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At least 1,297 records · Page 72

Caprock Remains Water Wet Under Geologic CO 2 Storage Conditions

Abstract Carbon storage technology is primarily targeted in saline formations, which is a porous rock matrix filled with brine, sealed with a low permeability caprock. There are significant variations of CO 2 wetting properties, typically reported in the literature as contact angle of CO 2 and brine interacting with a rock material, suggesting that CO 2 could become wetting under geostorage conditions and negatively impact containment effectiveness. Here, we performed the first controlled laboratory measurements of CO 2 ‐brine contact angles on shale rocks from low permeability sealing formations with distinctive mineralogic properties—calcite‐rich, quartz‐rich, and dolomite‐rich. We targeted temperatures at 40° and 100°C, pressures at 8.3, 34.5, and 62.1 MPa, and salinity at 35,000 and 260,000 ppm. Results show no significant change in contact angle with mineralogy, temperature, pressure, salinity, and CO 2 bubble size. We conclude that caprocks will remain water‐wet at geologic CO 2 storage conditions and will not lose their capillary sealing capacity.

Tapriyal, Deepak↗

Charged Ferroelectric Domain Walls for Deterministic ac Signal Control at the Nanoscale

The direct current (dc) conductivity and emergent functionalities at ferroelectric domain walls are closely linked to the local polarization charges. Depending on the charge state, the walls can exhibit unusual dc conduction ranging from insulating to metallic-like, which is leveraged in domain-wall-based memory, multilevel data storage, and synaptic devices. In contrast to the functional dc behaviors at charged walls, their response to alternating currents (ac) remains to be resolved. Here, we reveal ac characteristics at positively and negatively charged walls in ErMnO 3 , distinctly different from the response of the surrounding domains. By combining voltage-dependent spectroscopic measurements on macroscopic and local scales, we demonstrate a pronounced nonlinear response at the electrode-wall junction, which correlates with the domain-wall charge state. The dependence on the ac drive voltage enables reversible switching between uni- and bipolar output signals, providing conceptually new opportunities for the application of charged walls as functional nanoelements in ac circuitry.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗

Optimal Operation and Impact Assessment of Distributed Wind for Improving Efficiency and Resilience of Rural Electricity Systems

This project aims to empower rural utilities by developing advanced optimization models and algorithms for effectively integrating distributed wind energy alongside battery storage and other distributed energy resources (DERs). The primary objectives are to reduce peak demand, ensure reliable emergency power supply, and regulate voltage and frequency. To address operational challenges, the project introduces innovative mitigation strategies and ultrafast assessment frameworks to evaluate the impacts of distributed wind and DERs on rural grids, offering actionable solutions to potential issues. Economic viability is assessed through cost-benefit analysis using real rural utility data, ensuring the practical application of the project outcomes.

17 WIND ENERGY↗

The Future of Renewable Energy Transmission: An Autonomous Energy Grid

The drastic price reduction in variable renewable energy, such as wind and solar, coupled with the ease of use of smart technologies at the consumer level, is driving dramatic changes to the power system that will significantly transform how power is made, delivered, and used. Distributed energy resources (DERs)—which can include solar photovoltaic (PV), fuel cells, microturbines, gensets, distributed energy storage (e.g., batteries, ice storage), and new loads (e.g., electric vehicles (EVs), light-emitting diode (LED) lighting, smart appliances, and electric heat pumps)—are being added to electric grids and causing bidirectional power flows and voltage fluctuations that can impact optimal control and system operation. Residential solar installations, customer battery systems, and EVs are all seeing rapid increases in deployments. With DER seeing such increased use, it is not unreasonable to imagine a residential electricity customer having at least five controllable DERs. In future electric grids, as more DERs are integrated, the number of active control points will be too much for current control approaches to effectively manage.

30 DIRECT ENERGY CONVERSION↗

Sharing tuples across independent coordination namespace systems

A system and method for federating a tuple storage database across multiple coordinated namespace (CNS) extended memory storage systems allowing the sharing of tuples and tuple data across independent systems. The method provides a federation service for multiple coordination namespace systems. The method retrieves a tuple from connected independent CNS systems wherein a local CNS Controller sends a read request to the local gatekeeper to retrieve a first tuple and creates a local pending remote record. The local gatekeeper at a requesting node sends a broadcast query to a plurality of remote gatekeepers for the tuple and Remote gatekeepers at remote nodes query in its local CNS for the tuple. The Local gatekeeper process at the requesting node receives results from a plurality of remote gatekeepers for the said tuple and selects one remote gatekeeper to receive the requested tuple and broadcasts a read for tuple data with selected gatekeeper.

