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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 127 records · Page 7

Quinones having high capacity retention for use as electrolytes in aqueous redox flow batteries

We disclose quinone compounds and related species (Formula I) that possess significant advantages when used as a redox active material in a battery, e.g., a redox flow battery. In particular, the compounds provide redox flow batteries (RFBs) with extremely high capacity retention. For example, RFBs of the invention can be cycled for 500 times with negligible loss of capacity, and such batteries could be employed for years of service. Thus, the invention provides a high efficiency, long cycle life redox flow battery with reasonable power cost, low energy cost, and all the energy scaling advantages of a flow battery.

Aziz, Michael J.↗

Energy Storage Cost and Performance Database

In support of the U.S. Department of Energy’s Energy Storage Grand Challenge, Pacific Northwest National Laboratory is applying its rich history of battery research and development to provide the U.S. Department of Energy (DOE) and industry with a guide to current energy storage costs and performance metrics for various technologies. Cost and performance metrics for individual technologies track the following to provide an overall cost of ownership for each technology: cost to procure, install, and connect an energy storage system; associated operational and maintenance costs; and end-of-life costs. These metrics are intended to support DOE and industry stakeholders in making sound decisions about future R&D directions and priorities that move the United States closer to its goal of energy independence. The technologies currently being evaluated are lithium-ion [lithium iron phosphate (LFP) and nickel manganese cobalt (NMC)] batteries, vanadium redox flow batteries, lead-acid batteries, zinc-based batteries, hydrogen energy storage, pumped storage hydropower, gravitational energy storage, compressed air energy storage, and thermal energy storage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy and cost saving results for advanced technology systems from the Cogeneration Technology Alternatives Study (CTAS)

An overview of the organization and methodology of the Cogeneration Technology Alternatives Study is presented. The objectives of the study were to identify the most attractive advanced energy conversion systems for industrial cogeneration applications in the future and to assess the advantages of advanced technology systems compared to those systems commercially available today. Advanced systems studied include steam turbines, open and closed cycle gas turbines, combined cycles, diesel engines, Stirling engines, phosphoric acid and molten carbonate fuel cells and thermionics. Steam turbines, open cycle gas turbines, combined cycles, and diesel engines were also analyzed in versions typical of today's commercially available technology to provide a base against which to measure the advanced systems. Cogeneration applications in the major energy consuming manufacturing industries were considered. Results of the study in terms of plant level energy savings, annual energy cost savings and economic attractiveness are presented for the various energy conversion systems considered.

Sagerman, G. D.↗

Energy and cost savings results for advanced technology systems from the Cogeneration Technology Alternatives Study /CTAS/

The Cogeneration Technology Alternatives Study (CTAS), a program undertaken to identify the most attractive advanced energy conversion systems for industrial cogeneration applications in the 1985-2000 time period, is described, and preliminary results are presented. Two cogeneration options are included in the analysis: a topping application, in which fuel is input to the energy conversion system which generates electricity and waste heat from the conversion system is used to provide heat to the process, and a bottoming application, in which fuel is burned to provide high temperature process heat and waste heat from the process is used as thermal input to the energy conversion system which generates energy. Steam turbines, open and closed cycle gas turbines, combined cycles, diesel engines, Stirling engines, phosphoric acid and molten carbonate fuel cells and thermionics are examined. Expected plant level energy savings, annual energy cost savings, and other results of the economic analysis are given, and the sensitivity of these results to the assumptions concerning fuel prices, price of purchased electricity and the potential effects of regional energy use characteristics is discussed.

Sagerman, G. D.↗

Comparative evaluation of distributed-collector solar thermal electric power plants

Distributed-collector solar thermal-electric power plants are compared by projecting power plant economics of selected systems to the 1990-2000 timeframe. The approach taken is to evaluate the performance of the selected systems under the same weather conditions. Capital and operational costs are estimated for each system. Energy costs are calculated for different plant sizes based on the plant performance and the corresponding capital and maintenance costs. Optimum systems are then determined as the systems with the minimum energy costs for a given load factor. The optimum system is comprised of the best combination of subsystems which give the minimum energy cost for every plant size. Sensitivity analysis is done around the optimum point for various plant parameters.

