Search NASA⌕ Search

SEARCH · Search NASA

Results for “efficiency supply curves”

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.

41 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimizing Hydronic Heating for Comfort and Performance in Multifamily Housing

Inefficient control settings in multifamily boilers often lead to substantial energy and cost penalties. To address this, a Fault Detection and Diagnostic (FDD) tool was developed to automate data analysis and identify operational faults such as suboptimal outdoor temperature sensor placement, misconfigured outdoor air reset (OAR) curves, excess boiler cycling, and domestic hot water (DHW) setpoint errors. By comparing pre- and post-implementation periods and applying engineering models, the tool quantifies energy savings and reduces manual analysis time by over 90%. Testing on over 100 monitored sites and a targeted subset of 12 buildings showed an average 11% energy savings from remote optimization; further validation across 19 OAR curve changes confirmed the tool’s accuracy, predicting actual savings within ±5% for most cases. Simple payback can be under three years for many multifamily buildings, though rising hardware, labor, and fuel costs create uncertainties, and decarbonization goals increasingly shift focus to electrification. The FDD tool remains invaluable for optimizing existing boilers, enhancing future electrification measures, and adapting to new technologies by refining building load estimates. In doing so, it supports both near-term efficiency and long-term transitions to low-carbon alternatives, ensuring buildings achieve substantial cost and energy benefits throughout their system lifecycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Ad-Mat: Adaptations of Mature Manufacturing Strategies for Accelerated Redox Flow Battery Deployment

The concept of the Ad-Mat approach is to leverage existing adjacent markets across a broad scope of technologies in order to reduce the manufacturing learning curve and ultimately accelerate redox flow battery (RFB) deployment at scale. Lithium-ion batteries (LIBs) are currently the dominant energy storage technology, and they came to technological maturity under unique market conditions when there was no meaningful competition in the consumer electronic and electric vehicle (EV) space. Today, alternative chemistries that may be technologically better-suited for long-duration storage applications are experiencing a high barrier to entry. This is in large part due to the substantial bias towards the scaled-up production and supply chain that now exists for LIBs. In the case of RFBs in particular, numerous analyses have suggested that RFBs should theoretically have a much lower system cost than LIBs - however, this relies on a mature and competitive manufacturing landscape, which has been extremely challenging to achieve for both flow batteries and other LIB competitors. At the moment, LIB alternatives tend to have isolated small-scale manufacturing pathways, which preclude the economies of scale that would be required to compete with the mature LIB industry. In the present state of the industry, niche manufacturing tools and approaches have evolved to support each alternative technology, such that there is substantial replication and duplication in effort. Continuing to pursue a strategy of isolated manufacturing processes/approaches for each LIB-alternative may never allow for at-scale deployment. In order for RFBs to meaningfully compete with LIBs in the realm of LDES, a new disruptive approach based on cross-industry learning and coordination is needed - and this is exactly what our Ad-Mat concept aims to tackle. In this re-envisioned manufacturing landscape, tools and processes from mature industries can be adapted and deployed across the range of alternative energy storage technologies. Adapting tools, equipment, processes, and industrial learning from mature industries to meet the technological requirements of RFBs would open new markets for existing OEMs in adjacent industries, would prevent unnecessary duplication and re-development, would improve efficiency across the manufacturing chain, and would ultimately support reduced costs and accelerated deployment of RFBs at scale.

adaptive manufacturing↗
DOE OSTI2022

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗
DOE OSTI2022

Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States. Final Report on HydroWIRES Project D1: Improving Hydropower and PSH Representations in Capacity Expansion Models

Pumped storage hydropower represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24-GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio (Cole et al. 2021; Frazier et al. 2021). However, it is unclear how much potential the United States has for the development of new PSH. No new large PSH has been constructed in the United States since the 1990s, and attempts to quantify technical potential capacity from PSH project applications to the Federal Energy Regulatory Commission (FERC) suffer from inconsistent site and cost evaluation methodologies and likely are not representative of all PSH opportunities. This study seeks to better under understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. Individual sites are not modeled in sufficient detail for project-level development, but they do provide valuable insights into potential resource areas across the United States, including the ability to provide estimates for a range of long-term development scenarios.

13 HYDRO ENERGY↗
DOE OSTI2025

Application of Raman Spectroscopy to Determine Uranium Content in ADUN Solution

The work presented in this report is part of the ongoing efforts to address the nuclear material control and accounting needs for advanced reactor fuel fabrication facilities. This work was supported by the Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy Office of Nuclear Energy‘s Nuclear Fuel Cycle and Supply Chain program. The activities and engagements under the MPACT program are designed to support a robust US civilian nuclear energy enterprise. In the work described in this report, we supported MPACT objectives by developing measurement techniques that could be used for material accounting and process monitoring and by working with industry partners to identify existing gaps and areas for improvement. Oak Ridge National Laboratory has been working with commercial tristructural isotropic (TRISO) fuel fabricators such as Standard Nuclear to develop technology for rapid and cost-effective uranium content assessment. This work has focused on demonstrating advanced measurement techniques (e.g., Raman spectroscopy) that can be used for rapid, reliable, and cost-effective routine measurements of uranium content in feed solutions and liquid waste streams as well as for monitoring in-line process measurements and product streams. Specifically, this report explores techniques for accurately determining uranium content in acid-deficient uranyl nitrate (ADUN) solutions and detecting low uranium concentrations in ammonia solutions. Developing such measurement techniques will benefit TRISO fuel fabrication facilities, facilities involved in other parts of the fuel cycle that require online monitoring of aqueous solutions, and potentially molten salt fuel reactors. This work supports developing Raman spectroscopy procedures to determine uranium concentrations in ADUN solutions, which are used as feedstock in the sol–gel process for creating TRISO fuel. Some additional benefits of using Raman spectroscopy for uranium quantification in fabrication facilities include enabling online monitoring of the chemical process, which would provide near real-time feedback; eliminating the need for sample transfers, preparation, or dilution; providing nondestructive measurements; and user friendliness. In this fiscal year, FY25, we determined the identity of the unknown Raman band at approximately 853 cm−1 that was discovered in ADUN Raman spectra in FY24, created calibration curves and determined uranium concentrations of two ADUN solutions, and compared the Raman results to results obtained from inductively coupled plasma mass spectrometry and Davies–Gray titration. Furthermore, we have identified focus areas for experimentation in future fiscal years. A key result is that the accuracy of using Raman can provide accuracy comparable to destructive analysist techniques, With a well-developed calibration curve, using standards and a large number of samples (more than five samples), uncertainty on the order of 1%–3% is achievable. Given that the uncertainties achieved by Raman spectroscopy were on the order of the uncertainties achieved using ICP-MS, we conclude that with a well-developed procedure Raman spectroscopy can be used to determine uranium concentrations in ADUN solutions for NMC&A applications. The benefits of such an approach are that the time and effort will be less than that of comparable destructive analysis techniques, with approximately the same level of technical expertise. This will be attractive to operators of fuel fabrication facilities as it will lower costs and improve efficiencies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