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At least 1,783 records · Page 99

Prescient

Prescient is a software package for simulating electricity grid (power systems) operations, under both nominal and extreme event conditions. Core functionality includes discrete event simulation, commitment and dispatch optimization, probabilistic scenario construction, and reporting/visualization. SAND2020-0169 M 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.

Watson, Jean Paul↗

A Hybrid Demand Response Simulator Version 1.0

A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, and the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.

Lu, Ning↗

pnnl/archive-sprinter

The Archive Sprinter tool is designed to efficiently process synchrophasor measurements from electric power grids and export data signatures that summarize the grid's behavior. Parallel processing will allow data to be processed quickly to enable practical analyses of archives spanning years. The grid's behavior will be summarized using a wide-array of signatures calculated from the input data.

Follum, Jim↗

EGSim v1.0

EGSim contains tools aimed at simulating static load flow solutions for power grids. It implements models for loads, generators, and transmission lines. The static load flow solution is computed via gradient descent. SAND20019-4672 M

SciDAC↗

Generator Scorecard

Code built on Archive Walker. The Generator Scorecard analyzes power grid measurements to automate the process of evaluating the performance of generators. The tool includes three aspects: frequency response, voltage response, and voltage schedule tracking.

Follum, Jim↗

Sparow-Examples

SAND2026-16701O SPAROW-Examples software provides a repository of stochastic programming examples designed to demonstrate Sandia's SPAROW optimization library. This resource helps users learn to develop complex applications with SPAROW by offering reference implementations that can be used to test and enhance new optimization solvers. The library offers a diverse range of simple and complex exemplars, including those related to power grid applications such as unit commitment and expansion planning. 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↗

SPAROW: Stochastic Programming and Related Optimization Workflows

SAND2026-16703O SPAROW: Stochastic Programming and Related Optimization Workflows is a Python library tool that facilitates the development and solution of stochastic programming problems. It provides a user-friendly class structure for defining stochastic programs through scenario-based representations of uncertainties. SPAROW incorporates multiple optimization strategies, including integer programming with all scenarios, progressive hedging, Benders decomposition, and Snoglode, a novel technique developed by Carnegie Mellon University. It also features interfaces to external solvers and functions that are commonly used in analysis workflows, making it applicable to a wide range of scientific and engineering design challenges, particularly in power grid planning. 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-NM), Albu↗

EmissionsFlexibility

Software to calculate the how changes in electricity consumption change the generator which provides the electricity. This is applied to find how load shifting (e.g. data centers) impact the carbon emissions of the power grid.

Rhodes, Noah↗

Going mobile to address emerging climate equity needs in the heterogeneous urban environment

We report the Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step towards this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods (IOPs).. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

17 WIND ENERGY↗

The split system approach to managing time in simulations of hybrid systems having continuous and discrete event components

The efficient and accurate management of time in simulations of hybrid models is an outstanding engineering problem. General a priori knowledge about the dynamic behavior of the hybrid system (i.e. essentially continuous, essentially discrete, or 'truly hybrid') facilitates this task. Indeed, for essentially discrete and essentially continuous systems, existing software packages can be conveniently used to perform quite sophisticated and satisfactory simulations. The situation is different for 'truly hybrid' systems, for which direct application of existing software packages results in a lengthy design process, cumbersome software assemblies, inaccurate results, or some combination of these independent of the designer's a priori knowledge about the system's structure and behavior. The main goal of this paper is to provide a methodology whereby simulation designers can use a priori knowledge about the hybrid model's structure to build a straightforward, efficient, and accurate simulator with existing software packages. The proposed methodology is based on a formal decomposition and re-articulation of the hybrid system; this is the main theoretical result of the paper. To set the result in the right perspective, we briefly review the essentially continuous and essentially discrete approaches, which are illustrated with typical examples. Then we present our new, split system approach, first in a general formal context, then in three more specific guises that reflect the viewpoints of three main communities of hybrid system researchers and practitioners. For each of these variants we indicate an implementation path. Our approach is illustrated with an archetypal problem of power grid control.

99 GENERAL AND MISCELLANEOUS↗

On Mixed-Integer Programming Formulations for the Unit Commitment Problem

We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.

97 MATHEMATICS AND COMPUTING↗

Novel Gas-Driven Fuel Cell HVAC and Dehumidification Prototype

Performance of a novel gas-driven, electricity-producing heating, ventilation, and air conditioning (HVAC) system with no vapor compression and no hydrofluorocarbon (HFC) refrigerant shall be discussed in the paper. The prototype was evaluated at ORNL under a Small Business Voucher (SBV) Cooperative Research and Development (CRADA) program. The target market is commercial buildings in the United States. The goal is to mitigate or eliminate grid-power for building air conditioning, coincident peak demand and associated spinning reserves, aiding in flattening of the “duck curve”. The technical goal is to transform the common packaged rooftop unit into a cost-effective distributed energy resource, opening a new range of small applications and broad markets for micro-combined cycle cooling, heating, and power with integral thermal energy storage. The test results indicate the prototype would be competitive with natural gas distributed power plants with average electrical production ranging from 45% to 60% natural gas to electricity conversion efficiency. The technology has a Primary Energy Savings Potential of 4.4 Quads, higher than any other air conditioning and heating technology.

