Understanding Methods to Determine Energy Levels of Quantum Dot Films for Device Integration
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Materials science, Nanoscience and Nanotechnology↗
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Systems and methods for electrical energy storage
The present disclosure relates to an electrical energy storage apparatus which forms an interpenetrating, three dimensional structure. The structure may have a first non-planar channel filled with an anode material to form an anode, and a second non-planar channel adjacent the first non-planar channel filled with a cathode material to form a cathode. A third non-planar channel may be formed adjacent the first and second non-planar channels and filled with an electrolyte. The first, second and third channels are formed so as to be interpenetrating and form a spatially dense, three dimensional structure. A first current collector is in communication with the first non-planar channel and forms a first electrode, while a second current collector is in communication with the second non-planar channel and forms a second electrode. A separator layers separates the current collectors.
Duoss, Eric B.↗
Profitability of Merchant Investments in Battery Energy Storage Systems: Methods and Case Studies.
Abstract not provided.
Dvorkin, Yury↗
Systems and methods for managing energy storage operations
An energy storage device (ESD) manager determines charge conditions that result in charge-related aging of an energy storage device (ESD), such as a battery, cell, or the like. The ESD manager may determine charge-related costs for charge operations, which may quantify charge-related aging imposed by subjecting ESD to specified charge conditions. The ESD manager may evaluate and/or modify charge operations to reduce charge-related aging. The ESD manager may be further configured to model charge-related aging behavior over time and/or under variable charge conditions. The ESD manager may configure charge operations to ensure that charge-related performance loss remains below a threshold for a specified usage duration.
Gering, Kevin L.↗
Multi-fluid, earth battery energy systems and methods
The present disclosure relates to a system for storing and time shifting at least one of excess electrical power from an electrical power grid, excess electrical power from the power plant itself, or heat from a heat generating source, in the form of pressure and heat, for future use in assisting with a production of electricity. An oxy-combustion furnace is powered by a combustible fuel source, plus excess electricity, during a charge operation to heat a reservoir system containing a quantity of a thermal storage medium. During a discharge operation, a discharge subsystem has a heat exchanger which receives heated CO 2 from the reservoir system and uses this to heat a quantity of high-pressure, supercritical CO 2 (sCO 2 ) to form very-high-temperature, high-pressure sCO 2 at a first output thereof. The very-high-temperature, high-pressure sCO 2 is used to drive a Brayton-cycle turbine, which generates electricity at a first output thereof for transmission to a power grid. The Brayton-cycle turbine also outputs a quantity of sCO 2 which is reduced in temperature and pressure to a heat recuperator subsystem. The heat recuperator subsystem circulates the sCO 2 and re-heats and re-pressurizes the sCO 2 before feeding it back to the heat exchanger to be even further reheated, and then output to the Brayton-cycle turbine as a new quantity of very-high-temperature, high-pressure sCO 2 , to assist in powering the Brayton-cycle turbine.
Buschek, Thomas A.↗
Systems and methods for randomized energy draw or supply requests
The present disclosure can provide a distributed and anonymous approach to demand response of an electricity system. The approach can conceptualize energy consumption and production of distributed-energy resources (DERs) via discrete energy packets that are coordinated by a cyber computing entity that grants or denies energy packet requests from the DERs. The approach leverages a condition of a DER, which is particularly useful for (1) thermostatically-controlled loads, (2) non-thermostatic conditionally-controlled loads, and (3) bi-directional distributed energy storage systems, among others. In a first aspect of the present approach, each DER independently requests the authority to switch on for a fixed amount of time (i.e., packet duration). The coordinator determines whether to grant or deny each request based electric grid and/or energy or power market conditions. In a second aspect, bi-directional DERs, such as distributed-energy storage systems (DESSs) are further able to request to supply energy to the grid.
Frolik, Jeff↗
Device and method for improving specific energy requirement of plasma pyrolyzing or reforming systems
Devices and methods for reducing the specific energy required to reform or pyrolyze reactants in plasmas operating at high flow rates and high pressures are presented. These systems and methods include 1) introducing electrons and/or easily ionized materials to a plasma reactor, 2) increasing turbulence and swirl velocity of the flows of feed gases to have improved mixing in a plasma reactor, and 3) reducing slippage from a plasma reactor system. Such plasma systems may allow plasma reactors to operate at lower temperatures, higher pressure, with improved plasma ignition, increased throughput and improved energy efficiency. In preferred embodiments, the plasma reactors are used to produce hydrogen and carbon monoxide, hydrogen and carbon, or carbon monoxide through reforming and pyrolysis reactions. Preferred feedstocks include methane, carbon dioxide, and other hydrocarbons.
