Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “charging demand”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coexistence of Merons with Skyrmions in the Centrosymmetric Van Der Waals Ferromagnet Fe 5– x GeTe 2

Fe 5-x GeTe 2 is a centrosymmetric, layered van der Waals (vdW) ferromagnet that displays Curie temperatures T c (270–330 K) that are within the useful range for spintronic applications. However, little is known about the interplay between its topological spin textures (e.g., merons, skyrmions) with technologically relevant transport properties such as the topological Hall effect (THE) or topological thermal transport. Here, via high-resolution Lorentz transmission electron microscopy, it is shown that merons and anti-meron pairs coexist with Néel skyrmions in Fe 5-x GeTe 2 over a wide range of temperatures and probe their effects on thermal and electrical transport. A THE is detected, even at room T, that senses merons at higher T's, as well as their coexistence with skyrmions as T is lowered, indicating an on-demand thermally driven formation of either type of spin texture. Remarkably, an unconventional THE is also observed in absence of Lorentz force, and it is attributed to the interaction between charge carriers and magnetic field-induced chiral spin textures. Here these results expose Fe 5-x GeTe 2 as a promising candidate for the development of applications in skyrmionics/meronics due to the interplay between distinct but coexisting topological magnetic textures and unconventional transport of charge/heat carriers.

two-dimensional magnets↗
DOE OSTI2026

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Machine learning defect properties in Cd-based chalcogenides

Impurity energy levels in the band gap can have serious consequences for a semiconductor's performance as a photovoltaic absorber. Data-driven approaches can help accelerate the prediction of point defect properties in common semiconductors, and thus lead to the identification of potential deep lying impurity states. In this work, we use density functional theory (DFT) to compute defect formation energies and charge transition levels of hundreds of impurities in CdX chalcogenide compounds, where X = Te, Se or S. We apply machine learning techniques on the DFT data and develop on-demand predictive models for the formation energy and relevant transition levels of any impurity atom in any site. The trained ML models are general and accurate enough to predict the properties of any possible point defects in any Cd-based chalcogenide, as we prove by testing on a few selected defects in mixed chalcogen compounds CdTe 0.5 Se 0.5 and CdSe 0.5 S 0.5 . The ML framework used in this work can be extended to any class of semiconductors.

density functional theory↗
DOE OSTI2023

Quantification of Energy Savings and Demand Reduction for a Heat Pump Integrated with Thermal Energy Storage (Final Report)

To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries or installing new peaking power plants. Stakeholders and policy makers across the United States have expressed interests in promoting TES, as demonstrated by the US Department of Energy’s Grid-Interactive Efficient Buildings program and the efforts of various state legislatures. However, the cost value provided by TES are unclear. If reliable cost benefits were determined, stakeholders would have a clearer picture of the financial returns that can be gained from their investment in TES. The study in this report is conducted by ORNL with collaboration with Emerson the Helix Innovation Center. In the first part of this report, EnergyPlus was used to perform whole-building simulations for two residential buildings in Indianapolis and Atlanta. The HVAC system in both buildings were equipped with phase change material TES. The TES tank was charged in off-peak hours and discharged in peak hours to perform load shifting. First, the economic value implied by existing time-of-use (TOU) rates offered by utility companies was analyzed via whole-building simulation. Second, existing demand reduction (DR) incentives sourced from 3 different electrical grid administrators (i.e., California, Texas, and New England region) were surveyed to determine their implied value. The study suggests that the traditional value analysis that focuses on ROI for the building owner significantly undervalues TES technology making economic viability difficult. A more comprehensive value analysis that includes peak demand management and deferred capital for peaking power plants shows that TES should be economically viable but here the value is greater for the utility and requires large market penetration and aggregation to fully realize the benefits. Therefore, to facilitate commercialization, new business models are needed that include a broader range of stakeholders and distribute the value of TES proportionally. In the 2 nd part of this project, the benefits of a novel phase change material (PCM) integrated heat pump configuration were evaluated via detailed component based simulation. A one-dimensional PCM heat exchanger model which discretizes the PCM tank and refrigerant tubes into small control volumes is developed. Each control volume can have different PCM temperatures, PCM properties, and heat transfer coefficients. The PCM tank is charged by a wrapped tank condenser and discharged by an internal refrigerant coil. The PCM heat exchanger model is integrated into DOE/ORNL Heat Pump Design Model for heat pump system simulation. To demonstrate the performance of the PCM integrated heat pump, a case study in Chicago was performed. A Time-of-Use utility structure-based control strategy is implemented to schedule the PCM tank charging and discharging mode switching. Compared with a conventional electric heat pump, the PCM integrated heat pump shows superior performance on load shifting and utility cost reduction. As a result, the proposed system demonstrates 24.6% utility saving for cooling application and 25.8% utility saving for heating application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Battery calendar aging and machine learning

