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Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids

The OPEN COG Grid project is a collaborative effort between LLNL, NREL, and Texas A&M University (TAMU) to develop synthetic power system datasets that (i) contain all technical information that would be available in a real system, allowing to conduct studies ranging from dynamic simulation to long term planning studies; ii) are accessible to researchers from the broader data sciences community, as oppossed to power system experts only; and (iii) This report summarizes the work conducted during the first 15 months of execution of the project. These activities encompassed: 1. Conduct a survey of existing open data sets and open source power systems simulators, their supported use cases, and accessibility (Chapter 1). 2. Define a new extensible specification for power system data, covering all parameters necessary for most computational use cases (Chapter 2). 3. Collecting real technical system data to complete missing parameters in existing open source datasets (Chapter 3). 4. Develop models that capture the behavior of emergent actors in power grids, neglected by existing datasets; aggregated residential demand response (Chapter 4) and demand response of cryptocurrency miners (Chapter 5). 5. Collect detailed spatial information on distributed energy resources, particular, solar photovoltaic facilities (Chapter 6). The following chapters provide detailed descriptions of these tasks, the assumptions taken, and their findings. In conducting these tasks, the project team produced: two (accepted) conference papers; one journal paper under submission; one draft journal paper pending submission; released one repository with the developed power system data specification, with documentation and examples; and one extended dataset for the Texas power grid under review for release. The team hopes these contributions will enhance access to power system data and remove barriers to the development of new computational techniques for power systems, particularly, those inspired by cognitive sciences.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Liquid rocket combustion instability analysis by CFD methods

Combustion instability in liquid rocket engines is simulated computationally by using a simple two-parameter model for the combustion response function. The objectives of the study are to assess the capabilities of CFD algorithms for instability studies and to investigate the response to parametric effects such as bombs and distributed combustion. Results indicate that numerical solutions of high accuracy can be obtained if a sufficient number of grid points are used per wavelength of the disturbance. The short-term response to bombs or pulses triggers a large number of modes in the combustor whose faithful resolution requires highly dense grids, although there is evidence that correct long-term solutions can be obtained even if all the short-term frequencies are not resolved. Long-term responses to pulses are shown to decay to the most unstable mode in small amplitude cases, and to exhibit limit cycles in large amplitude cases. Comparison of distributed with concentrated heat release indicates the former is more stable for given values of the combustion response parameters, and that the distributed heat release gives rise to higher frequency disturbances. Wave steepening is observed in the solutions, but its effect is less pronounced in multidimensional waves than in one-dimensional waves.

Grenda, J. M.↗

Role of Standard Demand Response Signals for Advanced Automated Aggregation

Emerging standards such as OpenADR enable Demand Response (DR) Resources to interact directly with Utilities and Independent System Operators to allow their facility automation equipment to respond to a variety of DR signals ranging from day ahead to real time ancillary services. In addition, there are Aggregators in today’s markets who are capable of bringing together collections of aggregated DR assets and selling them to the grid as a single resource. However, in most cases these aggregated resources are not automated and when they are, they typically use proprietary technologies. There is a need for a framework for dealing with aggregated resources that supports the following requirements: • Allows demand-side resources to participate in multiple DR markets ranging from wholesale ancillary services to retail tariffs without being completely committed to a single entity like an Aggregator; • Allow aggregated groups of demand-side resources to be formed in an ad hoc fashion to address specific grid-side issues and support the optimization of the collective response of an aggregated group along a number of different dimensions. This is important in order to taylor the aggregated performance envelope to the needs to of the grid; • Allow aggregated groups to be formed in a hierarchical fashion so that each group can participate in variety of markets from wholesale ancillary services to distribution level retail tariffs. This paper explores the issues of aggregated groups of DR resources as described above especially within the context of emerging smart grid standards and the role they will play in both the management and interaction of various grid-side entities with those resources.

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Balancing Area Coordination: Efficiently Integrating Renewable Energy Into the Grid, Greening the Grid

Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. Coordinating balancing area operation can promote more cost and resource efficient integration of variable renewable energy, such as wind and solar, into power systems. This efficiency is achieved by sharing or coordinating balancing resources and operating reserves across larger geographic boundaries.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Demand Response Optimization and Management System for Real-TIme (DROMS-RT)