Bromberg, Leslie↗
The Wave Energy Converter Design Process: Methods Applied in Industry and Shortcomings of Current Practices
Wave energy is among the many renewable energy technologies being researched and developed to address the increasing demand for low-emissions energy. The unique design challenges for wave energy converter design—integrating complex and uncertain technological, economic, and ecological systems, overcoming the structural challenges of ocean deployment, and dealing with complex system dynamics—have lead to a disjointed progression of research and development. There is no common design practice across the wave energy industry and there is no published synthesis of the practices that are used by developers. In this paper, we summarize the methods being employed in WEC design as well as promising methods that have yet to be applied. We contextualize these methods within an overarching design process. We present results from a survey of WEC developers to identify methods that are common in industry. From the review and survey results, we conclude that the most common methods of WEC design are iterative methods in which design parameters are defined, evaluated, and then changed based on evaluation results. This leaves a significant space for improvement of methods that help designers make better-informed decisions prior to sophisticated evaluation, and methods of using the evaluation results to make better design decisions during iteration. Despite the popularity of optimization methods in academic research, they are less common in industry development. We end this paper with a summary of the areas of WEC design in which the testing and development of new methods is necessary, and where more research is required to fully understand the influence of design decisions on WEC performance.
16 TIDAL AND WAVE POWER↗
Bayes goes fast: Uncertainty quantification for a covariant energy density functional emulated by the reduced basis method
A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the calibration is enabled by the emulation of the high-fidelity model through the implementation of a reduced basis method (RBM)—a set of dimensionality reduction techniques that can speed up demanding calculations involving partial differential equations by several orders of magnitude. The RBM emulator we build—using only 100 evaluations of the high-fidelity model—is able to accurately reproduce the model calculations in tens of milliseconds on a personal computer, an increase in speed of nearly a factor of 3,300 when compared to the original solver. Besides the analysis of the posterior distribution of parameters, we present model calculations for masses and radii with properly estimated uncertainties. We also analyze the model correlation between the slope of the symmetry energy L and the neutron skin of 48 Ca and 208 Pb. The straightforward implementation and outstanding performance of the RBM makes it an ideal tool for assisting the nuclear theory community in providing reliable estimates with properly quantified uncertainties of physical observables. Such uncertainty quantification tools will become essential given the expected abundance of data from the recently inaugurated and future experimental and observational facilities.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A hybrid theoretical method for predicting electrokinetic energy conversion in nanochannels
Schematic illustration of the hybrid method model. ρ is the net charge density calculated from cDFT. v is the velocity calculated from non-equilibrium MD simulation. b and α W are the slipping length and the surface properties, respectively.
Hu, Xiaoyu↗
Measurement of Beam Energy in the Fermilab's Linac taken at the Transfer Line
Linac is the first machine in the accelerator chain at Fermilab where H$^{-}$ ions are accelerated from 35 keV to 401.5\,MeV and then injected into a synchronton known as Booster where they are stripped of their electrons to become protons. One of the tools used during tuning of the Linac extraction energy is two beam pickups known as Griffin Detectors. Our goal is to control the output energy using machine learning techniques to increase the reliability and quality of the beam delivered from Linac. The first step is to understand the data from the diagnostics to develop reliable and accurate energy measurement, and control methods before implementing machine learning techniques. Two methods of energy measurement were studied, and their results are compared. The first method was the time of flight measurement using Beam Position Monitors that provide beam phase measurement. The second method used the relation between beam transverse positions and dispersion values to calculate momentum variation. The results of these two measurement methods are found to be consistent.
43 PARTICLE ACCELERATORS↗
Battery Energy Storage System Evaluation Method
This report describes development of an effort to assess Battery Energy Storage System (BESS) performance that the US DOE Federal Energy Management Program (FEMP) and others can employ to evaluate performance of deployed BESS or solar photovoltaic (PV) +BESS systems. The proposed method is based on actual battery charge and discharge metered data to be collected from BESS systems provided by federal agencies participating in the FEMP's performance assessment initiatives. Long-term (e.g., at least one year) time series (e.g., hourly) charge and discharge data are analyzed to provide approximate estimates of key performance indicators (KPIs).
25 ENERGY STORAGE↗
Method of controlling a vehicle to adjust perception system energy usage
A method of controlling a vehicle includes determining a current operating situation of the vehicle, and identifying a subset of a plurality of sensors of the vehicle needed to provide data to enable a vehicle control function for the current operating situation of the vehicle. A remainder of the plurality of sensors is disengaged to reduce electric energy usage by the vehicle while the vehicle is operating in the current operating situation of the vehicle. A sampling rate for the selected subset of sensors may be reduced to further reduce energy usage of the vehicle. Additionally, an energy reduction processing strategy may be implemented to reduce a processor frequency or a voltage of a computing device used to provide the vehicle control function to further reduce energy usage of the vehicle.