Fujita, T.↗

The flexible magnetic field thruster

The thruster is designed so that ion currents to various internal surfaces can be measured directly; these measurements facilitate calculations of the distribution of ion currents inside the discharge chamber. Experiments are described suggesting that the distribution of ion currents inside the discharge chamber is strongly dependent on the shape and strength of the magnetic field but independent of the discharge current, discharge voltage, and neutral flow rate. Measurements of the energy cost per plasma ion suggest that this cost decreases with increasing magnetic field strength as a consequence of increased anode shielding from the primary electrons. Energy costs per argon plasma ion as low as 50 eV are measured. The energy cost per beam ion is found to be a function of the energy cost per plasma ion, extracted ion fraction, and discharge voltage. Part of the energy cost per beam ion has to do with creating many ions in the plasma and then extracting only a fraction of them into the beam. The balance of the energy goes into accelerating the remaining plasma ions into the walls of the discharge chamber.

Brophy, J. R.↗

Batteries for storage of wind-generated energy

Cost effectiveness characteristics of conventional-, metal gas-, and high energy alkali metal-batteries for wind generated energy storage are considered. A lead-acid battery with a power density of 20 to 30 watt/hours per pound is good for about 1500 charge-discharge cycles at a cost of about $80 per kilowatt hour. A zinc-chlorine battery that stores chlorine as solid chlorine hydrate at temperatures below 10 C eliminates the need to handle gaseous chlorine; its raw material cost are low and inexpensive carbon can be used for the chlorine electrode. This system has the best chance to replace lead-acid. Exotic alkali metal batteries are deemed too costly at the present stage of development.

Schwartz, H. J.↗

Photovoltaic (PV) System Levelized Cost of Energy (LCOE) Evaluation with Grid Support Function Valuation and Service Lifetime Estimation

Photovoltaic (PV) systems play a critical role in renewable energy resource grid integration, and levelized cost of energy (LCOE) is commonly used to evaluate PV system feasibility in modern power grids. In this work, a revised PV system LCOE calculation model is derived to quantify the potential of LCOE reduction. Particularly, the grid support functions are valuated to offset the investment and operation costs of PV systems, which thereby reduces the LCOE. Meanwhile, PV system service lifetime is also estimated with the derived PV inverter reliability model, considering the critical components (i.e., semiconductor devices and capacitors). The case studies with field datasets are conducted to validate the effectiveness of the developed LCOE calculation model.

Zhao, Shijia↗

Field Performance of Commercial Building Load Flexibility Using Model Predictive Control

Model Predictive Control (MPC) applied to buildings is starting to see some commercial adoption by companies. However, it is hard to estimate if relative energy cost savings are enough to justify the cost of MPC implementation with few reported demonstrations. In small commercial and residential buildings, a one size-fits-all solution can help reduce implementation costs, while in very large buildings or districts the potential energy cost savings magnitude can cover more tailored solutions. This estimation becomes harder for medium to large commercial buildings, where a one-size-fits-all solution cannot be adopted and potential energy cost savings might not be sufficient to cover a tailored solution. Therefore, value propositions in addition to energy efficiency alone can make MPC technology more attractive through additional energy cost savings. One such value proposition is load shifting in response to dynamic electricity prices. On this aspect, MPC is a key technology to unlock building thermal mass for energy flexibility in response to electric grid conditions. This study shows the experimental results of MPC control of an office building in Berkeley, where different dynamic electricity price profiles were used in the MPC objective function to shift the building load and to calculate hypothetical electricity costs. Results show potential 50% cost savings with respect to the existing controller with the dynamic price scenario.

