Results for “Consensus” — Page 10

DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Investigation of Ammonia Carrier Materials for Next Generation Ammonia Dosing System - CRADA 334 (Abstract)

Lean-burn gasoline and diesel engines can offer substantially higher fuel efficiency, good driving performance, and reduced carbon dioxide emission compared to stoichiometric gasoline engines. Various catalyst technologies have been developed to remove the pollutants from these engines. For example, a three-way catalyst (TWC) is used to remove hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) from gasoline engines during the stoichiometric conditions. During the lean-burn conditions, a TWC or a diesel oxidation catalyst (DOC) is used to control HC and CO emissions. NOx is removed by either lean NOx trap catalyst (LNT) that can store NOx under lean conditions and reduce NOx under rich conditions, or selective catalytic reduction catalyst (SCR) that can selectively remove NOx with a reducing agent. Among the NOx reduction catalyst technologies, SCR offers a number of advantages, including excellent NOx reduction efficiency over a wide range of temperatures and overall lower system cost. In fact, the SCR technology using ammonia (NH3) as reductant has been proven effective and used commercially for the removal of NOx emissions from stationary sources since the 1970s. Currently, SCR is being used to meet the NOx emission standards for diesel engines in Europe and North America, and also being considered for meeting the future NOx emission standards for lean-burn gasoline engines. Because of the challenges associated with storage, handling and transportation of ammonia on a vehicle, aqueous urea solution (e.g., Diesel Exhaust Fluid, AdBlue) has been developed as ammonia storage compound for mobile applications. When the aqueous urea solution is sprayed into exhaust gas stream, urea is decomposed to release ammonia, which then reduces NOx over the downstream SCR catalyst. Although aqueous urea solution technology has enabled automakers and engine manufacturers to meet the current NOx emission standards, this process of releasing ammonia requires a hot exhaust gas and sufficient mixing, creating challenges for low temperature NOx emission control and aftertreatment system packaging. For these reasons, alternative technologies have been developed as ammonia sources (e.g., solid urea, ammonium carbamate, metal ammine chloride) during the past few years. These technologies promise more convenient handling and distribution of ammonia sources, and help maximize the low-temperature performance of SCR catalysts and reduce the overall system volume and weight. However, none of these alternative technologies can be successfully implemented without the industry consensus. Therefore, the USCAR SCR work group, which is comprised of representatives from GM, Ford, and Chrysler, has decided to investigate the potential alternative ammonia carriers, define common standard vehicle interfaces, and address personal and environmental safety concerns with part suppliers and chemical companies. Under this CRADA Project, USCAR and Battelle will investigate alternative ammonia carrier materials that are currently under development. Based on the data and information derived under the CRADA project, the USCAR SCR work group plans to build the consensus and make recommendations for the industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Investigation of Ammonia Carrier Materials for Next Generation Ammonia Dosing System - CRADA 334 (Abstract)

Lean-burn gasoline and diesel engines can offer substantially higher fuel efficiency, good driving performance, and reduced carbon dioxide emission compared to stoichiometric gasoline engines. Various catalyst technologies have been developed to remove the pollutants from these engines. For example, a three-way catalyst (TWC) is used to remove hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) from gasoline engines during the stoichiometric conditions. During the lean-burn conditions, a TWC or a diesel oxidation catalyst (DOC) is used to control HC and CO emissions. NOx is removed by either lean NOx trap catalyst (LNT) that can store NOx under lean conditions and reduce NOx under rich conditions, or selective catalytic reduction catalyst (SCR) that can selectively remove NOx with a reducing agent. Among the NOx reduction catalyst technologies, SCR offers a number of advantages, including excellent NOx reduction efficiency over a wide range of temperatures and overall lower system cost. In fact, the SCR technology using ammonia (NH3) as reductant has been proven effective and used commercially for the removal of NOx emissions from stationary sources since the 1970s. Currently, SCR is being used to meet the NOx emission standards for diesel engines in Europe and North America, and also being considered for meeting the future NOx emission standards for lean-burn gasoline engines. Because of the challenges associated with storage, handling and transportation of ammonia on a vehicle, aqueous urea solution (e.g., Diesel Exhaust Fluid, AdBlue) has been developed as ammonia storage compound for mobile applications. When the aqueous urea solution is sprayed into exhaust gas stream, urea is decomposed to release ammonia, which then reduces NOx over the downstream SCR catalyst. Although aqueous urea solution technology has enabled automakers and engine manufacturers to meet the current NOx emission standards, this process of releasing ammonia requires a hot exhaust gas and sufficient mixing, creating challenges for low temperature NOx emission control and aftertreatment system packaging. For these reasons, alternative technologies have been developed as ammonia sources (e.g., solid urea, ammonium carbamate, metal ammine chloride) during the past few years. These technologies promise more convenient handling and distribution of ammonia sources, and help maximize the low-temperature performance of SCR catalysts and reduce the overall system volume and weight. However, none of these alternative technologies can be successfully implemented without the industry consensus. Therefore, the USCAR SCR work group, which is comprised of representatives from GM, Ford, and Chrysler, has decided to investigate the potential alternative ammonia carriers, define common standard vehicle interfaces, and address personal and environmental safety concerns with part suppliers and chemical companies. Under this CRADA Project, USCAR and Battelle will investigate alternative ammonia carrier materials that are currently under development. Based on the data and information derived under the CRADA project, the USCAR SCR work group plans to build the consensus and make recommendations for the industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Distributed Ledger Technology Preliminary Performance Assessment for Applications in Utilities Operational Technology