To design and demonstrate DROMS-RT, a highly distributed Demand Response Optimization and Management System for Real-Time (DROMS-RT) power flow control to support large scale integration of distributed renewable generation into the grid. AutoGrid developed a novel control and communications platform to allow highly dispatchable demand response (DR) services in time frames suitable for providing ancillary services to the transmission grid. These services will be substantially less expensive and more efficient than other forms of ancillary services options currently available to manage the intermittency associated with large-scale renewable integration. DROMSRT successfully leveraged Automated Demand Response (ADR) by fundamentally re-thinking the architecture of the DR platform from the ground up and by developing innovative new technologies in a number of areas related to DR. DROMS-RT leveraged the low-cost, open, interoperable DR signaling technology, OpenADR, and low-cost, internet-protocol based telemetry solutions to reduce the cost of hardware. This allowed DROMS-RT to provide dynamic price signals to millions of OpenADR clients. Statistically rigorous signal processing techniques were developed to reliably detect even small load reductions in the presence of noisy baseline profiles. Novel forecasting engines based on modern online machine learning algorithms enabled accurate individualized forecasts for customer loads in the presence of dynamic pricing signals, and a real-time decision engines enabled continuous optimization and optimal dispatch of DR resources across a large portfolio of heterogeneous loads that respond at varying time-scales. Moreover, the real-time optimization conducted by the decision engine can utilize grid physics to maximize load reduction at the transmission system in addition to the distribution sites, for more efficient grid operation. Finally, the Software-as-a-Service (SaaS) availability of the DROMS-RT platform has reduced the cost of deployment and enable participation of small commercial and residential customers in DR who otherwise would not be able to do so.

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Survey of Volumetric Grid Generators

This document is the result of an Internet Survey of Volumetric grid generators. As such we have included information from only the responses which were sent to us. After the initial publication and posting of this survey, we would encourage authors and users of grid generators to send further information. Here is the initial query posted to SIGGRID@nas and the USENET group sci.physics.computational.fluid-dynamics. Date: Sun, 30 Jan 94 11:37:52 -0800 From: woo (Alex Woo x6010 227-6 rm 315) Subject: Info Sought for Survey of Grid Generators I am collecting information and reviews of both government sponsored and commercial mesh generators for large scientific calculations, both block structured and unstructured. If you send me a review of a mesh generator, please indicate its availability and cost. If you are a commercial concern with information on a product, please also include references for possible reviewers. Please email to woo@ra-next.arc.nasa.gov. I will post a summary and probably write a short note for the IEEE Antennas and Propagation Magazine. Alex Woo, MS 227-6 woo@ames.arc.nasa.gov NASA Ames Research Center NASAMAIL ACWOO Moffett Field, CA 94035-1000 SPANET 24582::W00 (415) 604-6010 (FAX) 604-4357 fhplabs,decwrl,uunet)!ames!woo Disclaimer: These are not official statements of NASA or EMCC. We did not include all the submitted text here. Instead we have created a database entry in the freely available and widely used BIBTeX format which has an Uniform Resource Locator (URL) field pointing to more details. The BIBTeX database is modeled after those available from the BIBNET project at University of Utah.

Woo, Alex↗

ENERGY STAR Residential Water Heater Specification and Test Method for Connected Residential Water Heaters

Electric water heaters have long been used as a tool for demand response due to their inherent thermal storage and large electric load. Traditionally, electric water heaters have been controlled by external load control switches, but that type of control does not work well with more efficient heat pump water heaters and cannot ensure that consumers have adequate hot water. Water heater manufacturers are adding more sophisticated controls that allow utilities or consumers to control their water heaters in new ways that can provide demand response without impacting consumer comfort. Further, the electric utility grid has seen a rapid increase the availability of renewable energy, which, depending on the type of renewable energy, can provide large amounts of energy for a portion of the day, but reduced or no energy at other times. In response to these advances in controls, availability of periodic renewable energy, and in an effort to have a standard which can be applied at a national level, ENERGY STAR and the Department of Energy have developed a Product Specification and Test Method for Connected Residential Water Heaters. In this session, we will discuss the new specification and test method, as well as show some initial results from running the new test method with two different HPWHs at NREL.

connected water heater↗

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of the atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.

54 ENVIRONMENTAL SCIENCES↗

Microgrid's Role in Enhancing the Security and Flexibility of City Energy Systems

Smart cities depend on flexible and secure energy systems to ensure resilient power for critical infrastructure; however, recent weather-related events and cyberattacks have highlighted weaknesses in our energy systems, with the potential for widespread economic and security impacts. As stated by the Executive Office of the President, "the resilience of the US electric grid is a key part of the nation's defense against severe weather." To address the energy delivery security challenge, microgrids are rising as a viable solution that enhances the flexibility and resilience of the distribution grid and boosts the reliability of the local supply for the end-user. Traditionally, high capital investment has been a barrier to large-scale adoption of microgrid technology. Understanding the flexibility and resilience benefits of microgrids and accounting for the associated value streams can make the microgrid's proposition economically viable. In this chapter, microgrids' utility and their potential to serve as a flexible and resilient resource for the utility grid by providing capabilities such as peak shaving, demand response, and frequency regulation is presented. Moreover, other value streams, such as (1) their ability to island during a disaster and sustain critical loads which makes them a robust resilience solution for end-users, in the event of the utility grid outage and (2) microgrids also provide a flexible platform for integrating distributed energy resources in conjunction with storage and conventional generation technologies, strengthen microgrid's role in reducing the over-arching goal of emission reduction. Given the myriad of benefits associated with microgrids, we present strategies which can be employed for making microgrid itself resilient against physical and cyberthreats by employing hardware, software, and personnel training solutions to operate the microgrid before, during, and after a potential disaster. This chapter, thus, provides a holistic study of the microgrid as a resilience resource, for the utility grid, and a self-contained end-user for the end-user.

