, directly applying RL algorithms to train a satisfactory policy requires extensive tuning to be successful. To address this challenge, this paper leverages the curriculum learning (CL) technique to design a training curriculum involving a simpler steppingstone problem that guides the RL agent to learn to solve the original hard problem in a progressive and more effective manner. We demonstrate that compared with direct learning, CL facilitates controller training to achieve better performance. To study realistic scenarios where renewable forecasts used for decision-making are in general imperfect, the experiments compare the trained RL controllers against two model predictive controllers (MPCs) using renewable forecasts with different error levels and observe how these controllers can hedge against the uncertainty. Results show that RL controllers are less susceptible to forecast errors than the baseline MPCs and can provide a more reliable restoration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Controlled transitions between cupolets of chaotic systems

We present an efficient control scheme that stabilizes the unstable periodic orbits of a chaotic system. The resulting orbits are known as cupolets and collectively provide an important skeleton for the dynamical system. Cupolets exhibit the interesting property that a given sequence of controls will uniquely identify a cupolet, regardless of the system's initial state. This makes it possible to transition between cupolets, and thus unstable periodic orbits, simply by switching control sequences. We demonstrate that although these transitions require minimal controls, they may also involve significant chaotic transients unless carefully controlled. As a result, we present an effective technique that relies on Dijkstra's shortest path algorithm from algebraic graph theory to minimize the transients and also to induce certainty into the control of nonlinear systems, effectively providing an efficient algorithm for the steering and targeting of chaotic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Advanced control strategies for HVAC&R systems—An overview: Part II: Soft and fusion control

A chronological overview of the advanced control strategies for HVAC&R is presented. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and the fusion or hybrid of hard and soft control techniques. Part I focused on hardcontrol strategies; Part II focuses on soft and fusion control and some future directions in HVA&R research. This overview is not intended to be an exhaustive survey on this topic, and any omissions of other works is purely unintentional.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

U31: Vehicle Stability and Dynamics: Electronic Stability Control

A team led by NTRCI is working to improve the roll and yaw stability of heavy duty combination trucks through developing stability algorithms, assembling demonstration hardware, and investigating robust wireless communication. Modern electronic stability control (ESC) products automatically slow a vehicle rounding a corner too quickly or apply individual brakes when necessary to improve the steering characteristics of a vehicle. Air brake systems in North America provide no electronic communication between a tractor and semitrailer, limiting the degree to which control systems can be optimized. Prior research has demonstrated stability improvements where dynamic measurements and control commands are communicated between units of a vehicle. Three related activities were undertaken: (1) Develop an algorithm for the optimum yaw and roll control of a combination vehicle. Vehicle state parameters needed to control the vehicle and the proper brake response were determined. An integrated stability control for the tractor and semitrailer requires communication between the two units. Dynamic models were used to assess the algorithm. (2) Implement the ESC algorithm in the laboratory. Hardware components suitable for the harsh environment for measurement, sensor-to-controller communication, and semitrailer-to-tractor communication and brake actuation were specified and assembled as a working system. The goal was to collect the needed vehicle state information, transmit the information to the ESC system, and then actuate the brakes in response to controller commands. (3) Develop a wireless network with the data rate and reliability necessary to communicate dynamic signals for a vehicle stability control system. Adaptive connectivity-aware, multi-hop routing was selected because it can perform in the harsh environment where packet collisions and fading often will exist. The protocol is to give high priority to urgent messages.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System: Preprint

Frequency control from Photovoltaic (PV) plants has great potential to address the frequency response challenge of the power system with high renewable penetration. However, using model-based approaches to determine the optimal PV headroom reserve requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic one-day operation profile of the WECC system and demonstrates over 40% PV headroom saving compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2018