This paper provides descriptions of the key components of different distributed ledger technology platforms. Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices. The platforms use cryptographically linked “blocks” to store and verify transactional information between these organizations. DLT increases data security, data integrity, trust among its participants. Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories. In this study we examine twelve different DLT platforms. There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions. These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain. However, further development is required to realize the full promise of DLT. Our assessment includes a general description of each DLT and its key characteristics. Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless. The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements. During this research we found key parameters to measure performance and existing tools for assessment. Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability. The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks. From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures. The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗

DOE OSTI2022

A Hierarchical Framework for CO2 Storage Capacity in Deep Saline Aquifer Formations

Carbon dioxide (CO 2 ) storage in deep saline aquifers is a vital option for CO 2 mitigation at a large scale. Determining storage capacity is one of the crucial steps toward large-scale deployment of CO 2 storage. Results of capacity assessments tend toward a consensus that sufficient resources are available in saline aquifers in many parts of the world. However, current CO 2 capacity assessments involve significant inconsistencies and uncertainties caused by various technical assumptions, storage mechanisms considered, algorithms, and data types and resolutions. Furthermore, other constraint factors (such as techno-economic features, site suitability, risk, regulation, social-economic situation, and policies) significantly affect the storage capacity assessment results. Consequently, a consensus capacity classification system and assessment method should be capable of classifying the capacity type or even more related uncertainties. We present a hierarchical framework of CO 2 capacity to define the capacity types based on the various factors, algorithms, and datasets. Finally, a review of onshore CO 2 aquifer storage capacity assessments in China is presented as examples to illustrate the feasibility of the proposed hierarchical framework.

58 GEOSCIENCES↗

DOE OSTI2023

Detection of Candida DNA in peritoneal fluids by PCR assay optimizing the diagnosis and treatment for intra-abdominal candidiasis in high-risk ICU patients: A prospective cohort study

Background Intra-abdominal candidiasis (IAC) is the predominant type of invasive candidiasis with high mortality in critically ill patients. This study aimed to investigate whether the polymerase chain reaction (PCR) assay for detecting Candida DNA in peritoneal fluids (PF) is useful in diagnosing and management of IAC in high-risk patients in intensive care unit (ICU). Methods A prospective single-center cohort study of surgical patients at high risk for IAC was conducted in the ICU. PF was collected from the abdominal drainage tubes (within 24 h) or by percutaneous puncture. Direct PF smear microscopy, PF culture, blood culture, and serum (1–3)-β-D-glucan were performed in all patients. For Candida PCR assay, the ITS1/ITS4 primers that targeted the ITS1-5.8 s-ITS2 regions were used for PCR, and sequencing analysis was used to identify the pathogen at the species level. IAC was defined according to the 2013 European consensus criteria. Results Among 83 patients at high risk for IAC, the IAC criteria were present in 17 (20.5%). The sensitivity and specificity of the Candida PCR assay were 64.7 and 89.4%, respectively, and the area under the receiver operating characteristic curve was 0.77 (95% CI: 0.63–0.91). In this cohort, the positive predictive value and negative predictive value were 90.8% (95% CI: 80.3–96.2%) and 61.1% (95% CI: 36.1–81.7%), respectively. Diagnostic consistency was moderate (kappa 0.529, p < 0.001) according to the 2013 European consensus criteria. Conclusion Detection of Candida DNA in PF using PCR can be considered an adjunct to existing routine diagnostic tools which may optimize the diagnosis and antifungal treatment of IAC in high-risk patients in the ICU.

