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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 325 records · Page 18

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗

STS-114: Discovery Crew Arrival

George Diller of NASA Public Affairs narrates the STS-114 Crew arrival at Kennedy Space Center aboard a Gulf Stream aircraft. They were greeted by Center Director Jim Kennedy. Commander Eileen Collins introduced each of her crew members and gave a brief description of their roles in the mission. Mission Specialist 3, Andrew Thomas will be the lead crew member on the inspection on flight day 2; he is the intravehicular (IV) crew member that will help and guide Mission Specialists Souichi Noguchi and Stephen Robinson during their spacewalks. Pilot James Kelly will be operating the shuttle systems in flying the Shuttle; he will be flying the space station robotic arm during the second extravehicular activity and he will be assisting Mission Specialist Wendy Lawrence during the other two extravehicular activities; he will be assisting on the rendezvous on flight day three, and landing of the shuttle. Commander Collins also mentioned Pilot Kelly's recent promotion to Colonel by the United States Air Force. Mission Specialist 1, Souichi Noguchi from JAXA (The Japanese Space Agency) will be flying on the flight deck for ascent; he will be doing three spacewalks on day 5, 7, and 9; He will be the photo/TV lead for the different types of cameras on board to document the flight and to send back the information to the ground for both technical and public affairs reasons. Mission Specialist 5, Charles Camada will be doing the inspection on flight day 2 with Mission Specialist Thomas and Pilot Kelly; he will be transferring the logistics off the shuttle and onto the space station and from the space station back to the shuttle; He will help set up eleven lap tops on board. Mission Specialist 4, Wendy Lawrence will lead the transfer of logistics to the space station; she is the space station arm operator during extravehicular activities 1 and 3; she will be carrying the 6,000 pounds of external storage platform from the shuttle payload bay over to the space station; she is also in charge of the shuttle storage. Mission Specialist 2, Stephen Robinson is the flight engineer of the shuttle; he will be doing spacewalks with Mission Specialist Noguchi; he will set up the 11 lap top computers on board. Each crew member gave a brief message to the press. Commander Eileen later gave her final message and the crew walked back to the Astronaut Corps.

Source record↗

Design and experimental testing of a 150 kWh thermal battery using thermosiphons embedded in a concrete matrix for power plant flexible operation

One of the options for achieving the global temperature limitation of 1.5 °C target, for the mitigation of global warming, is based on the better penetration of renewables into the electrical grid. This has imposed a burden to fossil fuel fired power plants since they are required to operate away from their baseload mode to compensate for the inherent intermittence of the renewable power. Integrating energy storage with fossil plants is an option to achieve their needed flexibility. A cost competitive energy storage option for the solution is based on storing sensible heat in concrete. Here, this paper reports research results and development of a thermal battery cell (TBC) capable of operating at temperatures up to 425 °C. A novel concept consisting of a concrete matrix for sensible heat storage, engineered to provide enhanced thermal and mechanical properties, and twenty-two thermosiphon elements, engineered for dual action were designed and fabricated into a single thermal energy storage (TES) module. Research for the development of the components for the TBC was performed in the laboratory. Efficient heat transfer, to/from the storage media, was demonstrated under several charging and discharging conditions with a thermal storage capacity of 150 kWh th and a rapid discharge, making the TBC suitable for fast ramping when integrated with a fossil fuel fired power plant. Efficient radial heat transfer to the concrete was observed due to the well designed spacing and location of thermosiphons in the radial direction. A minimal temperature difference of 2 °C, between the thermosiphons bottom and top was obtained, demonstrating the isothermicity of those elements. An overall end-to-end TBC energy-to-energy round trip efficiency of 70% was achieved.

25 ENERGY STORAGE↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich data challenges existing data storage and access technologies, therefore precluding informatics advancements. Here we present MZA™ (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed by a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and efficient programmatic access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System for energy harvesting and/or generation, storage, and delivery

A device and method for harvesting, generating, storing, and delivering energy to a load, particularly for remote or inaccessible applications. The device preferably comprises one or more energy sources, at least one supercapacitor, at least one rechargeable battery, and a controller. The charging of the energy storage devices and the delivery of power to the load is preferably dynamically varied to maximize efficiency. A low power consumption charge pump circuit is preferably employed to collect power from low power energy sources while also enabling the delivery of higher voltage power to the load. The charging voltage is preferably programmable, enabling one device to be used for a wide range of specific applications.