Cryogenic Frostpoint Hygrometer (CFH) Instrument Handbook

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Cryogenic Frostpoint Hygrometer (CFH) is a small, balloon-borne instrument that provides highly accurate measurements of water vapor in the atmosphere. The CFH, although highly modified, is based upon the National Oceanic and Atmospheric Administration (NOAA)/Climate Monitoring and Diagnostic Laboratory (CMDL) frostpoint hygrometer (FPH) that has been flown in Boulder, Colorado, since 1980. The CFH has a significantly greater sensitivity to water vapor than standard radiosondes, as it can measure the frostpoint or dewpoint temperatures at an accuracy better than 0.2 K corresponding to water volume mixing ratios accuracies of only a few parts per million. The main instrument part is a small mirror, which is cooled by a cryogen in order to be covered with a thin layer of water vapor condensate. A pair of photodiodes detects the condensation on the temperature-controlled mirror. The phase of the condensate is controlled by a force-freezing algorithm, allowing for clear interpretation of the dew point versus frostpoint. The replacement of analog electronics with a microprocessor, a feedback controller, and thermistor calibration have led to improved accuracy and performance of the CFH over its predecessors. Further characteristics like reduced power consumption and low instrument weight made the CFH a successful instrument to perform in situ balloon-borne measurements of water vapor in the upper troposphere and lower stratosphere. CFH measurements are now used worldwide to validate radiosonde, satellite, and ground-based profiler measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Imaging for dismantlement verification: information management and analysis algorithms

The level of detail discernible in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes. An image will almost certainly contain highly sensitive information, and storing a comparison image will almost certainly violate a cardinal principle of information barriers: that no sensitive information be stored in the system. To overcome this problem, some features of the image might be reduced to a few parameters suitable for definition as an attribute, which must be non-sensitive to be acceptable in an Information Barrier regime. However, this process must be performed with care. Features like the perimeter, area, and intensity of an object, for example, might reveal sensitive information. Any data-reduction technique must provide sufficient information to discriminate a real object from a spoofed or incorrect one, while avoiding disclosure (or storage) of any sensitive object qualities. Ultimately, algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We discuss the utility of imaging for arms control applications and present three image-based verification algorithms in this context. The algorithms reduce full image information to non-sensitive feature information, in a process that is intended to enable verification while eliminating the possibility of image reconstruction. The underlying images can be highly detailed, since they are dynamically generated behind an information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography. We study these algorithms in terms of technical performance in image analysis and application to an information barrier scheme.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Voltage-Load Sensitivity Matrix Based Demand Response for Voltage Control in High Solar Penetration Distribution Feeders

This paper presents a voltage-load sensitivity matrix (VLSM) based voltage control method to deploy demand response resources for controlling voltage in high solar penetration distribution feeders. The IEEE 123-bus system in OpenDSS is used for testing the performance of the preliminary VLSM-based voltage control approach. A load disaggregation process is applied to disaggregate the total load profile at the feeder head to each load nodes along the feeder so that loads are modeled at residential house level. Measured solar generation profiles are used in the simulation to model the impact of solar power on distribution feeder voltage profiles. Different case studies involving various PV penetration levels and installation locations have been performed. Simulation results show that the VLSM algorithm performance meets the voltage control requirements and is an effective voltage control strategy.

distribution system modeling↗
DOE OSTI2011

Report on the analysis of field data relating to the reliability of solar hot water systems.

Utilities are overseeing the installations of thousand of solar hot water (SHW) systems. Utility planners have begun to ask for quantitative measures of the expected lifetimes of these systems so that they can properly forecast their loads. This report, which augments a 2009 reliability analysis effort by Sandia National Laboratories (SNL), addresses this need. Additional reliability data have been collected, added to the existing database, and analyzed. The results are presented. Additionally, formal reliability theory is described, including the bathtub curve, which is the most common model to characterize the lifetime reliability character of systems, and for predicting failures in the field. Reliability theory is used to assess the SNL reliability database. This assessment shows that the database is heavily weighted with data that describe the reliability of SHW systems early in their lives, during the warranty period. But it contains few measured data to describe the ends of SHW systems lives. End-of-life data are the most critical ones to define sufficiently the reliability of SHW systems in order to answer the questions that the utilities pose. Several ideas are presented for collecting the required data, including photometric analysis of aerial photographs of installed collectors, statistical and neural network analysis of energy bills from solar homes, and the development of simple algorithms to allow conventional SHW controllers to announce system failures and record the details of the event, similar to how aircraft black box recorders perform. Some information is also presented about public expectations for the longevity of a SHW system, information that is useful in developing reliability goals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