Hu, Yuxiao↗
Scaling Building Energy Audits through Machine Learning Methods on Novel Drone Image Data
Building energy audits are time-consuming and labor-intensive. This paper describes a new method using machine learning (ML) techniques on novel data sources (drone images) to improve the identification of building characteristics and retrofit opportunities, and thereby reduce the effort for audits. The new ML method includes: (1) Building footprint extraction using line extraction, polygonization, and polygon-merging, (2) Building envelope extraction using PIX4d modeling software to reconstruct a building 3D model, (3) Visualization tool for viewing images from the 3D model, (4) Window-to-wall ratio (WWR) using state-of-art deep neural network semantic segmentation, (5) Envelope thermal anomaly detection using an unsupervised machine learning clustering algorithm, and (6) Rooftop energy equipment detection based on an object detection algorithm. The testing of this method involved a comparison of additional ML-generated information overlaid on current ‘state-of-practice’ audit and remote assessment baselines using evaluation metrics: labor time and associated cost, marginal benefits of using ML-generated information in workflows for audits and remote assessments, integration potential with existing processes and tools, and replicability/scalability of the method. In two test buildings in California that had comprehensive drawings and meter data available, the ML method effectively generated a building footprint, envelope, rooftop equipment, WWR, and locations of envelope thermal anomalies. Projected target segments of the ML method are sites with minimal drawings and energy data, and underserved sectors such as multistoried housing, disadvantaged communities, and schools for which the ML method can enable identification of building asset characteristics and prioritization of envelope retrofits and decentralized energy equipment retrofits.
Singh, Reshma↗
Thermal Energy Storage Using Solid Particles for Long-Duration Energy Storage
The rapid growth of renewable energy increases the importance of economically firming the electricity supply from variable solar photovoltaic- and wind-power generators. Energy storage will be the key to manage variability and to bridge the generation gap over time scales of hours or days for high renewable grid integration. The integration of renewable power and storage of excess electricity has several significant and positive impacts including: 1) expanding the renewable energy portion of total electricity generation, 2) improving the peak-load response, and 3) coordinating the electricity supply and demand over the grid. Long-duration energy storage can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Several energy storage methods are deployed or under development, including mechanical, chemical or electrochemical, and thermal energy storage (TES). Comparing their economic potential for different scales and applications helps identify suitable technology to support high renewable grid integration. Despite the progress of TES technologies developed and deployed with concentrating solar power (CSP) systems, TES has been undervalued for its potential role in electric energy storage. This paper introduces TES methods applicable to grid energy storage and particularly focuses on solid-particle-based TES to serve the purpose of long-duration energy storage (LDES). The objective of this paper is to present a standalone particle-based TES system for electric storage and to show the potential of TES systems for LDES applications over other energy storage methods such as batteries, compressed-air energy storage, or pumped-storage hydropower.
27 ARPA - Advanced Research Projects Agency-Energy↗
Charge Transfer in 2D Halide Perovskites and 2D/3D Heterostructures
Halide perovskites have emerged as a versatile class of materials, with applications spanning photovoltaics, light-emitting diodes, transistors, and photodetectors. The introduction of semiconducting ligands to form two-dimensional (2D) perovskites on the surface of three-dimensional (3D) perovskites in perovskite solar cells has been shown to enhance the performance and stability. To improve the interface properties between the 3D perovskite layer and charge carrier transport layers, understanding the charge transfer (CT) process in 2D perovskites is crucial. In this Perspective, we address common terminological inaccuracies in energy level descriptions, delineate methods for energy alignment characterization, and present practical instances of CT in 2D perovskite-incorporated solar cells. Furthermore, we emphasize the significance of precise terminology, appropriate measurement techniques, and rational design of 2D ligands to harness the full potential of 2D perovskites in optoelectronic applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multielectron Organic Redoxmers for Energy-Dense Redox Flow Batteries
Redox flow battery is a highly promising stationary energy storage method but the limited energy density and high chemical cost are among the main barriers for commercialization. Multi-electron organic redoxmers represent a family of structurally tailorable candidates that can achieve multiplied energy density with decreased materials consumption, potentially resulting in a viable solution to address these challenges. In this work, the recent development of organic molecules with reversible multi-redox activities in both aqueous and nonaqueous electrolytes is reviewed. The major focus is on the fundamental correlation between the chemical structures and the functional properties of reported multi-electron organic molecules. Valuable insights are offered on rational structural design strategies for improving the relevant physico- and electro-chemical properties. Finally, the current challenges are discussed to suggest future research needs along the avenue of using the multi-electron approach to achieve energy-dense, stable, cost-effective redox flow batteries.
25 ENERGY STORAGE↗
Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories
In this work, we present an efficient energy-based method for structural optimization with stochastic electronic structure theories, such as diffusion quantum Monte Carlo (DMC). This method is based on robust line-search energy minimization in reduced parameter space, exploiting approximate but accurate Hessian information from a surrogate theory, such as density functional theory. The surrogate theory is also used to characterize the potential energy surface, allowing for simple but reliable ways to maximize statistical efficiency while retaining controllable accuracy. We demonstrate the method by finding the minimum DMC energy structures of the selected flake-like aromatic molecules, such as benzene, coronene, and ovalene, represented by 2, 6, and 19 structural parameters, respectively. In each case, the energy minimum is found within two parallel line-search iterations. The method is near-optimal for a line-search technique and suitable for a broad range of applications. It is easily generalized to any electronic structure method where forces and stresses are still under active development and implementation, such as diffusion Monte Carlo, auxiliary-field Monte Carlo, and stochastic configuration interaction, as well as deterministic approaches such as the random-phase approximation. Accurate and efficient means of geometry optimization could shed light on a broad class of materials and molecules, showing high sensitivity of induced properties to structural variables.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