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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Development of high resolution imaging detectors for x ray astronomy

This final report summarizes our past activities and discusses the work performed over the period of 1 April 1990 through 1 April 1991 on x-ray optics, soft x-ray (0.1 - 10 KeV) imaging detectors, and hard x-ray (10 - 300 KeV) imaging detectors. If microchannel plates (MCPs) can be used to focus x-rays with a high efficiency and good angular resolution, they will revolutionize the field of x-ray optics. An x-ray image of a point source through an array of square MCP pores compared favorably with our ray tracing model for the MCP. Initial analysis of this image demonstrates the feasibility of MCPs for soft x-rays. Our work continues with optimizing the performance of our soft x-ray MCP imaging detectors. This work involves readout technology that should provide improved MCP readout devices (thin film crossed grid, curved, and resistive sheets), defect removal in MCPs, and photocathode optimization. In the area of hard x-ray detector development we have developed two different techniques for producing a CsI photocathode thickness of 10 to 100 microns, such that it is thick enough to absorb the high energy x-rays and still allow the photoelectrons to escape to the top MCP of a modified soft x-ray imaging detector. The methods involve vacuum depositing a thick film of CsI on a strong back, and producing a converter device that takes the place of the photocathode.

Murray, S. S.↗
DOE OSTI2018

Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer

Geo-grid algorithms divide a large polygon area into several smaller polygons, which are important for studying or executing a set of operations on underlying topological features of a map. The current geo-grid algorithms divide a large polygon in to a set of smaller but equal size polygons only (e.g. is ArcMaps Fishnet). The time to create a geo-grid is typically proportional to number of smaller polygons created. This raises two problems - (i) They cannot skip unwanted areas (such as water bodies, given about 71% percent of the Earth's surface is water-covered); (ii) They are incognizant to any underlying feature set that requires more deliberation. In this work, we propose a novel dynamically spaced geo-grid segmentation algorithm that overcomes these challenges and provides a computationally optimal output for borderline cases of an uneven polygon. Our method uses an underlying topological feature of population distributions, from the LandScan Global 2016 dataset, for creating grids as a function of these weighted features. We benchmark our results against available algorithms and found our approach improves geo-grid creation. Later on, we demonstrate the proposed approach is more effective in harvesting Points of Interest data from a crowd-sourced platform.

Sims, Kelly↗
DOE OSTI2015

Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users and vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.

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DOE OSTI2018

Field evaluation of performance of HVAC optimization system in commercial buildings

Smart new building technologies that offer continuous dynamic optimization of Heating, Ventilation, and Air Conditioning (HVAC) control hold promise to advance building operations for efficiency and grid response. These technologies use data from the control system to determine the analytically optimal setpoints, and then write back the optimal setpoints into the control system to minimize system energy consumption or costs. There are limited studies documenting field validations of these technologies. This paper presents the results from a long-term field evaluation of a model-predictive HVAC optimization system that installed in four commercial buildings. Energy savings analysis was conducted based on pre/post submetered energy use. Across the cohort of evaluation sites, HVAC savings following the implementation of the optimization system were mixed, ranging from 0–9%. Analysis of site operational data showed that occupant comfort was neither positively nor negatively impacted. Key technology adoption considerations and recommendations are summarized in the paper. The technology performs best when HVAC systems are in good working condition, and can be exercised to achieve the full range of its optimized setpoints–however it may not provide extensive additional savings over cases where best practice sequences of operation and reset strategies are already comprehensively implemented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Self-Driving Microscopy for AI/ML-Enabled Physics Discovery and Materials Optimization

Materials are the bedrock of economy and foundation for all real-world technologies. The viability of space travel, grid energy storage, solar to fuels conversion, methane removal, and photovoltaic energy solutions hinge on the discovery and optimization of novel materials and rapid scaling toward manufacturing. The last 20 years have seen an exponential growth in the theoretical predictive capability for crystalline materials and small molecules. However, it is only in the last five years that we have seen the rapid expansion of high-throughput synthesis enabled by laboratory robotics and microfluidics, as well as a resurgence of combinatorial synthesis (Abolhasani and Kumacheva 2023; Epps and Abolhasani 2021; Jiang et al. 2022; Rajan 2008; Soldatov et al. 2021; Szymanski et al. 2023). Combinatorial synthesis, microfluidics, and ultimately dip-pen megalibraries have demonstrated the ability to “write” multicomponent nanomaterials at high throughput scale, generating millions of material examples in the 3D, 4D, and 5D composition spaces (Chen et al. 2016, 2019; Jibril et al. 2022).