Jacob, Philip↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

Review of Wave Energy Converter Power Take-Off Systems, Testing Practices, and Evaluation Metrics: Preprint

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continuing proving themselves as a promising modern renewable energy field. One of the difficulties that wave energy systems have been struggling to overcome is the design of highly efficient energy conversion systems that can convert the mechanical power, derived from the oscillation of wave activated bodies, into another useful product. Often the power take-off (PTO) is defined as the single unit responsible for converting mechanical power into another usable form such as electricity, pressurized fluid, compressed air, and others. The PTO, and the entire power conversion chain (PCC), is of great importance as it affects not only how efficient wave power is converted into electricity, but also contributes to the mass, size, structural dynamics, and levelized cost of energy (LCOE) of the wave energy converter (WEC). Unlike wind and solar, there is no industrial standard device, or devices, for wave energy conversion and this diversity is transferred to the PTO system. The majority of current WEC PTO systems incorporate a mechanical or hydraulic drive train, power generator, and an electrical control system. The challenge of WEC PTO designs is designing a mechanical-to-electrical component that can efficiently convert irregular, bi-directional, low frequency and low alternating velocity wave motions. While gross average power levels can be predicted in advance, the variable wave elevation input has to be converted into smooth electrical output and hence usually necessitates some type of energy storage system, such as battery storage, accumulator super capacitors, etc., or other means of compensation such as an array of devices. One of the primary challenges for wave energy converter systems is the fluctuating nature of wave resources, which require WEC components to be designed to handle loads (i.e. torques, forces, and powers) that are many times greater than the average load. This approach requires a much greater PTO capacity than the average power output and indicates a higher cost. In addition, supporting mechanical coupling and or gearing can be added to the PCC to help alleviate the difficulties with transmission and control of fluctuating large loads with low frequencies (indicative of wave forcing) into smaller loads at higher frequencies (optimum for conventional electrical machine design) can quickly increase the complexity of the PCC which could result in a greater number of failure modes and increased maintenance costs. All of the previous points demonstrate how the PTO influences WEC dynamics, reliability, performance and cost which are critical design factors. This paper further explores these topics by providing a review of the state-of-the-art PTO systems currently under development, how these novel PTO systems are tested and derisked prior to precommercial deployment, and the evaluation metrics historically used to differentiate between PTO designs and how they can be improved to support control co-design focused development of wave energy systems.

laboratory testing↗

Operando Investigation on the Role of Densification and Chemo-Mechanics on Solid-State Cathodes

All solid-state batteries are desirable for a range of energy storage applications which require high energy density. Achieving a high energy density in a solid-state battery requires the operation of an energy dense anode with a composite solid-state cathode. Pores and/or voids within a solid state cathode are ion-blocking and thus control over the concentration and distribution of pores in the initial electrode and cycled electrode is desirable. This study provides an understanding of the interplay between electrode microstructure and mechanics on active material utilization in solid state cathodes composed of NCM 811 and Li 6 PS 5 Cl. Decreasing the solid electrolyte particle size leads to greater active material-electrolyte contact and less total deformation when exposed to an external load. Composite cathodes with greater compliance can potentially decrease strain between the active material and solid electrolyte, decrease delamination events and result in higher overall active material utilization and high capacity retention.