Trainor, John T.↗

System for energy harvesting and/or generation, storage, and delivery

A device and method for harvesting, generating, storing, and delivering energy to a load, particularly for remote or inaccessible applications. The device preferably comprises one or more energy sources, at least one supercapacitor, at least one rechargeable battery, and a controller. The charging of the energy storage devices and the delivery of power to the load is preferably dynamically varied to maximize efficiency. A low power consumption charge pump circuit is preferably employed to collect power from low power energy sources while also enabling the delivery of higher voltage power to the load. The charging voltage is preferably programmable, enabling one device to be used for a wide range of specific applications.

Trainor, John T.↗

Quantification of Dead Lithium on Graphite Anode under Fast Charging Conditions

A series of computational and experimental studies were conducted to understand the onset of lithium plating and subsequent quantification of dead lithium on graphite electrodes in the design of fast charging batteries. The experiments include titration and relaxation studies for detecting initiation of lithium metal plating for various SOC and C-rates, which are compared against the thermodynamically consistent phase field computational results. The collaborative study on "model graphite electrode" with 2.18 mAh cm-2 nominal capacity at 25 degrees C demonstrates: (1) the macroscopic voltage response during relaxation studies indicate the reintercalation of plated lithium into the graphite anode; (2) for SOC below 60% and low C-Rates, there is no dead lithium; (3) for SOC between 60% to 80%, and C-Rates in the range of 4C-6C show dead lithium both in experiments and simulations; (4) at 100% SOC and 4C-6C rates, large amounts of dead lithium are observed. The study presented here allows us to evaluate the effects of the physical properties of the electrochemical system on plating and stripping kinetics and the amount of dead lithium on graphite electrodes, which determines the cell capacity loss under fast charge.

batteries↗

Effect of thermal environments on fast charging Li-ion batteries

Battery thermal management systems (BTMSs) are expected to keep the battery temperature at a moderate level (~30 °C) to minimize the thermally exacerbated degradation. However, during fast charging, a strong cooling system is required to restrict the temperature rise of Li-ion batteries (LiBs), which significantly increases the cost and weight of battery packs, and induces a large temperature variation inside the battery. Here, in this work, we find that all these drawbacks could be relieved by allowing LiBs to charge at higher temperatures. Since the fast charging of a LiB only takes a tiny fraction of its lifetime, the aging rate is limited even at a charging temperature of 60 °C. Three types of thermal environments are proposed: kept constant at 30 °C, preheated to 60 °C, and adiabatic fast charging. With an experimentally validated electrochemical-thermal (ECT) coupled model, we explore the interplay between thermal management and the fast-charging performance. It is found that a gradually increasing temperature profile is the best option to balance the lithium plating and thermal management of the battery. Combining adiabatic fast charging with a preheating step, we can achieve minimal cooling need, perfect temperature uniformity within a battery, and fast-charging capability simultaneously.

25 ENERGY STORAGE↗

High Capacity Adsorption—Dominated Potassium and Sodium Ion Storage in Activated Crumpled Graphene

In this study, structurally and chemically defective activated-crumbled graphene (A-CG) is employed to achieve unique synergy of large reversible potassium (K) and sodium (Na) ion storage capacity with fast charging and extended cyclability. A-CG synthesis consists of low temperature spraying of graphene oxide slurry, followed by partial reduction annealing and air activation. For K storage, the reversible capacities are 340 mAh g -1 at 0.04 A g -1 , 261 mAh g -1 at 0.5 A g -1 , and 210 mAh g -1 at 2 A g -1 . For Na storage, the reversible capacities are 280 mAh g -1 at 0.04 A g -1 , 191 mAh g -1 at 0.5 A g -1 , and 151 mAh g -1 at 2 A g -1 . A-CG shows a stable intermediate rate (0.5 Ag -1 ) cycling with both K and Na, with minimal fade after 2800 and 8000 cycles. These are among the most favorable capacity—rate capability—cyclability combinations recorded for potassium-ion battery and sodium-ion battery carbons. Electroanalytical studies (cyclic voltammetry, galvanostatic intermittent titration technique, b -value) and density functional theory (DFT) reveal that enhanced electrochemical performance originates from ion adsorption at various defects, such as Stone–Wales defects. Moreover, DFT highlights enhanced thermodynamic stability of A-CG with adsorbed K versus with adsorbed Na, explaining the unexpected higher reversible capacity with the former.

25 ENERGY STORAGE↗