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At least 937 records · Page 52

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DOE OSTI2020

Optimal PMU Restoration for Power System Observability Recovery After Massive Attacks

Cyber-physically resilient power system operation requires rapid recovery of situational awareness after disastrous scenarios such as massive cyber attacks. In this article, the concept of optimal sequential restoration of Phasor Measurement Units is introduced, aiming at rapid recovery of power system observability in post-attack scenarios. Additionally, the observability recovery problem is formulated as a Mixed Integer Linear Programming problem to maximize the cumulative observability level gained over time during the restoration process. Three alternative objective functions-maximizing the number of observable buses, the number of observable branches, and the total amount of observable power flow-are considered. The effectiveness of the proposed optimal strategy is verified by comparing it with heuristic approaches on the IEEE 57-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A Reference Implementation for a Quantum Message Passing Interface

Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelities for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected is highly demanding. To realize the internode communication of quantum information, the software interface, Quantum Message Passing Interface (QMPI), leveraging the framework built for classical MPI but taking advantage of quantum teleportation to communicate between different quantum nodes was proposed. In this project, we develop the QMPI with point-to-point and collective operations in Qiskit and characterize its performance by demonstrating the application implementations. Moreover, we developed a new technique for optimizing collective communication of the distributed quantum programs with Multi-Controlled Toffoli gates. This technique beats the state-of-the-art in terms of fidelity and the number of remote EPR pairs consumed in both simulations and experiments.

Shi, Yue↗

DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2019

Optimal Variable Switching Frequency Scheme to Reduce Loss of Single-Phase Grid-Connected Inverter With Unipolar and Bipolar PWM

Reducing the power loss of a converter without increasing its volume or cost in hardware has always been a much sought-after but challenging goal. This article proposes a comprehensive variable switching frequency (VSF) scheme to improve the overall system efficiency while still meeting a given total harmonic distortion (THD) requirement without any hardware changes, achieved only by changes to the controller. In this article, it is analyzed that for the H-bridge inverter, the inductor copper loss and the switch conduction loss are independent of the switching frequency (SF), while the device switching loss and the inductor core loss are functions of the SF. This article aims at weighting the combined switching loss and inductor core loss for both the unipolar and bipolar modulation techniques, with the constraint on the output THD, which, for fixed passive components, is a function of inductor ripple current that in turn depends on the SF. An optimal VSF scheme is devised through rigorous mathematical analysis of the output ripple component and the SF-dependent losses. In each switching cycle, the inductor ripple current is predicted with the circuit parameters, such as duty cycle, switching period, inductance, and dc voltage, and by implementing the VSF scheme, the current ripple is optimally varied such as to satisfy the THD requirement while reducing the SF-dependent losses. A generalized method to design VSF schemes for any topology and specifications is also presented, which would help future users in designing the VSF controller. A 1-kW H-bridge inverter using SiC MOSFETs and powdered iron/ferrite core has been built to validate the theoretical analysis. Both constant SF (CSF) scheme (200 kHz) and optimal VSF scheme with simple controller modification have been implemented in the experimental prototype using DSP TMS320f28335. Compared with the CSF scheme, the optimal VSF scheme shows a significant improvement in the system efficiency at rated power from 94.7%...

conduction loss↗

DOE OSTI2023

Distributed Energy Resource-Cognizant Upgrade Paths to the Traditional Restoration Strategy of Utilities for Improved Load Restoration

Climate change has resulted in increasingly impactful and more frequent occurrences of extreme weather events. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks under fault scenarios; however, currently, utilities deploying the automated fault location, isolation and restoration (FLISR) function in their advanced distribution management system (ADMS) do not take into account the available generation and load-modification capabilities of distributed energy resources present in the disconnected network due to an upstream isolated fault. This results in the network reconfiguration and restoration to result in sub-optimal load restoration. Therefore, this paper presents two approaches that can upgrade the existing FLISR capabilities of distribution utilities to significantly increase the restoration of critical loads. The performance of the proposed approaches is evaluated on a numerical model of a real distribution feeder in Georgia, USA.