25 ENERGY STORAGE↗

Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts

Non-powered dams (NPDs) are dams that do not include hydraulic turbine (hydropower) equipment. Currently, there are more than 80,000 such dams in the United States, which provide a variety of non-energy benefits, including flood control, water supply, navigation, and recreation. Approximately 500 of these NPDs are identified as having the potential to add hydropower generation (totaling up to a capacity of more than 8200 MW). A large share of investment costs and environmental impacts of dam construction have already been incurred at these NPDs. Hence, adding power to the existing dam structure is hypothesized to be achieved at a lower cost, with less risk, and a shorter timeframe than the development required for new dam construction. The abundance of NPDs, the associated environmental favorability, and cost advantages, combined with the reliability, predictability, and dispatchability of hydropower, make NPDs a strong candidate in the nation’s renewable energy portfolio. To assess the NPD to hydropower conversion potential, in this study, we developed a GIS-based multi-criterial decision analysis tool, which allows users to rank these NPDs based on the grid, community, industry, and environmental impacts (i.e., GCIE impacts). This web-based interactive tool (developed using open-source Python and JavaScript) lets the user choose from a wide range of features to define each of the GCIE impact scores through a user-friendly graphical user interface. These features are related to dam operation, hydropower generation opportunity, power market economy, social vulnerability and risk, proximity to critical infrastructure and energy generating facilities, environmental concerns (air, water, and critical habitat), and exposure to natural hazards. The overall priority score of NPDs is calculated based on user-defined weights for each of the GCIE impact scores. Besides ranking NPDs, the tool can also be used to estimate the energy-storage feasibility (battery, hydrogen, and pump-storage hydropower) at each of the potential sites.

13 HYDRO ENERGY↗

Cold-Starting All-Solid-State Batteries from Room Temperature by Thermally Modulated Current Collector in Sub-Minute

All-solid-state batteries (ASSBs) show great potential as high-energy and high-power energy storage devices but their attainable energy/power density at room temperature is severely reduced because of the sluggish kinetics of lithium-ion transport. Here we first reported a thermally modulated current collector (TMCC), which can rapidly cold-start ASSBs from room temperature to operating temperatures (70–90 °C) in less than one minute, and simultaneously enhance the transient peak power density by 15-fold compared to one without heating. This TMCC is prepared by integrating a uniform, ultrathin (~200 nm) nickel layer as a thermal modulator within an ultralight polymer-based current collector. By isolating the thermal modulator from the ion/electron pathway of ASSBs, it can provide fast, stable heat control yet does not interfere with regular battery operation. Moreover, this ultrathin (13.2 μm) TMCC effectively shortens the heat transfer pathway, minimizes heat losses, and mitigates the formation of local hot spots. The simulated heating energy consumption can be as low as ~3.94% of total battery energy. This TMCC design with good tunability opens new frontiers towards smart energy storage devices in the future from the current collector perspective.

25 ENERGY STORAGE↗

Solid State Solar Thermochemical Fuel (SoFuel) for Long Duration Storage

Efficient thermal storage systems, when coupled with renewable energy, enable the decarbonization of numerous industrial processes requiring high temperature steam or air, and provide a path for seasonal building heating, especially for colder climates. Existing thermal storage systems face a significant challenge due to losses inherent to all high temperature systems. A viable route to long-term storage is to use thermochemical reactions to convert concentrated solar energy to a fuel that is shelf-stable and can be stored at room temperature, thus eliminating losses associated with high temperature storage. The Solid-State Solar Thermochemical Fuel (SoFuel) technology developed by Michigan State University, Oregon State University, and Mississippi State University provides reactors and processes with minimal sensible heat losses and allows storing solar energy as a solid-state fuel at room temperature for long duration. The production of SoFuel occurs within a cylindrical cavity reduction chemical reactor that captures concentrated solar radiation from a solar field. Reactive magnesium manganese oxide (Mg-Mn-O) resides within the cylindrical cavity chemical reactor and undergoes thermal reduction as the temperature exceeds 1350°C. The thermally reduced Mg-Mn-O pellets (the SoFuel) are cooled down through a recuperative process and stored within a bin until used. The SoFuel can directly supply up to 1100C heat to an adjacent power plant for electricity generation or industrial heating. Oxidation of SoFuel pellets occurs in a counter flow reactor and supplies heat to the user for electricity generation or industrial processing, after which the fuel is returned to the concentrating solar field where it is regenerated for re-use. Both reactors can be controlled well using a variety of strategies. With the low cost of the material, its cyclability, and the possibility of using the pelletized with on-sun reactors, or with electricity that would be curtailed, this project offers a viable option of medium- and long-term thermal energy storage.