36 MATERIALS SCIENCE↗
NASA NTRS2014

Arbitrary Shape Deformation in CFD Design

Sculptor(R) is a commercially available software tool, based on an Arbitrary Shape Design (ASD), which allows the user to perform shape optimization for computational fluid dynamics (CFD) design. The developed software tool provides important advances in the state-of-the-art of automatic CFD shape deformations and optimization software. CFD is an analysis tool that is used by engineering designers to help gain a greater understanding of the fluid flow phenomena involved in the components being designed. The next step in the engineering design process is to then modify, the design to improve the components' performance. This step has traditionally been performed manually via trial and error. Two major problems that have, in the past, hindered the development of an automated CFD shape optimization are (1) inadequate shape parameterization algorithms, and (2) inadequate algorithms for CFD grid modification. The ASD that has been developed as part of the Sculptor(R) software tool is a major advancement in solving these two issues. First, the ASD allows the CFD designer to freely create his own shape parameters, thereby eliminating the restriction of only being able to use the CAD model parameters. Then, the software performs a smooth volumetric deformation, which eliminates the extremely costly process of having to remesh the grid for every shape change (which is how this process had previously been achieved). Sculptor(R) can be used to optimize shapes for aerodynamic and structural design of spacecraft, aircraft, watercraft, ducts, and other objects that affect and are affected by flows of fluids and heat. Sculptor(R) makes it possible to perform, in real time, a design change that would manually take hours or days if remeshing were needed.

Landon, Mark↗
DOE OSTI2016

Operations DER-CAM based Microgrid Controller, v1.0

The ODC Microgrid Controller is an optimization-based model predicative microgrid controller (MPMC) to minimize operation cost (and/or CO2 emissions) in a microgrid in the grid-connected mode. It is composed of several modules, including a) forecasting, b) optimization, c) data exchange and d) power balancing modules. In the presence of a multi-layered control system architecture, these modules will reside in the supervisory control layer.

STADLER, MICHAEL↗
DOE OSTI2021

A System of Agents for Supporting Optimization and Control of a Connected Community

The residential sector consumes a significant portion of the electricity sold in the United States. Above 60% of the energy used in the sector is used to operate heating, ventilation, and air conditioning (HVAC) systems and water heating (WH) systems. With the increase of intelligence in the grid and the new decision and control options enabled by the Internet of Things; control of these devices can be used to support the grid. Therefore, this article presents a scalable multiagent system for optimizing HVAC and WH systems while maintaining comfort. It allows a utility to orchestrate the shifting of energy from critical periods without direct control, but instead by using a price signal. The architecture, optimization formulation, implementation strategy and results from an implementation project are discussed.

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DOE OSTI2017

Optimal capacity planning of MG with multi-energy coordinated scheduling under uncertainties considered

Multi-objective optimisation of capacity planning for a grid-connected Microgrid (MG) with multi-energy demands is developed in this study. The optimal multi-energy coordinated scheduling, in which uncertainties of renewable energy generation and electricity demand are described by uncertainty intervals, is considered within the capacity planning model. To solve the capacity planning problem while considering the optimal scheduling with uncertainties, a two-level optimisation approach is proposed by integrating interval mixed integer linear programming for scheduling into the multi-objective particle swarm optimisation for capacity planning. The multi-objective addresses the economic issue by minimising the worst-case optimal annual costs of device investments, operation and maintenance, and pollutant emission treatment, as well as the reliability concern by minimising the worst-case optimal annual costs of energy outage. Several MG cases studies are shown to demonstrate the proposed method.