DER↗

DOE OSTI2023

Experimental Verification of An Electro-Hydraulic Actuation System Driven by An Integrated Electro-Hydraulic Unit

This paper proposes an electro-hydraulic actuator (EHA) system, and a novel-designed electro-hydraulic unit (EHU) consisting of a fixed-displacement hydraulic gear machine and a variable-speed electric machine. The novel EHU design integrates an electric machine and a hydraulic machine in a single housing, targeting optimal compactness, power density, and component reduction. The EHA system features an open circuit design, where hydraulic hoses connect the EHU with a tank, a valve manifold, and the hydraulic cylinder. In this way, the proposed EHA technology can be used to implement distributed hydraulic actuation in a vehicle without requiring changes to the hydraulic actuators or at the overall layout of the hydraulic components with respect to the original vehicle design. A dedicated test rig is developed to verify the performance of the proposed EHA system. Here, the efficiency of the EHA is measured in a steady state and under a realistic duty cycle of a commercial compact loader. The efficiency of the EHA system based on the measurements on the test rig can reach 54% with up to 20 kN load and 6 kW power level. Furthermore, the EHU is implemented on the reference machine to drive the boom function. Preliminary results on the performance of the EHU show an efficiency of up to 68% under different loading conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Distributed Energy Resource-Cognizant Upgrade Paths to the Traditional Restoration Strategy of Utilities for Improved Load Restoration: Preprint

DER↗

DOE OSTI2021

A Data-Driven Multi-Period Importance Sampling Strategy for Stochastic Economic Dispatch

Power systems with high penetrations of renewable energy (e.g., wind power) require sophisticated approaches to optimize system performance due to uncertainty in short-term system generation capacity. In this paper, we combine a data-driven analog scenario selection method with importance sampling to create a novel scenario construction approach for two-stage stochastic economic dispatch problems with a large number of wind farms on a network. The proposed method produces scenarios with realistic physics by finding high-fidelity analogs that can describe future states of the system. We show how to extend this method to multi-period operations and demonstrate the effectiveness of this technique by simulating economic dispatch operations on a synthetic test system over the course of a week.

data-driven forecasting↗

DOE OSTI2023

Robust Resilient Signal Reconstruction under Adversarial Attacks

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We include a new challenge of robust estimation of the attack support. The problem is then cast as a constrained optimization problem merging promising techniques in the area of deep learning and estimation theory. A pruning algorithm is developed to reduce the "false positive" uncertainty of data-driven attack localization results, thereby improving the probability of correct signal reconstruction. Sufficient conditions for the correct reconstruction and the associated reconstruction error bounds are obtained for both exact and inexact attack support estimation. Moreover, a simulation of a water distribution system is presented to validate the proposed techniques.

Robust, Signal reconstruction, Resilient estimator↗

DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

INL, PNNL, and NREL, with support from our academic and industry partners, hosted a 2-day webinar to learn more about the benefits of hybrid energy systems, considerations for designing the right system for communities, and practical tools that can help with the design and development process. In Day 2 of this webinar, the focus was on tools that can be used to help inform design decisions for hybrid systems, including resource analysis, siting, resilience, valuation, and resource optimization. Day 2 also highlighted funding opportunities for hybrid systems.

14 SOLAR ENERGY↗

DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

14 SOLAR ENERGY↗

DOE OSTI2019

A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations

The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Enhancing Even Gas Distribution in Porous Media with Radial Flow