Batteries continue to attract immense attention due to the critical need for new energy technologies that can help humankind transition to a net-zero future. To meet global goals for implementation of new batteries, the research community needs to more coherently consider how to go about the process of innovation, development, and validation of new technologies. Current practices for bringing a new battery technology from the benchtop to deployment can be very time consuming and complex, given that batteries can have distinct aging pathways based on both how they are cycled and their storage conditions. In nearly all use cases, batteries experience periods of active cycling and also extended periods of rest. Thus, calendar time often occurs when a battery is close to fully charged. Currently, the combined cycle and calendar life aspects receive inconsistent attention during most stages of research and development. For batteries to fulfill the critical role envisioned to meet global energy demands, greater uniformity in practice is needed to alleviate potential delays caused by the inconsistent acquisition of aging data. In this study, we present our thoughts and recommendations on the need to further advance commonality and availability of calendar aging data for emerging high-energy and long-duration batteries. While there is a broad need to adopt best practices for both calendar and cycle life assessment, a push to greater uniformity in approach and reporting is sorely needed to allow calendar life predictions to harness many of the advances that have recently been seen for cycle life prediction using machine learning (ML) and other techniques.

25 ENERGY STORAGE↗
DOE OSTI2026

Hofstadter butterfly and quantum transport benchmarks in PVA-exfoliated graphene heterostructures

Polymer exposure during van der Waals heterostructure fabrication is widely regarded as compromising the integrity of the electronic system required for hosting emergent quantum physics. This assumption has persisted largely because electronic benchmarking of heterostructures from polymer-exposed graphene has remained limited to only foundational transport metrics, such as mobility and charge inhomogeneity. Here, we challenge this assumption by establishing that graphene heterostructures produced by polyvinyl alcohol (PVA)-assisted exfoliation and encapsulated in hexagonal boron nitride using elevated-temperature lamination satisfy demanding quantum transport benchmarks. Beyond exhibiting ultra-high mobility and ballistic transport, these heterostructures yield quantum scattering times comparable to the best polymer-free devices. Most demanding of all, moiré superlattices from PVA-exposed graphene exhibit Hofstadter butterfly spectra, confirming spatially uniform interlayer coupling across the device area. These results establish that PVA exposure is compatible with low-disorder electronic systems, relaxing the trade-off between scalable fabrication and low-disorder quantum transport. This study motivates further development of polymer-assisted assembly with engineered residue-removal protocols.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An AFM study of Zn/MnO 2 Co-deposition (ORISE Internship Report)

With the growing demand for rechargeable batteries, the aqueous Zn-ion battery has shown promise as a cheaper and safer alternative to modern Li-ion batteries. Meanwhile, for developing batteries with optimal charge transfer, electrodes with interpenetrating geometries have been explored to minimize the distance traveled by ions in the electrolyte. Creating a Zn-ion battery with interpenetrating electrodes may allow for more efficient cycling, but requires the co-deposition of anode and cathode materials. Because of the highly sensitive nature of electrodeposition, the presence of additional ions may have an impact on the success and homogeneity of cathode/anode deposition, possibly preventing the proper function of an interpenetrating Zn battery. This study examined the effects of added ions on Zn deposition through in situ Atomic Force Microscopy with the goal of determining whether the co-deposition of Zn and MnO 2 is a viable option for electrodes with interpenetrating geometries. Solutions of 1M ZnSO 4 and 1M ZnSO 4 + 0.1M C 4 H 6 MnO 4 were made to simulate normal and co-deposition conditions. Layers of Zn were electrodeposited onto a Cu microelectrode at a current density of 10mA cm -2 with intermittent AFM imaging after 50 deposited monolayers. The presence of manganese acetate (C 4 H 6 MnO 4 ) was found to decrease Zn nucleation size on the Cu UME, suggesting the presence of C 4 H 6 MnO 4 would not negatively impact the co-deposition of Zn and MnO 2 .