25 ENERGY STORAGE↗

Solid State Solar Thermochemical Fuel (SoFuel) for Long Duration Storage

Efficient thermal storage systems, when coupled with renewable energy, enable the decarbonization of numerous industrial processes requiring high temperature steam or air, and provide a path for seasonal building heating, especially for colder climates. Existing thermal storage systems face a significant challenge due to losses inherent to all high temperature systems. A viable route to long-term storage is to use thermochemical reactions to convert concentrated solar energy to a fuel that is shelf-stable and can be stored at room temperature, thus eliminating losses associated with high temperature storage. The Solid-State Solar Thermochemical Fuel (SoFuel) technology developed by Michigan State University, Oregon State University, and Mississippi State University provides reactors and processes with minimal sensible heat losses and allows storing solar energy as a solid-state fuel at room temperature for long duration. The production of SoFuel occurs within a cylindrical cavity reduction chemical reactor that captures concentrated solar radiation from a solar field. Reactive magnesium manganese oxide (Mg-Mn-O) resides within the cylindrical cavity chemical reactor and undergoes thermal reduction as the temperature exceeds 1350°C. The thermally reduced Mg-Mn-O pellets (the SoFuel) are cooled down through a recuperative process and stored within a bin until used. The SoFuel can directly supply up to 1100°C heat to an adjacent power plant for electricity generation or industrial heating. Oxidation of SoFuel pellets occurs in a counter flow reactor and supplies heat to the user for electricity generation or industrial processing, after which the fuel is returned to the concentrating solar field where it is regenerated for re-use. Both reactors can be controlled well using a variety of strategies. With the low cost of the material, its cyclability, and the possibility of using the pelletized with on-sun reactors, or with electricity that would be curtailed, this project offers a viable option of medium- and long-term thermal energy storage.

14 SOLAR ENERGY↗

Targeted synthesis and reaction mechanism discussion of Mo 2 C based insertion-type electrodes for advanced pseudocapacitors

Mo 2 C is one of the few compounds that possess good electronic conductivity. Meanwhile, it possesses a natural 1D zigzag tunnel structure that is ideally suited for fast ion diffusion. Here, an effective approach is demonstrated for fabrication of structurally stable N-doped Mo 2 C/C nanobelts. They demonstrate high and fast energy storage ability with initial capacitances of 1139 C g -1 at 1 mV s-1, 151 C g -1 at an extremely high scan rate of 2000 mV s -1 and 208 C g -1 at a discharge current density of 200 A g -1 . After electrochemical activation of cycling, the capacity is continuously enhanced and much higher capacitances of 2523 C g -1 at 1 mV s -1 and 1403 C g -1 at 50 A g -1 are achieved after 15,000 cycles at 50 mV s -1 . Using the power law, it is evaluated that a surface-controlled capacitive process makes the main contribution to the capacity, which is over 90% when the scan rates are higher than 10 mV s -1 and still high as 73% at 1 mV s -1 . From in situ synchrotron XRD, it is found that there is a negligible change in the crystal structure and volume during charging/discharging, reflecting an insertion-type charge storage mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗

GridDS: Data Science Toolkit for Energy Grid Data

According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is

Ladd, Alexander↗

Modulating the Surface Ligand Orientation for Stabilized Anionic Redox in Li‐Rich Oxide Cathodes

Abstract Anionic redox chemistry is emerging as a key concept in the development of high‐energy lithium‐ion batteries, as it enables a nearly doubled charge storage capacity, aiding the development of high‐capacity batteries. However, the anionic reactivity is frequently irreversible from charge to discharge, leading to rapid decay of the capacity and voltage of batteries over long‐term cycling. Although the possibility of controlling the anionic redox reactions by tuning the geometric and electronic structures has recently been proposed, the implementation of this strategy is still a critical challenge. Herein, a strategy is proposed to improve the anionic redox reversibility of a model anionic redox active cathode material, Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , by tuning the surface ligand geometry via the growth of a lattice‐compatible spinel LiCoO 2 coating layer on the particle surface. Detailed local structure and first principles investigations reveal that the shape and orientation of the octahedral layer in the host lattice are modified. Accordingly, a two‐band oxygen redox behavior is triggered in the ligand‐orientation‐regulated Li‐rich cathode, leading to enhanced reversibility, and thus, remarkably improved capacity and voltage retention over cycling. This study highlights the importance of controllable ligand orientation, carving a new path for the development and design of Li‐rich cathodes in the future.

Liu, Yanchen↗

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