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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

behind-the-meter↗
DOE OSTI2025

Modeling distributed energy resource aggregations in security constrained unit commitment and economic dispatch

The Federal Energy Regulatory Commission (FERC) recently issued Order 2222, which requires all wholesale electricity markets in the US to allow distributed energy resources (DERs) to participate in the market as aggregated resources. These DER aggregations may be composed of many individual resources that are offered and dispatched by the market as a single entity. We present here a model of a distributed energy resource aggregator (DERA) that is scheduled by a market operator’s security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED). The DERA model includes constraints for battery energy storage systems (BESSs), demand response resources (DRRs), and a simple distributed energy resource (DER). This paper describes a model for each resource type and presents two methods for the DERA to generate market offer curves: a profit-maximizing optimization to compute cost curves and a direct cost algorithm to determine dispatch costs for each resource and combine into cost curves. Once all participating DERAs are scheduled in SCUC/SCED, the model is then modified to dispatch individual DERs to maximize profit or minimize schedule deviation of the DERAs. A simulation of a representative day illustrates the DERA offers, the scheduled generation, and the DERA dispatch. Findings show the potential for unavoidable schedule deviations due to internal DER constraints and due to economic incentives to deviate from the SCUC/SCED schedules. This highlights the importance of DERA offer construction on market efficiency and system reliability. Novel aspects of our approach include: (1) We consider the asymmetry of price incentives impacting DERAs from the wholesale market compared to those impacting consumers from the retail market, as imposed by current regulations and laws. (2) We model aggregate consumer response through statistically parameterizable utility functions rather than a potentially impractical approach of modeling each individual consumer. (3) We show how to use the DERA operational dispatch model to create offers into the wholesale electricity market. (4) We show how DERAs may fail to meet their scheduled dispatch because the market offer format may not permit them to fully express their operational features such as intertemporal costs and constraints to the market.

aggregations↗
DOE OSTI2022

Lithium-Ion Battery Design for Grid-Scale Energy Storage App

A software that delivers parameters from energy storage system (ESS) to container, rack, module and single cell design, as well as data analysis on arbitrage energy and frequency regulation of ESS in different regions, has been developed. The Lithium-ion Battery Design for Grid-scale Energy Storage App V1.0 has the capability to output the system, module and cell design with the energy, power, capacity, group method, cost of single cell, and single cell test protocol which break down from input energy storage system data in different regions. The default chemistry of the battery is LiFePO4 and graphite. The energy density of the graphite/LiFePO 4 pouch cell ranges from 100 Wh/kg to 200 Wh/Kg in the software. Graphite/LiFePO 4 pouch cell (up to 1Ah in lab) manufacturing line is also built and can be used to evaluate the test protocol, moreover, for electrolyte evaluation in other ESMI seedling projects. The software enables rapid prototyping to accelerate energy storage research, development, and manufacturing.

Liu, Dianying↗
DOE OSTI2022

The Economic Impact of Battery Degradation Modelling Uncertainty

Battery energy storage systems (BESS) are used for a variety of applications, with their economic benefit often being the decisive factor for deployment. A multitude of physico-chemical aging mechanisms lead to capacity fade over a BESS life cycle. The models that are used to describe this capacity fade are prone to inherent model errors. Through a holistic techno-economic modelling approach, we investigate the impact of battery degradation modelling uncertainty on the economic benefit of representative BESS applications. Here, it is shown how improved parameter fit quality can reduce the resulting economic uncertainty. Furthermore, we highlight that the consideration of degradation modelling uncertainty is especially crucial when: (i) the cash flow highly depends on the available battery capacity, (ii) a fixed, e.g. warranty mandated, state of health limit acts as the threshold for battery end-of-life, (iii) long evaluation periods and low discount rates are the focus of economic evaluation.

aging↗
DOE OSTI2022

Rolling Optimization of Transmission Network Recovery and Load Restoration Considering Hybrid Wind-Storage System and Cold Load Pickup

A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.

chance-constrained optimization↗
DOE OSTI2020

Environmental and economic optima of solar home systems design: A combined LCA and LCC approach

Here, we compare the economic and environmental optimal design of Solar Home Systems (SHSs) and explore the role of economic incentives (such as tariffs and technology costs) in approximating the two optima. To achieve that, we present a methodology for the environmental and economic evaluation of grid-connected SHSs: user-scale electric systems involving a photovoltaic (PV) power system and a battery energy storage system. The proposed methodology is based on a mixed integer linear programming (MILP) optimization, life cycle assessment and life cycle costing. This methodological framework is applied to a case study involving a typical SHS installation in Italy. The results of the environmental optimal design brought to the evaluation of a 3.25 kW PV assisted by 8.66 kWh of nickel cobalt manganese batteries, whereas the costs of the SHS are minimized by a small PV system (less than 1 kW). Results underline that the environmental optimal configurations rely on battery technologies, which entails a significant cost compared to the grid connection. In contrast, the economic optimal design solutions is less impactful than the grid mix both from an environmental and economic points of view. Thanks to a reduction of batteries and PV costs, the environmental impact of the economic optimal design is expected to decrease in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Utility-Scale Shared Energy Storage Deployment: Challenges, Research Gaps, and Opportunities

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

Gautam, Mukesh [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2023

Distributed Wind-Hybrid Microgrids with Autonomous Controls and Forecasting

Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services - all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.