Packed beds, such as those used in thermal energy storage (TES) systems, typically use flow from one end to the other. This axial flow configuration leads to inefficiencies due to dispersion effects and high pressure drop. Instead of axial flow, this work proposes radial flow in packed beds, where a central tube provides flow that transports fluid from the center to the bed’s wall. Radial flow could be a promising solution to increase the efficiency of charging/discharging processes in TES systems. For instance, studies have been conducted on the thermal behavior during the charging process using radial flow and axial flow, and it was found that radial flow is better than axial flow in terms of thermal performance, where more energy can be stored in the storage tank during the charging process. However, the design of the radial pipe should be optimized to improve even flow distribution. In this work, numerical investigations on different designs were analyzed to enhance even flow gas distribution in the porous media when using this radial technique. This work shows the impact of different parameters on the even flow distribution into the packed bed for two different designs: 1) one radial tube at the center to provide the radial flow along with an annular tube at the wall to receive the flow, and 2) one radial tube at the center and four radial tubes at the wall. Air was used as fluid and 6 mm alumina beads as packing materials. Computational fluid dynamics (CFD) models in COMSOL Multiphysics were used to simulate the behavior of air flow through the piping and packed bed. It was found that the flow into the bed from the radial tube can be affected by different parameters: space between the holes, size/diameter of the holes, number of segments/zones, number of the holes in each zone and the length of each zone.

Beck, David M.↗

DOE OSTI2026

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Deformation of pores in response to uniaxial and hydrostatic stress cycling in Marcellus Shale: Implications for gas recovery

One of the main challenges during gas production from shale reservoirs is low recovery rate. One contributing factor to this outcome is an insufficient understanding of pore systems, especially pore behaviour following changes in reservoir conditions or resulting from gas production practices. Because the pressure in the producing well can be controlled, understanding the effects of pressure variation on the pore size distribution and methane trapping is necessary to help design optimal conditions to improve the gas recovery rate. This work is the first systematic study of sub-millimeter pore deformation in shale caused by uniaxial and hydrostatic stress up to 100 MPa. Overmature samples from the Middle Devonian Marcellus Shale were analyzed using neutron scattering (SANS and USANS) techniques to interpret the response of nanopores to stress cycling of magnitude and duration compatible with the hydraulic fracturing treatments. Experiments reported here are performed at a series of uniaxial pressures up to 100 MPa and at hydrostatic pressures of deuterated methane 0 and 50 MPa. Since at the original depth of the shale samples’ burial of 2184 m the hydrostatic pressure is approximately 27 MPa and the lithostatic pressure is about 55 MPa, the experimental conditions reasonably well simulate the reservoir pressure regime. Our SANS and USANS results show that different pore sizes are affected by uniaxial stress in different ways. Specifically, in the pore size range from 1 nm to 800 nm, a decrease of pore density with pressure is observed, with the most depleted being mesopores of about 100 nm in diameter. The observed decrease is likely related to deformation of kerogen, followed by a loss of pore nano-volume, as well as methane trapped in the micropores. For pores larger than 5 μm, USANS data suggest that the negative trend is reversed at above 74 MPa, and the number density of large macropores may increase with increased stress even above the original value. The increased number of macropores at high pressure may create new interconnected conduits for gas migration, resulting in a better recovery rate. Another important finding of this study is an irreversible rearrangement of pore size distribution taking place after pressure cycling. Furthermore, this irreversible reorganization of pore size distribution should be taken into account during management of well production to maximize recovery rate.

03 NATURAL GAS↗

DOE OSTI2024

Rosario Strait Tidal Energy plus Energy Storage — Preliminary Economic Assessment

The Orcas Power and Light Co-op (OPALCO) is a non-profit utility that provides energy services to approximately 11,700 customers across 20 islands in San Juan County, Washington. OPALCO is developing a diverse set of local renewable energy resources to reduce dependence on mainland Washington State for energy and to reduce the regional need for fossil-fueled power. OPALCO’s load doubles in winter but solar production is roughly 20% of levels reached in summer periods. Tidal energy is strong year-round, night and day, and is predictable, requiring much less storage to firm it. To assess the technical and economic feasibility of tidal power, working in combination with multiple other distributed energy resources (DERs), Argonne National Laboratory (Argonne) employed an optimization model to evaluate several economic benefits associated with varying scales of tidal power of between 2.4 and 9.6 megawatts (MW) and other DERs. In addition to existing photovoltaic (PV) and battery energy storage system (BESS) resources located on Decatur Island, Argonne also evaluated the addition of a BESS on southern Orcas Island with power and energy capacities ranging from 1-4 MW and 2-4 hours in storage duration.

25 ENERGY STORAGE↗

DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