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DOE OSTI2019

Assessment of CReST-VCT Deployment in Real-Time Environments: Communication System Examination

Incorporation of decentralized generation or distributed energy resources (DERs) such as solar and wind, is transforming the electricity grid. These resources have the potential to provide greater overall value when they are grid connected and coordinated between transmission and distribution systems. The Coordinated Real-Time Sub-Transmission Volt-VAr Control Tool (CReST-VCT) has been proposed to provide co-optimization between transmission and distribution systems maximizing DER utilization while maintaining overall grid stability. In this paper, we examine the communication systems that are necessary to support the integration of the CReST-VCT optimization mechanism in a real-time operational environment. The required communication interfaces will be identified based on the operation model of CReST-VCT. The characteristics of the communication systems at these interfaces will be described to establish the context within which CReST-VCT will operate. The related protocols and cybersecurity domain will be reviewed. Potential issues and concerns will then be identified to guide subsequent integration efforts.

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DOE OSTI2018

Assessment of Optimal Flexibility in Ensemble of Frequency Responsive Loads

Potential of electrical loads in providing grid ancillary services is often limited due to the uncertainties associated with the load behavior. A knowledge of the expected uncertainties with a load control program would invariably yield to better informed control policies, opening up the possibility of extracting the maximal load control potential without affecting grid operations. In the context of frequency responsive load control, a probabilistic uncertainty analysis framework is presented to quantify the expected error between the target and actual load response, under uncertainties in the load dynamics. A closed-form expression of an optimal demand flexibility, minimizing the expected error in actual and committed flexibility, is provided. Analytical results are validated through Monte Carlo simulations of ensembles of electric water heaters.

Kundu, Soumya↗
NASA NTRS1993

Calculation of optimum airfoils using direct solutions of the Navier-Stokes equations

A method has been developed which calculates the optimum airfoil shape at a specified operating condition. The Reynolds-averaged Navier-Stokes equations with a turbulence model are used as the governing equations for the fluid flow, and are explicitly introduced into the optimization analysis as constraint equations. The locations of all grid points which define the surface of the airfoil are design variables, eliminating the need for shape functions to describe changes in the airfoil geometry. A generalized reduced-gradient method is used to find the optimum airfoil shape. The use of a direct solution technique (Newton's method) to solve the Navier-Stokes equations allows for the efficient solution of the problem. This paper describes the optimization method and presents sample results.

Felker, Fort F.↗
DOE OSTI2022

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

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DOE OSTI2018

Parallel dispatch: a new paradigm of electrical power system dispatch

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus, the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids, extend system operators U+02BC capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

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DOE OSTI2020

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA-Based Surrogate for Spatial Fields

Global Climate Model tuning (calibration) is a tedious and time-consuming process, with high-dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand-picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere-only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient-based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly-tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high-dimensional output and operating in a fraction of the time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Efficient algorithm for locating and sizing series compensation devices in large power transmission grids: II. Solutions and applications

In a companion manuscript, we developed a novel optimization method for placement, sizing, and operation of Flexible Alternating Current Transmission System (FACTS) devices to relieve transmission network congestion. Specifically, we addressed FACTS that provide Series Compensation (SC) via modification of line inductance. In this manuscript, this heuristic algorithm and its solutions are explored on a number of test cases: a 30-bus test network and a realistically-sized model of the Polish grid (~ 2700 nodes and ~ 3300 lines). The results on the 30-bus network are used to study the general properties of the solutions including non-locality and sparsity. The Polish grid is used as a demonstration of the computational efficiency of the heuristics that leverages sequential linearization of power flow constraints and cutting plane methods that take advantage of the sparse nature of the SC placement solutions. Using these approaches, the algorithm is able to solve an instance of Polish grid in tens of seconds. We explore the utility of the algorithm by analyzing transmission networks congested by (a) uniform load growth, (b) multiple overloaded configurations, and (c) sequential generator retirements.

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