ancillary services↗
DOE OSTI2022

Lewis Acid Site Assisted Bifunctional Activity of Tin Doped Gallium Oxide and Its Application in Rechargeable Zn‐Air Batteries

The enhanced safety, superior energy, and power density of rechargeable metal‐air batteries make them ideal energy storage systems for application in energy grids and electric vehicles. However, the absence of a cost‐effective and stable bifunctional catalyst that can replace expensive platinum (Pt)‐based catalyst to promote oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) at the air cathode hinders their broader adaptation. Here, in this work, it is demonstrated that Tin (Sn) doped β‐gallium oxide (β‐Ga 2 O 3 ) in the bulk form can efficiently catalyze ORR and OER and, hence, be applied as the cathode in Zn‐air batteries. The Sn‐doped β‐Ga 2 O 3 sample with 15% Sn (Sn x =0.15 ‐Ga 2 O 3 ) displayed exceptional catalytic activity for a bulk, non‐noble metal‐based catalyst. When used as a cathode, the excellent electrocatalytic bifunctional activity of Sn x =0.15 ‐Ga 2 O 3 leads to a prototype Zn‐air battery with a high‐power density of 138 mW cm −2 and improved cycling stability compared to devices with benchmark Pt‐based cathode. The combined experimental and theoretical exploration revealed that the Lewis acid sites in β‐Ga 2 O 3 aid in regulating the electron density distribution on the Sn‐doped sites, optimize the adsorption energies of reaction intermediates, and facilitate the formation of critical reaction intermediate (O*), leading to enhanced electrocatalytic activity.

Lewis acid sites↗
DOE OSTI2022

Intercalation of Ca into a Highly Defective Manganese Oxide at Room Temperature

The utilization of oxide frameworks as intercalation cathodes for non-aqueous Ca-ion batteries potentially unlocks a new energy storage system that delivers high energy density. However, the slow kinetics of Ca 2+ in oxide electrodes strongly handicaps their activity and reversibility at room temperature. Here, nanocrystals of layered MnO x containing a high concentration of atomic defects and lattice water are shown to have remarkable electrochemical activity towards Ca 2+ , amounting to a capacity of ~130 mAh/g at room temperature. Multimodal characterization revealed the notable degree of intercalation by probing the structural, compositional and redox changes undertaken by the defective MnO x nanocrystals. The results suggest that the existence of atomic defects and lattice water played a role in improving Ca 2+ diffusivity in the oxide. These outcomes reaffirm the prospects for functional Ca-ion batteries using oxide cathodes under moderate conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

AnisONet: A deep neural operator-based anisotropic permeability upscaler from pore to Darcy scale

Directional permeability variations, which govern directional fluid flow in porous media with anisotropy, are important to accurately predict flow behavior, reactive transport, and fluid–solid interactions for various processes such as enhanced geothermal systems, energy storage devices, and biological systems. However, the intricate architecture of porous media makes it difficult to predict directional permeabilities. In this work, we present a novel machine learning (ML) framework, AnisONet, built upon an integration of a convolutional neural network, Swin transformer, and the deep operator network architecture, designed to predict anisotropic permeability and upscale predictions to larger spatial domains. First, AnisONet was evaluated with three classes of two-dimensional (2D) porous media, including synthetic circular and elliptical grains and natural sandstone grains from micro-computed tomography images. A lattice Boltzmann model (LBM) was used to calculate directional permeabilities at every 10° angle, producing 19 data points per image of porous media. AnisONet is then trained to predict permeability as a function of rotation angle. AnisONet showed strong predictive capability of directional permeability. Second, we tested our model for five upscaling cases with a large image size in the finite-element method (FEM) for 2D Darcy flow with various permeability tensor construction methods. Overall, upscaled permeability tensors in FEM simulations produce a reasonably good match with LBM results, highlighting the importance of selecting appropriate tensor formation strategies for accurate permeability upscaling. AnisONet, as a directional permeability estimator, could be further developed for more complex geometries, with the potential to develop a foundational ML model for various applications in porous media.

42 ENGINEERING↗
DOE OSTI2024

Performance and Durability of Hybrid Fuel Cell Systems for Class-8 Long Haul Trucks

Hybrid fuel cell-battery configurations are investigated that overcome thermal management issues in fuel cell powertrains for heavy-duty Class 8 trucks. The battery is sized so that it has sufficient capacity to provide supplemental power and energy on a hill climb transient at end-of-life. A dynamic load sharing strategy is developed to distribute the power demand between the fuel cell system (FCS) and the energy storage system in a manner that optimizes their lifetimes. The FCS end-of-life is identified as the terminal point beyond which the stack cannot generate the rated power with target power density at 0.7 V and 40 °C ambient temperature. Reaching the target lifetime with a-Pt/C cathode catalyst in one hybrid configuration requires voltage clipping to 813 mV, idle power limited to 50 kW, catalyst overloading to 0.45 mg cm -2 total Pt in anode and cathode, and 44% active membrane area oversizing. The stack and FCS drive cycle efficiencies decrease by 4.2% and 5.4%, respectively, during the electrode lifetime. Further, the FCS performance, durability and cost are compared with the targets of 68% peak efficiency, 0.30 mg cm -2 total Pt loading, 2.5 kW/g PGM Pt group metal (PGM) loading, 750 mW cm -2 power density, 25,000-h lifetime and $80/kW cost.

33 ADVANCED PROPULSION SYSTEMS↗