cyber-physical system↗

Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization

How much elevated atmospheric CO2 concentration (eCO2) contributes to the terrestrial carbon sink (NEP) is a debated issue (Friedlingstein et al., 1995; Field & Raupach, 2004; Schimel et al., 2015; Keenan et al., 2016; Huntzinger et al., 2017). The results from Free-Air CO2-Enrichment (FACE) experiments at the site scale show that eCO2 generally increase plant growth and net ecosystem CO2 uptake for a few years after exposure to eCO2, but the effects were highly variable across sites (Jastrow et al., 2005; De Graaff et al., 2006), which poses a challenge for scaling up these local observations. Here, we extract the simulated short-term responses of NEP to eCO2 from global carbon models using a substitute pulse-response approach, and compare them with site-scale responses from FACE experiments in temperate ecosystems. In 12 gridded terrestrial ecosystem models examined, the large-scale NEP sensitivity to eCO2 across the Northern Hemisphere (NH) temperate region is linearly related to the site-scale sensitivity across different ecosystems. We use this emergent relationship, together with the observed response to eCO2 in the FACE site-scale data to estimate a data constrained effect of eCO2 on the NH temperate NEP of 0.73 ± 0.22 Pg C yr-1 per hundred parts per million (ppm) of CO2 increase during the past five decades. This is 26% higher than the mean of the model ensemble. Among the models, those with carbon-nitrogen interactions underestimate the sensitivity of NEP to eCO2, suggesting overly strong nitrogen-limitations on carbon uptake. We further identify that the NEP sensitivity to eCO2 at NH temperate scale is linearly correlated with that at global scale across the models. Extrapolating the constrained NH eCO2 effect to the global terrestrial carbon sink provides an estimate of 4.1 ± 1.5 Pg C yr-1 [100 ppm]-1. Large uncertainties remain regarding the global response broadly inferred from temperate FACE data, due to the lack of observations in boreal and tropical regions, emphasizing the importance of deploying new FACE experiments in those regions.

Liu, Yongwen↗

Learning Distribution Grid Topologies: A Tutorial

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distribution grids. The primary focus is to highlight methods that overcome the limited availability of measurement devices in distribution grids, while enhancing topology estimates using conservation laws of power-flow physics and structural properties of feeders. Grid data from phasor measurement units or smart meters can be collected either passively in the traditional way, or actively, upon actuating grid resources and measuring the feeder's voltage response. Analytical claims on feeder identifiability and detectability are reviewed under disparate meter placement scenarios. Such topology learning claims can be attained exactly or approximately so via algorithmic solutions with various levels of computational complexity, ranging from least-squares fits to convex optimization problems, and from polynomial-time searches over graphs to mixed-integer programs. Although the emphasis is on radial single-phase feeders, extensions to meshed and/or multiphase circuits are sometimes possible and discussed. Here this tutorial aspires to provide researchers and engineers with knowledge of the current state-of-the-art in tractable distribution grid learning and insights into future directions of work.

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Use of high-granularity CdZnTe pixelated detectors to correct response non-uniformities caused by defects in crystals

Following our successful demonstration of the position-sensitive virtual Frisch-grid detectors, we investigated the feasibility of using high-granularity position sensing to correct response non-uniformities caused by the crystal defects in CdZnTe (CZT) pixelated detectors. The development of high-granularity detectors able to correct response non-uniformities on a scale comparable to the size of electron clouds opens the opportunity of using unselected off-the-shelf CZT material, whilst still assuring high spectral resolution for the majority of the detectors fabricated from an ingot. Here, we present the results from testing 3D position-sensitive 15×15×10 mm 3 pixelated detectors, fabricated with conventional pixel patterns with progressively smaller pixel sizes: 1.4, 0.8, and 0.5 mm. We employed the readout system based on the H3D front-end multi-channel ASIC developed by BNL's Instrumentation Division in collaboration with the University of Michigan. We use the sharing of electron clouds among several adjacent pixels to measure locations of interaction points with sub-pixel resolution. By using the detectors with small-pixel sizes and a high probability of the charge-sharing events, we were able to improve their spectral resolutions in comparison to the baseline levels, measured for the 1.4-mm pixel size detectors with small fractions of charge-sharing events. These results demonstrate that further enhancement of the performance of CZT pixelated detectors and reduction of costs are possible by using high spatial-resolution position information of interaction points to correct the small-scale response non-uniformities caused by crystal defects present in most devices.