The need for application-based adaptation of deformable image registration

Purpose: To utilize a deformable phantom to objectively evaluate the accuracy of 11 different deformable image registration (DIR) algorithms. Methods: The phantom represents an axial plane of the pelvic anatomy. Urethane plastic serves as the bony anatomy and urethane rubber with three levels of Hounsfield units (HU) is used to represent fat and organs, including the prostate. A plastic insert is placed into the phantom to simulate bladder filling. Nonradiopaque markers reside on the phantom surface. Optical camera images of these markers are used to measure the positions and determine the deformation from the bladder insert. Eleven different DIR algorithms are applied to the full and empty-bladder computed tomography images of the phantom (fixed and moving volumes, respectively) to calculate the deformation. The algorithms include those from MIM Software (MIM) and Velocity Medical Solutions (VEL) and nine different implementations from the deformable image registration and adaptive radiotherapy toolbox for Matlab. These algorithms warp one image to make it similar to another, but must utilize a method for regularization to avoid physically unrealistic deformation scenarios. The mean absolute difference (MAD) between the HUs at the marker locations on one image and the calculated location on the other serves as a metric to evaluate the balance between image similarity and regularization. To demonstrate the effect of regularization on registration accuracy, an additional beta version of MIM was created with a variable smoothness factor that controls the emphasis of the algorithm on regularization. The distance to agreement between the measured and calculated marker deformations is used to compare the overall spatial accuracy of the DIR algorithms. This overall spatial accuracy is also utilized to evaluate the phantom geometry and the ability of the phantom soft-tissue heterogeneity to represent patient data. To evaluate the ability of the DIR algorithms to accurately transfer anatomical contours, the rectum is delineated on both the fixed and moving images. A Dice similarity coefficient is then calculated between the contour on the fixed image and that transferred, via the calculated deformation, from the moving to the fixed image. Results: The phantom possesses sufficient soft-tissue heterogeneity to act as a proxy for patient data. Large discrepancies appear between the algorithms and the measured ground-truth deformation. VEL yields the smallest mean spatial error and a Dice coefficient of 0.90. MIM produces the lowest MAD value and the highest Dice coefficient of 0.96, but creates the largest spatial errors. Increasing the MIM smoothness factor above the default value improves the overall spatial accuracy, but the factor associated with the lowest mean error decreases the Dice coefficient to 0.85. Conclusions: Different applications of DIR require disparate balances between image similarity and regularization. A DIR algorithm that is optimized only for its ability to transfer anatomical contours will yield large deformation errors in homogeneous regions, which is problematic for dose mapping. For this reason, these algorithms must be tested for their overall spatial accuracy. The developed phantom is an objective tool for this purpose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques

Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A Secure Learning Control Strategy via Dynamic Camouflaging for Unknown Dynamical Systems under Attacks

This paper presents a secure reinforcement learning (RL) based control method for unknown linear time-invariant cyber-physical systems (CPSs) that are subjected to compositional attacks such as eavesdropping and covert attack. We consider the attack scenario where the attacker learns about the dynamic model during the exploration phase of the learning conducted by the designer to learn a linear quadratic regulator (LQR), and thereafter, use such information to conduct a covert attack on the dynamic system, which we refer to as doubly learning-based control and attack (DLCA) framework. We propose a dynamic camouflaging based attack-resilient reinforcement learning (ARRL) algorithm which can learn the desired optimal controller for the dynamic system, and at the same time, can inject sufficient misinformation in the estimation of system dynamics by the attacker. The algorithm is accompanied by theoretical guarantees and extensive numerical experiments on a consensus multi-agent system and on a benchmark power grid model.

Mukherjee, Sayak↗
DOE OSTI2025

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hamiltonian switching control of noisy bipartite qubit systems

Abstract We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental noise on qubits. We demonstrate the control for a central spin coupled to bath spins via isotropic Heisenberg interactions, and then make physical applications to the protection of quantum gates performed on superconducting transmon qubits coupling to environmental two-level-systems (TLSs) through dipole-dipole interactions, as well as on such qubits coupled to both TLSs and a Lindblad bath. The control field is classical and acts only on the system qubits. We use reinforcement learning with policy gradient to optimize the Hamiltonian switching control protocols, using a fidelity objective for specific target quantum gates. We use this approach to demonstrate effective suppression of both coherent and dissipative noise, with numerical studies achieving target gate implementations with fidelities over 0.9999 (four nines) in the majority of our test cases and showing improvement beyond this to values of 0.999 999 999 (nine nines) upon a subsequent optimization by GRadient Ascent Pulse Engineering (GRAPE). We analyze how the control depth, total evolution time, number of environmental TLS, and choice of optimization method affect the fidelity achieved by the optimal protocols and reveal some critical behaviors of bipartite control of quantum gates.

Physics↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