25 ENERGY STORAGE↗
DOE OSTI2026

Development of Next Generation Hierarchical Hybrid Cu-Si anode Batteries via Direct-Ink Writing Application: End of (6th) Month Report - November 2025

Sustainable renewable energy continues to be in dire need to effectively combat global warming. Emerging technology for electric vehicles/ devices remains in high demand that is not only lower in cost, more efficient, but safer in comparison to commercial materials on the market. Although first-generation lithium-ion batteries have exhibited extensive commercial application, conventional graphite no longer meets this increasing demand as an efficient anode material. Due to the fact that graphite has a subpar theoretical specific capacity (372 mAh g -1 ), thus significant limitations in rate capability (for potential faster charging at higher C-rates currently commercially available.). Alternatively, silicon has gained significant attention as a superior candidate to potentially surpass graphite. Due to silicon’s exceedingly high theoretical capacity (4,200 mAh g -1 ) in comparison to standard graphite, its abundance thus in turn it’s low-cost, in addition to exhibiting a significantly low working potential (< 0.4 V vs Li/Li + ). However, one of the main (and most detrimental) challenges is silicon’s tendency to expand in volume (> 300%) upon discharge as it begins the lithiation process. As a direct result, it causes not only for the particles to both crack and pulverize under mechanical stress as the volume continues to expand and contract during cycling. Upon assembling the cell, it needs to undergo ‘charging’ for initially discharging/ ‘activating’ the cell, otherwise commonly known as the ‘formation’ step. As a result a solid electrolyte interface (SEI) layer begins to form at the anode surface because some of the electrolyte begins to react during the formation process. However, this (SEI) layer is deemed as a ‘protective’ interlayer because in theory it prevents further reaction as the cell continues to cycle. However, due to the volume change it causes significant degradation at the interface. As cracking starts to occur at the anode surface, it results in a ‘new’ altered surface with each cycle that causes further reaction with the electrolyte as a byproduct quickly consuming active Li/ and more electrolyte. Thus, fracturing this ‘protective layer,’ causing significantly higher impedance as a result, and in turn a decline in capacity due to active Li-loss. In addition to the active material exfoliating off from the current collector, further contributing to the steady decline in capacity and overall performance. Current state of the art Si-anode batteries on the market range between a maximum content of 5-10 Si wt%. It has been previously reported Tesla has utilized SiO x -C anodes containing 5 wt% Si within their ‘Model 3/ Model X’ electric vehicles. However, more recent ‘Model 3’ vehicles have started to incorporate 10 Si wt%, in which they were able to increase their energy density upwards by approximately 30%. Recent effort has been focused on continuing to increase the wt% of Si being utilized, eventually to 100 wt% of Si, to maximize the energy density even further.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗
DOE OSTI2021

Cost targets to achieve commercially viable thermal storage in buildings

To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries or installing new peaking power plants. Stakeholders and policy makers across the United States have expressed interests in promoting TES, as demonstrated by the US Department of Energy’s Grid-Interactive Efficient Buildings program and the efforts of various state legislatures. However, the cost value provided by TES are unclear. If reliable cost benefits were determined, stakeholders would have a clearer picture of the financial returns that can be gained from their investment in TES. In this report, EnergyPlus was used to perform whole-building simulations for two residential buildings in Indianapolis and Atlanta. The HVAC system in both buildings were equipped with phase change material TES. The TES tank was charged in off-peak hours and discharged in peak hours to perform load shifting. First, the economic value implied by existing time-of-use (TOU) rates offered by utility companies was analyzed via whole-building simulation. Second, existing demand reduction (DR) incentives sourced from 3 different electrical grid administrators (i.e., California, Texas, and New England region) were surveyed to determine their implied value. Lastly, the economic value implied by different types of deferred peak power plants were reviewed. The full value of TES to the entire society consists of value to the utility, OEMs, facility installers, and other stakeholders. This report focuses on the value to the utility with emphasis on the deferred capital of peak power plant. The value from the deferred capital of peak power plant is manifested to the customer in the form of demand reduction program and Time-of-Use utility rate program. In this report, an initial proxy of the value of TES is made by assuming the deferred capital cost of power plant is the full value to reduce peak demand. Three levels of financial value of TES systems were assessed. Two are currently available to some residential customers: (1) the benefit from TOU pricing alone and (2) the benefit from TOU pricing in combination with DR incentive programs. The third level was computed as the full cost of deferred capital cost of peaking power plants. This represents the potential value that could be gained by the utilities or conceivably be offered to consumers.