Xie, Min↗

DOE OSTI2023

Evaluation of Potential In Vitro Recombination Events in Codon Deoptimized FMDV Strains

Codon deoptimization (CD) has been recently used as a possible strategy to derive foot-and-mouth disease (FMD) live-attenuated vaccine (LAV) candidates containing DIVA markers. However, reversion to virulence, or loss of DIVA, from possible recombination with wild-type (WT) strains has yet to be analyzed. An in vitro assay was developed to quantitate the levels of recombination between WT and a prospective A24-P2P3 partially deoptimized LAV candidate. By using two genetically engineered non-infectious RNA templates, we demonstrate that recombination can occur within non-deoptimized viral genomic regions (i.e., 3'end of P3 region). The sequencing of single plaque recombinants revealed a variety of genome compositions, including full-length WT sequences at the consensus level and deoptimized sequences at the sub-consensus/consensus level within the 3'end of the P3 region. Notably, after further passage, two recombinants that contained deoptimized sequences evolved to WT. Overall, recombinants featuring large stretches of CD or DIVA markers were less fit than WT viruses. Our results indicate that the developed assay is a powerful tool to evaluate the recombination of FMDV genomes in vitro and should contribute to the improved design of FMDV codon deoptimized LAV candidates.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

diffReplication - An Energy-Aware Fault Tolerance Model for Silent Error Detection and Mitigation in Heterogeneous Extreme-scale Computing Environment

At extreme scale, the frequency of silent errors – a class of errors that remain undetected by low-level error detection mechanisms – increases significantly with the computational complexity of the application and the scale of the computing infrastructure. As hardware and software advances are made to usher in the next scientific era of computing, developing new approaches to mitigate the impact of silent errors remains a challenging problem. In this work, we propose an energy-aware fault-tolerance model, referred to diffReplication to overcome silent errors. In the proposed model, the main process is associated with one replica that executes at the same rate as the main process, and one diffReplica that is executed at a fraction of the main process' execution rate. If the main and its replica reach consensus at the end of a computation phase, the state of the diffReplica is updated and computation is resumed. If the synchronization attempt results in a disagreement, however, the diffReplica increases its execution speed to complete the computation and quickly reach the synchronization barrier. Assuming a single error over any given synchronization interval, a majority voting is used to reach consensus and tolerate silent errors. To further enhance its performance, diffReplication is augmented with speculative execution, whereby the main or its fast replica is selected to continue execution without waiting for the diffReplica. The selection process is based on the previous behaviour of the main and its replica. A performance analysis study is carried out to assess the performance of diffReplication, in terms of the energy saving and time-to-completion reduction achieved by the diffReplication scheme. The experiment shows that speculative execution reduces the time to completion with additional energy, and dynamic decision-making balances the energy consumption and time to completion.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Bayesian and HRA-Aided Method for the Novel Reliability Analysis of Software

Technological advancements and nuclear power plant modernization has inspired considerable research in the areas of safety and reliability, yet there remains a lack of consensus for the reliability assessment of digital instrumentation and control (I&C) systems. Motivated by the lack of consensus for reliability analysis methods, this work employs a novel framework that incorporates Bayesian, human reliability, and common-cause failure (CCF) modeling techniques. The novel framework allows the use of state-of-the-art or classical modeling techniques when accounting for human and CCF effects on system reliability. The Bayesian and HRA-Aided Method for the Reliability Analysis of Software (BAHAMAS) is demonstrated by a case study for the quantification of software hazards found in a previous analysis of a digital reactor trip system. The results demonstrate the ability of BAHAMAS to account for human activities during the software development life cycle and their influence on software reliability. BAHAMAS is a flexible tool for extending the coverage of conventional probabilistic risk assessments to include modernized digital I&C systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Accelerating technology development to monitor and minimize effects from land‐based wind energy on birds and bats

While wind energy is a key sector of domestic energy production for the United States, operation of wind turbines directly and indirectly adversely affects certain species of birds and bats. The cumulative effect of wind turbine strikes can have both biological and regulatory consequences, and, in some cases, delay permitting and construction or affect ongoing operations. Technology can help quantify and minimize these effects, but the pace of development, acceptance, and adoption of technological solutions is slow. Although adopting cost‐effective technologies may reduce negative effects on wildlife and help achieve both energy production and conservation goals, consensus is lacking among developers, regulators, and the conservation community regarding how to define technology effectiveness and acceptance and how to develop a standardized process for doing so. Removing barriers to technology advancement requires deviating from the status quo. Changes include 1) creating incentives to mitigate impacts, 2) establishing options for research as mitigation, 3) rethinking how research is funded, 4) increasing stakeholder coordination, and 5) increasing the efficiency of research and development. We recommend the creation of a national framework to establish clear criteria and protocols for technology evaluation and adoption.

