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At least 163 records · Page 9

Deer Park Energy Center Natural Gas Combined Cycle Carbon Capture System Front-End Engineering Design Study (Final Scientific/Technical Report – Unlimited)

Calpine Texas CCUS Holdings, LLC (Calpine), Shell Catalysts & Technologies (SCT), Technip Energies (TEN), and Sargent & Lundy, LLC (S&L) have conducted a Front-End Engineering Design (FEED) Study to integrate a new carbon capture system at Calpine’s Deer Park Energy Center (DKEC). The DKEC facility is a nominal 1200 MW gas-fired co-generation power plant situated at the Shell Chemical Manufacturing (Shell) Facility located in Deer Park, Texas. Steam is produced for use by the adjacent Shell Chemical Manufacturing Facility as well as by the onsite steam turbine for electrical generation. The power output from DKEC is provided to the Electric Reliability Council of Texas (ERCOT) operated power grid. DKEC provides power to industrial and commercial customers via this interconnection.

03 NATURAL GAS↗

Seismic Contingency Auto Generator

This code takes in premade earthquake scenario XML files from USGS, power grid data, and converts them into a contingency file (.con file) that can be used by power grid solvers. Within the .con file are a number (Specified by the user) of contingencies that have randomly failed power transformers based on their likelihood of failure and peak ground acceleration (PGA) value around the transformer. The transformers' likelihood of failure was calculated based on a variety of finite element modeling on various transformer designed for specific transformer voltage classes. Parameters from these FEM were used to create generic fragility curves for transformers within a specific voltage class, which correspond with earthquake PGA values to produced a probability of failure for a given earthquake scenario. More refined versions of this process, such as specifying specific transformer design categories within a voltage class, could also be applied in future iterations of the software.

Vaagensmith, Bjorn [Idaho National Laboratory (INL↗

Voltage stability smart meter for analyzing voltage data and controlling an electrical power source and/or an electric appliance

Systems and methods for voltage stability monitoring and active/reactive power support are disclosed herein. In some embodiments, a smart electric meter of an end user in a grid power system can measure the voltage supplied to the end user via the grid power system, and can analyze the voltage data to detect critical voltage characteristics. The critical voltage characteristics may indicate that a voltage collapse event is likely. The smart electric meter can further estimate a voltage stability margin based on the voltage data. If necessary, the smart electric meter can control an electrical power source and/or an electric appliance positioned at or near the end user to increase the voltage stability margin.

Min, Liang↗

UAV Inspection of Electrical Transmission Infrastructure with Path Conformance Autonomy and Lidar-Based Geofences NASA Report on UTM Reference Mission Flights at Southern Company Flights November 2016

Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.

Moore, Andrew J.↗

A Comparison Of A Solar Power Satellite Concept To A Concentrating Solar Power System

A comparison is made of a Solar Power Satellite concept in geostationary Earth orbit to a Concentrating Solar Power system on the ground to analyze overall efficiencies of each infrastructure from solar radiance at 1 AU to conversion and transmission of electrical energy into the power grid on the Earth's surface. Each system is sized for a 1-gigawatt output to the power grid and then further analyzed to determine primary collector infrastructure areas. Findings indicate that even though the Solar Power Satellite concept has a higher end-to-end efficiency, that the combined space and ground collector infrastructure is still about the same size as a comparable Concentrating Solar Power system on the ground.

Smitherman, David V.↗

Automation for Grid Interconnected Laboratory Emulation

As computational capabilities improve, digital twins are becoming vital for evaluating equipment realistically in laboratories. This paper outlines a digital twin architecture for the power grid, employing electromagnetic transient (EMT) simulation alongside real-time simulation of power hardware and hierarchical control systems. EMT simulation occurs on a high-performance computing server for scalability. Additionally, the paper describes a workflow and real-time data streaming software facilitating connectivity among EMT simulation, hierarchical control systems, and power hardware. This software enables automated equipment connectivity in the laboratory for realistic evaluations, aiding in identifying necessary upgrades for both equipment control systems and the power grid.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure↗

Loss of Glen Canyon Dam Hydropower Plant Capabilities

The power grid in the western United States is undergoing a major transformation, driven by technological advancements, power markets, policy shifts, and evolving energy demands. The integration of variable renewable energy (VRE) resources, such as wind and solar, into the power grid has become a major driver of change. Between 2018 and 2023, about 19 gigawatts (GW) of new solar capacity and 14 GW of new wind capacity was built in the Western Interconnection (WI) region. These two VRE resources accounted for the majority of WI capacity additions. The Western Interconnection is expected to host 30 GW of wind, 40 GW of solar, and 14 GW of energy storage by 2030 (Western Electricity Coordinating Council n.d.).

13 HYDRO ENERGY↗

Duty cycle testing and performance evaluation of the SM-229 teleoperator

The first known experimental studies and analyses of teleoperator performance for specific duty cycles are discussed. The results are presented in two distinct areas as position usage patterns, and as three-dimensional power grids. The position usage patterns are a valuable means to assess the available motion range. The power grids are a unique concept for evaluating joint performance. Final conclusions contain recommendations to upgrade the teleoperator for optimum performance.

Stoughton, Robert S.↗

A Comparison of a Solar Power Satellite Concept to a Concentrating Solar Power System

A comparison is made of a solar power satellite (SPS) concept in geostationary Earth orbit to a concentrating solar power (CSP) system on the ground to analyze overall efficiencies of each infrastructure from solar radiance at 1 AU to conversion and transmission of electrical energy into the power grid on the Earth's surface. Each system is sized for a 1-gigawatt output to the power grid and then further analyzed to determine primary collector infrastructure areas. Findings indicate that even though the SPS concept has a higher end-to-end efficiency, the combined space and ground collector infrastructure is still about the same size as a comparable CSP system on the ground.