Zanetti, Ettore↗

Catalina Repower Feasibility Study: NREL Phases I & II Summary Report

Engineers at the National Renewable Energy Laboratory (NREL) supported Southern California Edison (SCE) and the United States Environmental Protection Agency (EPA) by conducting technical and economic analyses for energy systems at Santa Catalina (Catalina) Island, which is located 22 miles off the coast of Long Beach, California. This effort was part of a broader Repower Catalina Feasibility Study that was also supported by NV5, an engineering consulting firm and project partner to NREL for this analysis. This document describes NREL’s techno-economic modeling and optimization analysis for the first two phases of this project which focus on supply-side generation and energy storage options for Catalina. SCE’s goal for this analysis is to determine a strategy for electricity generation on Catalina Island that results in lower energy costs, improved energy resiliency, and reduced air emissions. EPA goals for this effort are to reduce emissions of air pollution and encourage renewable energy development on contaminated and formerly contaminated lands when such development is aligned with the community’s vision for the site. Currently, an on-island SCE power plant serves the Catalina Island electrical load with 6 reciprocating diesel generators totaling 9.4 MW; 23 propane-fueled microturbines totaling 1.5 MW; and a 1-MW, 7.2-MWh sodium sulfur battery energy storage system (BESS). In 2017, the electricity consumption on the island was 29.1 GWh, with an average load of 3.3 MW and peak load of approximately 5.5 MW. Considering new environmental standards on diesel generator emissions from California’s South Coast Air Quality Management District, a 60% renewable energy target for 2030 laid out in California’s Senate Bill 100, SCE’s Clean Power Electrification Pathway, and the characteristics of the island’s existing diesel generators, SCE is seeking to evaluate the technical and economic implications of different energy technology options to determine a path forward. Phases I and II of the Repower Catalina Feasibility Study, summarized in this document, evaluated the following: Interconnection with the mainland via an undersea cable; On-island fossil fuel generation, including diesel, propane, and/or liquified natural gas (LNG); On-island renewable energy (RE) technologies, including solar photovoltaics (PV), wind turbines, and wave energy devices; BESS to support the above generation technologies; Initial analysis of the potential impacts of implementing energy efficiency measures. Results indicate strong techno-economic potential for a mix of on-island diesel and/or propane generators, solar PV, BESS, and energy efficiency measures to help SCE and Catalina achieve their goals compliant with California’s emissions and clean energy standards while minimizing electricity life cycle costs (LCC) over the 30-year analysis period. This document summarizes the considerations and findings of Phases I and II, focusing on high-level takeaways from Phase I and more detailed results from Phase II, and discusses a potential path forward for Phase III.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impacts of turbine and plant upsizing on the levelized cost of energy for offshore wind

Turbine and plant upsizing are major trends in offshore wind deployment, although the quantitative impact on project costs has not been well-characterized. The uncertain value of continued wind turbine and project growth limits the ability of the supply chain to prepare for future technology trends, leading to challenges in the realization of larger projects. This analysis explores the levelized cost of energy impacts of turbine ratings between 6 and 20 MW and plant capacities between 250 and 2,500 MW for fixed-bottom offshore wind using techno-economic cost models for foundation, electrical, installation, and operation and maintenance costs, along with annual energy production. We consider a nominal set of technology assumptions for all scenarios to isolate economies of size and scale without additional benefits from decreasing turbine capital costs, quantity discounts for larger projects, or optimized technology solutions. These results indicate that using a 20-MW wind turbine in a 2,500-MW power plant array can reduce the levelized cost of energy by over 23% relative to the global average turbine and plant size installed in 2019; primarily because of reductions in the balance-of-system and operation and maintenance costs. We also identify improved installation vessels, optimized export systems, and novel operation and maintenance strategies as additional cost reduction opportunities. These results suggest that upsizing represents a significant cost reduction opportunity for offshore wind energy and will continue to be a main factor in shaping the future of the sector.

17 WIND ENERGY↗

Two-stage membrane-based process utilizing highly CO 2 -selective membranes for cost and energy efficient carbon capture from coal flue gas: A process simulation study