17 WIND ENERGY↗

DOE OSTI2020

Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling

Plug-and-play priors (PnP) is an image reconstruction framework that utilizes an image denoiser as an imaging prior. Unlike traditional regularized inversion, PnP does not require the prior to be expressible in the form of a regularization function. This flexibility enables PnP algorithms to exploit the most effective image denoisers, leading to their state-of-the-art performance in various imaging tasks. However, many powerful denoisers, such as the ones based on convolutional neural networks (CNNs), do not have tunable parameters that would allow controlling their influence within PnP. To address this issue, in this paper, we introduce a scaling parameter that adjusts the magnitude of the denoiser input and output. We theoretical justify the denoiser scaling from the perspectives of proximal optimization, statistical estimation, and consensus equilibrium. Finally, we provide numerical experiments demonstrating the ability of denoiser scaling to systematically improve the performance of PnP for denoising CNN priors that do not have explicitly tunable parameters.

Boosting↗

DOE OSTI2023

Convex Decreasing Algorithms: Distributed Synthesis and Finite-Time Termination in Higher Dimension

Here we establish finite time termination algorithms for consensus algorithms based on geometric properties that yield finite-time guarantees, suited for use in high dimension and in the absence of a central authority. These pursuits motivate a new peer to peer convex hull algorithm which is utilized for one stopping algorithm. Further an alternative lightweight norm based stopping criteria is also developed. The practical utility of the algorithm is illustrated through MATLAB simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

A Distributed Control Architecture for Cascaded H-Bridge Converter with Integrated Battery Energy Storage

Cascaded H-bridge topology has been used in grid-tied converters for battery energy storage system due to its modular structure. To fully utilize the converter’s modularity, this paper proposes a hierarchical distributed control architecture that consists of primary control, secondary control and battery state of charge (SOC) balancing control. Primary control ensures accurate current tracking while a distributed secondary control based on consensus algorithm is presented to regulate power sharing among modules and is proved to be stable theoretically. Here, a distributed SOC balancing control is further introduced to improve energy efficiency of battery energy storage system. Finally, the hierarchical distributed control strategy is implemented using hardware controllers and a software platform. Besides, a carrier phase shift control is also implemented to achieve multilevel output voltage and harmonic reduction. The experimental results demonstrate the performance of the proposed control scheme effectively.

25 ENERGY STORAGE↗

DOE OSTI2024

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

American Nuclear Society Standards Committee Subcommittee 8 Meeting [Slides]

The agenda was as follows: Discussion of Agenda, membership, Winter Meeting ANS-8 Subcommittee Minutes, ISO TC85/SC5/WG8 Standards Activity Report - D. Bowen, Nuclear Criticality Safety Consensus Committee (NCSCC) Activity Report - L. Wetzel, Reports from Working Group Chairs, and Old/New Business.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Cooperative Systems in Presence of Cyber-Attacks: A Unified Framework for Resilient Control and Attack Identification

Here, this paper considers a cooperative control problem in presence of unknown attacks. The attacker aims at destabilizing the consensus dynamics by intercepting the system’s communication network and corrupting its local state feedback. We first revisit the virtual network based resilient control proposed in our previous work and provide a new interpretation and insights into its implementation. Based on these insights, a novel distributed algorithm is presented to detect and identify the compromised communication links. It is shown that it is not possible for the adversary to launch a harmful and stealthy attack by only manipulating the physical states being exchanged via the network. In addition, a new virtual network is proposed which makes it more difficult for the adversary to launch a stealthy attack even though it is also able to manipulate information being exchanged via the virtual network. A numerical example demonstrates that the proposed control framework achieves simultaneously resilient operation and real-time attack identification.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Material-Dependent Antagonistic Effects between Soot and ZDDP

While soot in engine oil is known to accelerate the wear of diesel and gasoline direct-injection compression-ignition engines, there is a lack of consensus on the wear mechanism though various hypotheses have been proposed in the literature. Particularly, some recently observed antagonistic effects between soot and a common lubricant antiwear additive, zinc dialkyldithiophosphate (ZDDP), while others did not. The discrepancy is, in part, explained by the strong alloy dependence of such antagonism discovered in this study. Specifically, four alloys, 52100 steel and M2, M50, and A2 tool steels, are tested in lubricants containing carbon black (CB, a soot surrogate) with and without ZDDP present. Adding the CB alone to the oil increases the wear rate for all steel alloys as expected. However, distinct wear performance is observed for the four steel alloys when ZDDP is introduced to the CB-containing oil: while the 52100 steel has notable wear reduction, the three tool steels suffer significant wear increase. Comprehensive tribofilm characterization suggests that the Mo content in the steel alloy and the sulfur from ZDDP strongly influence wear behavior. The combination of CB/Mo-catalyzed sulfidation and CB-accelerated abrasion is hypothesized to be responsible for the high wear of the Mo-alloyed tool steels.

36 MATERIALS SCIENCE↗