25 ENERGY STORAGE↗
DOE OSTI2022

Implantable photoelectronic charging (I-PEC) for medical implants

Medical implants with functionalities such as sensing, health monitoring, stimulation, diagnosis, and physiological treatment are rapidly growing. With the increasing functional sophistication and addition of modules such as data transmission, on-chip processing, and data storage, energy demand of the implantable system is also growing. Using implantable energy harvester either to recharge or ultimately replace hazardous battery is essential to provide a long-term sustainable solution. Furthermore, energy harvesting techniques using piezoelectric, thermoelectric, radio frequency power transmission, biofuel, and photoelectronic (or sometimes termed as “photovoltaic” in terms of solar light harvesting, i.e., PV) conversion, have been attempted for the implantable, but these methods are currently limited by insufficient power output, large footprint, and low efficiency. Nevertheless, the planar PV with potential of lighter weight, higher energy density, and higher efficiency, provides promising power solution for in-body medical implants. In this short review, we will discuss the potential opportunities and challenges associated with PV's for medical implants, covering materials, to devices, and to system level requirements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Nuclear Science User Facilities: Instrument Scientist Program

The traditional single institution User Facility model prevalent in the DOE complex funds Instrument Scientists (IS) full-time to collaborate with and guide users, disseminate results through publication, build a broad and competent user base, continuously improve instrumentation, enhance data collection methods, and improve data analysis methods. This model focuses the Instrument Scientist on ensuring that visiting researchers obtain the best and most comprehensive data. Instrument Scientists are also expected to establish personal research programs based on the use of the instrument(s) under their charge, which allows for further advances in instrumentation and science. This model ensures that the User Facility offers unique, world-leading instruments and data analysis to the user community, creates high demand among top researchers for the use of these capabilities, and as a result, positively impacts science and technology in the United States.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Treatment of Lagoon Dairy Manure Wastewater via Iron Electrocoagulation, Microfiltration, and Adsorption

Dairy manure wastewater generated by flushing barn cow waste contains nutrients, pathogens, and organic and inorganic contaminants. This study utilized a process consisting of iron electrocoagulation (Fe-EC), microfiltration (MF), and activated carbon (AC) adsorption to treat farm wastewater and explore the reclamation of clean water for irrigation and livestock consumption. Significant removal (>99.9%) of chemical oxygen demand (COD), total organic carbon (TOC), phosphorus (P), turbidity, and microorganisms, as well as ions including magnesium, calcium, sulfur, and silica was achieved by the combined EC-MF-AC process. Specifically, a charge loading of ∼37,500 C/L in a continuous-flow EC configuration, followed by MF, achieved more than 95% removal of TOC and COD. Characterization of produced flocs and foam via scanning-electron microscopy with energy-dispersal spectroscopy and Fourier transform infrared spectroscopy confirmed the removal of ions, including calcium, sulfur, and silica. A key finding was the electrocatalytic conversion of nitrogen species to ammonia gas through the intermediate reduction of nitrate/nitrite, which led to ∼60% total nitrogen (TN) removal. AC treatment further improved TN removal to ∼70%. The Fe-EC process also eradicated >99.9% of bacteria. Preliminary process cost assessment, based on recycled materials for EC electrodes, showed significant cost savings (∼2 times) compared to commercial electrodes.

Dutta, Swapnamoy [ORNL]↗
DOE OSTI2022

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↗
DOE OSTI2022

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↗
DOE OSTI2022

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↗
DOE OSTI2021

Minimizing Oxygen Permeability in Chitin/Cellulose Nanomaterial Coatings by Tuning Chitin Deacetylation

The demand for packaging materials with low gas permeabilities is increasing, but commonly used petroleum-derived single-use plastics are not renewable, biodegradable, or easy to recycle. Nanomaterials composed of chitin and cellulose, which are abundant in nature, have high crystallinities and low oxygen permeabilities (OP), providing a viable alternative. In this work, we explore how deacetylation conditions of crab shell chitin can be used to tune the charge and size of resulting chitin nanowhiskers (ChNWs) and the resulting OP of layered film structures. Three deacetylation factors, the concentration of sodium hydroxide (%NaOH), temperature (T), and reaction time, were explored using a three-factor three-level Taguchi design with an orthogonal array. Furthermore, the resulting ChNW suspensions were sequentially spray-coated with suspensions of cellulose nanocrystals (CNCs) onto cellulose acetate (CA) films to form a multilayer structure. We show that ChNWs prepared under more aggressive deacetylation conditions inside the original orthogonal array (higher %NaOH, T, and time) had shorter lengths but the surface charge was significantly influenced only by more aggressive deacetylation outside of the original design conditions. With only ~10% decrease in the ultimate tensile strength and no significant loss in failure strain, the ChNW-CNC coating resulted in ~20% decrease in WVTR in comparison to uncoated CA films. The optimization of process conditions resulted in CA-ChNW-CNC films with a 91-99% decrease in OP (132-16.7 cm 3 ∙μm/m 2 /day/kPa versus 1553 cm3∙μm/m2/day/kPa for uncoated CA).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Combined Cycle Integrated Thermal Energy Storage “CiTES” (Final Scientific/Technical Report)