Smitherman, David V.↗

A Real-Time Implementation and Validation of Federated Learning for Grid Services

Grid-edge devices are becoming increasingly important in the energy transition. Preserving privacy was not previously considered an important aspect for power grid operations, but with the increased proliferation of customer-owned assets, it is now an essential consideration. Several mechanisms have been proposed to provide privacy for non-utility owned assets in the power grid. Federated learning (FL) is one method gaining prominence in this area. Although FL has been used for other applications, such as auto-complete in phones, there has not been much investigation into whether these approaches are feasible for grid applications. In this work, we use a research platform with real-time simulators and hardware-in-the-loop capabilities to investigate how FL can be applied to grid-edge devices, and we present the potential grid services that can be derived for these devices. We discuss the computational challenges with deploying complex FL approaches, and we explore several grid services, including participation in retail electricity markets, voltage control, and resilience-driven reconfiguration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comparative life cycle assessment of various hydrogen pathways for cleaner methanol synthesis

This study evaluates the potential environmental impacts of e-methanol production using hydrogen from green, yellow, and blue sources, including Gas Switching Reforming for high purity hydrogen production with carbon capture (GSR-H 2 ), and compares their performance across current and renewable energy scenarios. Using a cradle-to-gate life cycle assessment (LCA), the study quantifies impacts across seven TRACI categories. Global warming potential (GWP) ranged from 0.28 kg CO 2 eq/kg MeOH for green hydrogen with renewables to 2.55 kg CO 2 eq/kg MeOH for SMR-CC under grid power. Among the scenarios, renewable electrolysis achieves the lowest GWP, while GSR-H 2 under renewable power offered the best balance of emissions reductions and resource efficiency among the fossil-based routes, offering a viable transitional solution in regions dependent on natural gas infrastructure. The study reveals GSR-H 2 's potential as an alternative to conventional steam methane reforming with carbon capture (SMR-CC), showing its advantages in carbon capture efficiency and reduced life cycle emissions as well as significantly lower water consumption. GSR-H 2 , when powered by renewables, consumed only 1.41 L of water per kg MeOH, an 82% reduction compared to grid-powered electrolysis, highlighting its potential in water-scarce regions. This study is the first to evaluate GSR-H 2 as a hydrogen source for e-methanol, providing new evidence for its role as a cleaner, scalable transitional solution aligned with cleaner production principles.

08 HYDROGEN↗

LLGOMAX: Enhancing Industry-Standard Tools for AC Optimal Unit Commitment (CRADA Final Report)

This was a collaborative effort between Lawrence Livermore National Security, LLC ("LLNS"), as manager and operator of Lawrence Livermore National Laboratory ("LLNL") and ECCO International Inc. ("Participant"). The team designed and implemented a new approach for the Security-Constrained Alternating-Current Unit Commitment (SCACUC) problem. The SCACUC problem is a mathematical optimization problem that decides which generating units should be online and how much power should be produced (and consumed) at each point of the power grid. The decisions are made so as to minimize the total cost of supplying electricity while respecting technical constraints of the power grid, both under normal and emergency conditions. The team developed a solution for SCACUC as specified in the ARPA-E Grid Optimization Competition (GOC) Challenge 3, which put forth a forward-looking version of the problem, which many features not present in today’s electricity market specifications for SCACUC.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗

Stability, Transient Response, Control, and Safety of a High-Power Electric Grid for Turboelectric Propulsion of Aircraft

This document contains the deliverables for the NASA Research and Technology for Aerospace Propulsion Systems (RTAPS) regarding the stability, transient response, control, and safety study for a high power cryogenic turboelectric distributed propulsion (TeDP) system. The objective of this research effort is to enumerate, characterize, and evaluate the critical issues facing the development of the N3-X concept aircraft. This includes the proposal of electrical grid architecture concepts and an evaluation of any needs for energy storage.

Armstrong, Michael↗

nnopf

SAND2026-19433O The nnopf tool addresses the optimal power flow (OPF) problem by optimizing electricity delivery from generating plants to consumers. At the same time, it minimizes costs and adheres to power grid constraints. While traditional methods for solving OPF can be computationally intensive, the tool mitigates this challenge by training neural networks on power grids to predict optimal solutions for the OPF problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-CA), Live↗

Extending Grid Computing to Remote Locations

NASA Glenn Research Center, in cooperation with NASA Ames and geologists from the University of Cincinnati and Bowling Green State University has extended the computational capabilities of the information Power Grid to remote research sites. The combination of satellite (EOS) data acquisition and the IPG processing provides geologists with the ability to identify the key mineralogical features at the research site. The underlying connectivity for this research environment is provided by the Numerical Research and Education Network (NREN) using a combination of terrestrial and mobile satellite-based networking solutions. Our approach not only speeds the process of scientific discovery, but also serves as a simple demonstration of NASA's capacity for geological classification and exploration of remote sites such as the Martian surface. The NASA Glenn Demonstrations combines satellite (EOS) data acquisition and the computational capabilities or the Information Power Grid (IPG) to provide geologists with the ability to identify key mineralogical features in near real-time of an area in study. This capability could someday allow geological classification of rocks and minerals of remote sites such as the Martian surface.

Griffin, Robert↗