36 MATERIALS SCIENCE↗

Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

Kalsi, Karanjit↗

Demand Response for Thermal Fairness in District Heating Networks

District Heating (DH) networks are complex thermal grids wherein a centrally heated fluid is circulated through a network of pipes and heat exchangers to meet the heating needs of residential and commercial buildings. Several factors can lead to inefficient and unfair energy distribution among consumers in these networks. These include varying levels of building insulation, distance of individual buildings from the central energy source, and thermal losses in network pipes. Moreover, shortage of energy at the central energy source and extreme weather conditions can exacerbate these issues, leading to differing levels of thermal comfort and customer disgruntlement in the long run. In this paper, we propose and study a demand response scheme that attempts to ensure thermal fairness among energy consumers in modern thermal grids. We develop optimization formulations based on thermodynamic models of DH networks, which determine optimal energy flow for individual buildings in order to achieve thermal fairness across the network. Our experimental results using physics based models for DH networks show that it is possible to achieve network level thermal fairness based social welfare objectives by controlling network parameters such as mass flow rates of water to the consumer premises and the supply water temperature, even when some network parameters like building thermal characteristics remain unknown.

Bhattacharya, Saptarshi↗

Big-Data Analytics for Electric Grid and Demand-Side Management

This report describes research to characterize the status of, and trends in, big-data analytics for the electricity grid. The research focused on 1) identifying power-grid big-data sources, types, and characteristics; and 2) characterizing big-data architecture, analytic methods, technology applications, and challenges. The first part of this report describes the main sources and characteristics of big data for the smart grid and comprehensively reviews big-data architecture, technologies, and applications in the power sector. The second part of this report presents case studies of big data applications in the power industry: (1) a smart-meter data and predictive analytics method for demand response (DR), (2) synchrophasor data analytics for the distribution grid, and (3) utility data for peak-demand management. For the predictive analytics case study, smart-meter-data-driven and physical models were developed to predict the potential kilowatt (kW) capacity reduction from DR. The DR estimation framework that was developed works for both small and large-scale customers. The synchrophasor case study demonstrates use of an algorithm applied to time-series data to detect events that appear as significant changes, known as “edges,” in voltage magnitude measurements. The synchrophasor case study also introduces an approach for clustering sets of events to reveal unique features that distinguish them (e.g., distinguishing capacitor bank switching from transformer tap changes). The peak-demand management case study describes the use of the data analytics to enable DR programs to limit forecasted peak demand, resulting in cost savings to the utility. The findings from the research described in this report support identification of opportunities and technologies for big-data and analytics applications for demand-side management in the power sector as well as other approaches to modernizing the electricity grid.

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Rapid Evaluation and Response to Impacts on Critical End-Use Loads Following Natural Hazard-Driven Power Outages: A Modular and Responsive Geospatial Technology

The disparate nature of data for electric power utilities complicates the emergency recovery and response process. The reduced efficiency of response to natural hazards and disasters can extend the time that electrical service is not available for critical end-use loads, and in extreme events, leave the public without power for extended periods. This article presents a methodology for the development of a semantic data model for power systems and the integration of electrical grid topology, population, and electric distribution line reliability indices into a unified, cloud-based, serverless framework that supports power system operations in response to extreme events. An iterative and pragmatic approach to working with large and disparate datasets of different formats and types resulted in improved application runtime and efficiency, which is important to consider in real time decision-making processes during hurricanes and similar catastrophic events. This technology was developed initially for Puerto Rico, following extreme hurricane and earthquake events in 2017 and 2020, but is applicable to utilities around the world. Given the highly abstract and modular design approach, this technology is equally applicable to any geographic region and similar natural hazard events. In addition to a review of the requirements, development, and deployment of this framework, technical aspects related to application performance and response time are highlighted.

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Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

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Development of a Flexible Framework of Common Hypersonic Navier-Strokes Meshes for the Space Shuttle Orbiter

A flexible framework for the development of block structured volume grids for hypersonic Navier-Stokes flow simulations was developed for analysis of the Shuttle Orbiter Columbia. The development of the flexible framework, resulted in an ability to quickly generate meshes to directly correlate solutions contributed by participating groups on a common surface mesh, providing confidence for the extension of the envelope of solutions and damage scenarios. The framework draws on the experience of NASA Langely and NASA Ames Research Centers in structured grid generation, and consists of a grid generation process that is implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (CAI) team, Ames developing the surface grids that described the computational volume about the orbiter, and Langely improving grid quality of Ames generated data and constructing the final volume grids. Distributing the work among the participants in the Aerothermodynamic CIA team resulted in significantly less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand for new meshes to explore new damage scenarios within a aggressive timeline.

Alter, Stephen J.↗