The Phase I of this project confirmed the technical feasibility of a Combined Cycle integrated Thermal Energy Storage “CiTES” system, calculated the key performance parameters like power efficiency and costs, and proved its commercial value with full-year simulations for several US electricity markets with high degree of variable renewable generation and volatile hourly electricity prices. The core element of this project is the Electro Thermal Energy Storage (ETES) technology from Siemens Gamesa Renewable Energy GmbH, using thermally stable and inexpensive volcanic rocks as storage material and air as heat transfer medium. This technology is backed by more than 10 years of experience and a 440MMBTU (130MWh-th) pilot plant in Hamburg, Germany, which is in operation since 2019. The integration of this thermal storage in an existing combined cycle power plant (CCPP) is typical power plant technology without any major technology risks. It allows the storage of inexpensive renewable energy during times of surplus renewable generation and the discharge of this energy in times of high energy demand when the fossil plant is in operation. This supplements the fossil power generation with CO2-emission-free energy. The secondary effect of the CiTES system is that a small part of the stored thermal energy is used to keep the heat recovery steam generator (HRSG) and steam turbine (ST) of the combined cycle power plant in hot and ready-to-start condition. This enables the plant to start rapidly when fossil generation is required to satisfy demand as soon variable generation drops off in the evenings or during cloud cover and calm wind periods. Without pre-warming of the HRSG and ST, the CCPP would need several hours for a cold or warm start, burn a lot of gas and release high NOx emissions during start and wouldn’t be able to use the short times of high energy prices in an efficient or economical manner. The economic parameters of CiTES were determined by a full year “8760” simulation using a data set calculation for each of the hours of the year, and historical electricity and gas prices. For consistency, the simulations were focused on the pre-COVID year 2019. The financially most attractive markets were in the Energy Reliability Council of Texas (ERCOT) region, which allowed substantial value generation with arbitrage (charge with cheap energy during renewable surplus times and discharge when energy is needed and expensive). The improvement of flexibility with the CiTES system by pre-heating and warm-keeping of the CCPP allowed for additional power generation during short time periods when demand is high but renewable generation is down; when the hourly energy prices are highest in these markets. The simulations are based on 2019 data, when ERCOT had 27GW of installed photovoltaic (PV) and wind generation. They showed that the created revenue with the prototypically sized CiTES system of 1,000MMBTU (300MWh-th) falls a little bit short of what is expected from a commercially viable investment. The system has optimization opportunities for cost reduction and increased effectiveness which will be realized during a potential Phase II Pre-FEED study following this project. Furthermore, it is safe to assume that a lot of renewable generation capacity will be added all over the US in the coming years. As an example, ERCOT is predicting to more than double its renewable generation from 27GW in 2019 to a forecasted 63GW in 2023. This will increase the amount of renewable overproduction exponentially. This rapid increase of local overproduction and the need to curtail renewable generation is well documented by the California ISO (www.CAISO.com / managing oversupply). However, the simulations also revealed a weakness in the structure of the electricity markets in the US. More specifically, when electricity prices are very low and approaching negative levels, the owners of Variable Renewable Energy (VRE) will curtail a part of their facility to stabilize the price by reducing supply. This results in a situation in which storage facilities, which are integrated in existing fossil assets and don’t have the behind-the-meter benefit of a VRE, won’t be able to purchase low cost – otherwise curtailed – renewable energy off the grid. A special tariff, which motivates VRE owners to sell otherwise curtailed renewable energy to storage facilities (Hydrogen, thermal, pumped hydro, etc.) can solve this issue. The implementation of such a regulating tariff by Independent System Operators, thus avoiding renewable curtailment, is a pre condition for successful commercialization for renewable energy storage technologies. With this advancement of design and technology and improvements in the market environment, it can be expected that the Combined Cycle integrated Thermal Energy Storage proves itself as an important innovation to keep highly efficient, natural gas-based power generation economically successful and relevant for the power industry in the United States of America.

Wolf, Thorsten↗