Membrane technology for CO 2 capture has become an attractive strategy due to its cost and energy efficiency and low materials costs. In the past decade, membrane-based process designs for post-combustion power plant CO 2 capture have been developed, utilizing existing highly CO 2 -permeable membranes with relatively low CO 2 /N 2 selectivity (<50), and have obtained reasonably economic carbon capture. However, few membrane-based process designs were proposed for moderate to highly CO 2 -selective membranes (CO 2 /N 2 selectivity of 50–300, and >300, respectively), which have vastly emerged in recent years, such as various facilitated transport membranes (FTMs). Herein, we proposed a two-stage membrane-base process design targeting economic carbon capture from coal-fired flue gas. This process design features the utilization of highly CO 2 -selective membranes for one-stage CO 2 enrichment to 95% dry-base purity in the first stage and recycle of the remaining CO 2 by a highly CO 2 -permeable membrane in the second stage, in order to achieve economic CO 2 capture with 90% capture rate and >95% CO 2 product purity. Through an integration-iteration membrane model and the Aspen Plus process simulation, a sensitivity study of operating pressures (feed and permeate pressures) and membrane properties (CO 2 permeance and CO 2 /N 2 selectivity) was conducted. Critical CO 2 /N 2 selectivity of 300–400 was found for the highly CO 2 -selctive membranes to meet the demand for cost and energy efficient results. The lowest possible membrane area of 4.8 × 10 5 m 2 and fractional energy of 19.3% were obtained, which is comparable to or even more attractive than reported membrane-based process designs. Here, this work provides a new membrane process design option for highly CO 2 -selective membranes and gives insights on the influence of membrane performance and operation condition.

42 ENGINEERING↗

The zero-emissions cost of energy: a policy concept

The energy sector generates over 70% of global greenhouse gas (GHG) emissions, but existing energy-climate policies do little to reduce GHG emissions to prevent climate change. We present a new carbon tax policy concept in which energy users would be taxed an amount equal to the cost of cleaning up the emissions that they create, wherein the tax revenues would be used to operate negative emissions technologies. The policy is based on applying the zero-emissions cost (ZEC) metric to energy prices, which includes the 'regular' cost of an energy source plus the cost of sequestering its emissions. Using the ZEC, (a) the energy sector would be emissions-neutral, (b) biofuels would be cheaper than petroleum fuels, and (c) renewable electricity would be cheaper than fossil-fuel electricity. We calculate the energy spending as a fraction of gross domestic product for 'regular' and ZEC cost scenarios. Implementing the ZEC carbon-tax policy would enable a monumental shift to a net-zero emissions energy sector, but carries a significant risk of causing an economic recession. The summary point of this commentary is to demonstrate a pathway to achieve net-zero GHG emissions from the US energy sector, and to contemplate the associated economic impacts on our society.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Spatial impacts of technological innovations on the levelized cost of energy for offshore wind power plants in the United States

Recent studies predict significant decreases in the future levelized cost of energy (LCOE) of offshore wind energy, much of which is attributed to anticipated cost reductions from technological innovation. This study evaluates the spatial variability of LCOE caused by technology-induced decreases in a range of capital, operational, and financial cost categories. A spatial cost model of fixed-bottom and floating offshore wind plants is used to model the impact across thousands of potential United States sites. A specified change in an individual turbine subsystem cost produces a range of LCOE outcomes due to the varying geospatial characteristics of the considered sites and the nonlinear, interactive dependency on these input parameters; for example, a 10.8% improvement in net capacity factor can reduce LCOE by between 6% and 20% at different sites. This work expands upon the existing offshore wind literature, which typically evaluates cost sensitivities at a single site and does not consider the spatial variance in LCOE. The results suggest that the impact of technological innovations can be considerable and should be considered on a spatial as well as temporal basis when prioritizing technology innovation research or funding decisions to advance offshore wind technologies in the United States.

17 WIND ENERGY↗

Informing electrification strategies of residential neighborhoods with urban building energy modeling

Electrifying end uses is a key strategy to reducing GHG emissions in buildings. However, it may increase peak electricity demand that triggers the need to upgrade the existing power distribution system, leading to delays in electrification and needs of significant investment. There is also concern that building electrification may cause an increase of energy costs, leading to further energy burden for low-income communities. This study uses the urban scale building modeling tool CityBES to assess the electrification impacts of more than 43,000 residential buildings in a neighborhood of Portland, Oregon, USA. Energy efficiency upgrades were investigated on their potential to mitigate the increase of peak electricity demand and energy burden. Simulation results from the calibrated EnergyPlus models show that electrification with heat pumps for space heating and cooling as well as for domestic water heating can reduce CO2e emissions by 38%, but increase peak electricity demand by about 9% from the baseline building stock. Combining electrification measures and energy efficiency upgrades can reduce CO2e emissions by 48% while reducing peak electricity demand by 6% and saving the median household energy costs by 28%. City and utility decision makers should consider integrating energy efficiency upgrades with electrification measures as an effective residential building electrification strategy, which significantly reduces carbon emissions, caps or even decreases peak demand while reducing energy burden of residents.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal Operation of Residential High Performance Water Heater for Reduction of Electricity Cost and Peak Demand Through Field Validation