Betts, Daniel↗

Hofstra University Center for Condensed Matter Research (Final Report)

Research performed by the Hofstra University Center for Condensed Matter Research added to our understanding of quantum computing, by providing theoretical analyses of entanglement entropy, superconductivity, by providing additional theoretical analyses of instabilities in superconductors, the design of future solar cells by research validating in part copper oxide as a low cost material the dynamics of excitable media by further work on the major chemical model, the Belousov Zhabotinsky reaction, and the dynamics of small random networks with scaling, typical of those in economics and the power grid.

14 SOLAR ENERGY↗

Protocol for Uniformly Measuring and Expressing the Performance of Energy Storage Systems

The U.S. Department of Energy’s Energy Storage Systems (ESS) Program, through the support of Pacific Northwest National Laboratory (PNNL) and Sandia National Laboratories (SNL), facilitated the development of the protocol provided in this report. The focus of the protocol is to provide a uniform way of measuring, quantifying, and reporting the performance of EESs in various applications; something that does not exist today and, as such, is hampering the consideration and use of this technology in the market. The availability of an application-specific protocol for use in measuring and expressing performance-related metrics of ESSs will allow technology developers, power-grid operators and other end-users to evaluate the performance of energy storage technologies on a uniform and comparable basis. This will help differentiate technologies and products for specific application(s) and provide transparency in how performance is measured. It also will assist utilities and other consumers of ESSs make more informed decisions as they consider the potential application and use of ESSs, as well as form the basis for documentation that might be required to justify utility investment in such technologies.

Bray, Kathryn L.↗

Online Analysis of Wind and Solar Part I: Ramping Tool

To facilitate wider penetration of renewable resources without compromising system reliability concerns arising from the lack of predictability of intermittent renewable resources, a tool for use by California Independent System Operator (CAISO) power grid operators was developed by Pacific Northwest National Laboratory (PNNL) in conjunction with CAISO with funding from California Energy Commission. This tool predicts and displays additional capacity and ramping requirements caused by uncertainties in forecasts of loads and renewable generation. The tool is currently operational in the CAISO operations center. This is one of two final reports on the project.

ancillary services↗

Adaptive Liquid Crystal Windows

Energy consumption by private and commercial sectors in the U.S. has steadily grown over the last decade. The uncertainty in future availability of imported oil, on which the energy consumption relies strongly, resulted in a dramatic increase in the cost of energy. About 20% of this consumption are used to heat and cool houses and commercial buildings. To reduce dependence on the foreign oil and cut down emission of greenhouse gases, it is necessary to eliminate losses and reduce total energy consumption by buildings. To achieve this goal it is necessary to redefine the role of the conventional windows. At a minimum, windows should stop being a source for energy loss. Ideally, windows should become a source of energy, providing net gain to reduce energy used to heat and cool homes. It is possible to have a net energy gain from a window if its light transmission can be dynamically altered, ideally electronically without the need of operator assistance, providing optimal control of the solar gain that varies with season and climate in the U.S. In addition, the window must not require power from the building for operation. Resolution of this problem is a societal challenge and of national interest and will have a broad global impact. For this purpose, the year-round, all-climate window solution to provide an electronically variable solar heat gain coefficient (SHGC) with a wide dynamic range is needed. AlphaMicron, Inc. (AMI) developed and manufactured 1ft × 1ft prototype panels for the world’s first auto-adjusting Adaptive Liquid Crystal Windows (ALCWs) that can operate from sunlight without the need for external power source and demonstrate an electronically adjustable SHGC. This novel windows are based on AlphaMicron’s patented e-Tint ® technology, a guest-host liquid crystal system implemented on flexible, optically clear plastic films. This technology is suitable both for OEM and aftermarket (retro-fitting) lamination to new and existing windows. Low level of power consumption by ALCWs allows for on-board power electronics for automatic matching of transmission through windows to varying climate conditions without drawing the power from the power grid. ALCWs are capable of transmitting more sunlight in winters to assist in heating and less sunlight in summers to minimize overheating. As such, they can change the window from being a source of energy loss to a source of energy gain. In addition, the scalable AMI’s roll-to-roll process, proved by making 1ft × 1ftALCW prototype panels, allows for cost-effective production of large-scale window panels along with capability to change easily their color and shape. In addition to architectural glazing in houses and commercial buildings, ALCWs can be used in other applications where control of sunlight is needed, such as green houses, used by commercial produce growers and botanical gardens, cars, aircrafts, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