Water heating accounts for about 18% of a typical US home’s energy use. Modern water heaters have enabled control options through APIs, offering customers the opportunity to reduce their energy cost and peak demand by dynamically adjusting settings. A water heater’s capacity to store energy using its storage tank makes it an asset for peak demand reduction and energy cost savings. For this reason, a mixed-integer linear programming model is proposed to minimize the energy cost of a high-performance water heater while also reducing the peak demand of the residential household under a time-of-use utility rate by dynamically changing the water heater’s running mode. Specifically, a multi-objective optimization model is formulated to determine the mode settings of the water heater considering hot water use, time-of-use rate, and peak demand limit of the residential household. The mode settings are associated with different dead bands of water temperature for triggering on/off action of the heat pump and heating element. A 66-gal hybrid electric high performance water heater was used for numerical simulation and practical experiments. The simulation results were well aligned with measurements of practical experiments, validating the soundness of the thermodynamic model. In addition, reductions of energy cost, enabling affordability, and reducing peak demand are demonstrated. The research team also developed a software framework with dashboards to automatically and continuously monitor and manage devices.

Liu, Guodong [ORNL] (ORCID:0000000213498608)↗

Assessing uncertainty in the timing of energy use during cost-optimal distributed energy technology selection and sizing

This paper empirically derives uncertainty ranges in cost-optimal solar PV and storage sizing by comparing results from the REopt Lite optimization platform from metered data and a set of simulated Department of Energy Commercial Reference Building (CRB) profiles at 65 sites. We find load profile shape alone does not explain a site’s optimal configurations (i.e., PV, Storage, PV and Storage, No System). Still, load profile shape does introduce uncertainty to optimal PV and storage capacities. Across all cases where PV is part of an optimal configuration, we find the average ratio of power capacities derived from metered loads to capacities derived from CRB profiles to be 0.97 (and as high as 1463), where 1 would be a perfect match in system size. For storage, the ratio is 1.6 (and as high as 42). We also assess how, in the absence of complete metered data, a CRB profile can be selected that would be expected to yield the most similar solar PV and storage capacities. From those metrics that can be available from billing data (i.e., peak demand, monthly load totals), we find that uncertainty is most reduced by selecting the CRB’s with an annual peak occurring at the most similar time, or those with the lowest average root mean square error (RMSE) among monthly peak loads. This research can help improve the implementation and interpretation of results derived from simulated load profiles and is an important next step in advancing smart grid solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ion thruster performance model

A model of ion thruster performance is developed for high flux density, cusped magnetic field thruster designs. This model is formulated in terms of the average energy required to produce an ion in the discharge chamber plasma and the fraction of these ions that are extracted to form the beam. The direct loss of high energy (primary) electrons from the plasma to the anode is shown to have a major effect on thruster performance. The model provides simple algebraic equations enabling one to calculate the beam ion energy cost, the average discharge chamber plasma ion energy cost, the primary electron density, the primary-to-Maxwellian electron density ratio and the Maxwellian electron temperature. Experiments indicate that the model correctly predicts the variation in plasma ion energy cost for changes in propellant gas (Ar, Kr and Xe), grid transparency to neutral atoms, beam extraction area, discharge voltage, and discharge chamber wall temperature. The model and experiments indicate that thruster performance may be described in terms of only four thruster configuration dependent parameters and two operating parameters. The model also suggests that improved performance should be exhibited by thruster designs which extract a large fraction of the ions produced in the discharge chamber, which have good primary electron and neutral atom containment and which operate at high propellant flow rates.

Brophy, J. R.↗