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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Practical and thermodynamic constraints on electromicrobially accelerated CO 2 mineralization

By the end of the century, tens of gigatonnes of CO 2 will need to be removed from the atmosphere every year to maintain global temperatures. Natural weathering of ultramafic rocks and subsequent mineralization reactions can convert CO 2 into ultra-stable carbonates. Although this will draw down all excess CO 2 , it will take thousands of years. CO 2 mineralization could be accelerated by weathering ultramafic rocks with biodegradable lixiviants. We show that if these lixiviants come from cellulosic biomass, this demand could monopolize the world’s biomass supply. We demonstrate that electromicrobial production technologies (EMP) that combine renewable electricity and microbial metabolism could produce lixiviants for as little as $\$200$ to $\$400$ per tonne at solar electricity prices achievable within the decade. We demonstrate that EMP could make enough lixiviants to sequester a tonne of CO 2 for less than $\$100$. This work highlights the potential of this approach and the need for extensive R&D.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Techno-economic and life cycle analysis of synthetic natural gas production from low-carbon H 2 and point-source or atmospheric CO 2 in the United States

Synthetic natural gas (SNG) is of great interest in reducing fossil energy consumption while maintaining compatibility with existing NG infrastructure and end-use applications equipment. SNG can be produced using clean H 2 generated from renewable or nuclear energy and CO 2 captured from stationary sources or the atmosphere. In this study, we develop an engineering process model of SNG production using Aspen Plus® and production scales reported by the industry. We examine the levelized cost and life cycle greenhouse gas (GHG) emissions of SNG production under various CO 2 supply scenarios. Considering the higher cost of H 2 transportation compared with CO 2 transportation, we assume that CO 2 feedstock is transported via pipeline to the H 2 production location, which is collocated with the SNG plant. We also evaluate the cost of CO 2 captured from the atmosphere, assuming the direct air capture process can occur near the SNG facility. Depending on the CO 2 supply chain, the levelized cost of SNG is estimated to be in the range of $\$45–76$ per million British thermal units (MMBtu) on a higher heating value (HHV) basis. The SNG production cost may be reduced to $\$27–57$/MMBtu-HHV by applying a tax credit available in the United States for low-carbon H 2 production (45V). With a lower electricity price of 3¢/kWh for water electrolysis and accounting for a 45V tax credit, the SNG cost reaches parity with the cost of fossil NG. Depending on the CO 2 supply chain, SNG can reduce life cycle GHG emissions by 52–88% compared with fossil NG.

03 NATURAL GAS↗
DOE OSTI2023

Electrolyzer energy dominates separation costs in state-of-the-art CO 2 electrolyzers: Implications for single-pass CO 2 utilization

In low-temperature CO 2 electrolysis, a fundamental trade-off exists between maximizing electrolyzer performance and minimizing downstream CO 2 recovery. Here, by coupling a down-the-gas-channel electrolyzer model with a techno-economic analysis, we find that the optimal single-pass CO 2 conversion for ethylene production is typically low—on the order of 5%–10%—although larger optima are found if the H 2 faradic efficiency is very low. Similarly, strategies for eliminating carbonate crossover require more energy than downstream gas separation if they increase the cell potential by ~0.2 V; however, when CAPEX are accounted for, this “break-even” voltage increases to ~ 0.4 to 0.8 V for electricity prices varying from 6c/kWh to 1.5c/kWh. These findings are a consequence of the low energy requirements of industrial gas separation relative to electrochemical CO 2 reduction. Under most circumstances, maintaining near-optimal electrolyzer performance is more important than reducing or eliminating downstream gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The "Perfect Storm" for Distributed Wind Markets

Close to 1 GW of distributed wind has been installed across all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Yet the number of installations varies greatly by state, even when wind resources are similar. This article examines three key factors that over the past thirteen years have shown to be enablers of success for distributed wind installations in the United States: 1) favorable policy environments, including consistent incentives, administrative support for cutting through red tape, and favorable interconnection, net metering, and permitting policies; 2) high electricity prices that would be displaced by wind energy generation, and, 3) favorable wind resources, enabling steady production of energy. Not all conditions need to be met simultaneously, yet of the studied markets for distributed wind in Iowa, New York, Washington, and Oregon, the most successful ones exhibit at least two out of the three conditions mentioned. We describe steps that policymakers, regulators, and market players have taken in the past to increase distributed wind installations in the United States.

Foster, Nikolas AF↗
DOE OSTI2022

Pathways of clean energy heating electrification programs for reducing carbon emissions in Northwest China

We report clean energy heating electrification programs provide a promising way to reduce carbon emissions from fossil fuel combustion and consumption. This work studies the cost competitiveness of clean energy heating technologies under three dynamic mechanisms: investment costs, subsidy policies, and operating costs with real data. It provides key insights into the cost competitiveness of the different heating technologies deployed in different areas, as well as their sensitivity to the three dynamic mechanisms. The results show that currently, the distinct heating programs are more cost-efficient in the urban area with existing heating networks. The average payback period of all district clean energy heating programs in the urban area is 14.9 years, while that of the individual clean heating programs is 24.7 years. The individual heating programs are becoming increasingly cost-competitive with the incentive mechanisms, especially the electricity pricing mechanisms. Moreover, individual heating technologies present remarkable advantages on flexibility and sustainability in the long run. According to the technology diffusion model proposed in this paper, the individual clean heating programs will occupy more than 50% of the market share in 2050 under the comprehensive effect of CAPEX, government subsidies, and OPEX. The real-world results and analysis render references to shape the pathway of clean energy heating electrification in Northwest China and other regions with a similar situation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimization of Operating Profit for the FEED of the PZAS Process for CO 2 Capture on a 460 MW NGCC

A rating model of PZAS (Piperazine with the Advanced Stripper) for a 460 MW natural gas combined cycle was developed from vendor-provided equipment performance data. Surrogate rating models were built and used to optimize variable profit of the system subject to natural gas and electricity price at a fixed value for CO 2 of $\$80$/tonne. Several process constraints were considered between ambient temperatures of 4.4 and 40.5 °C. Lower lean loading resulted in lower reboiler heat duty of about 2.2 GJ/tonne. Lean loading at 0.2 mol/equiv N was sufficient at an ambient temperature of 4.4 °C to maximize variable profit. Solvent precipitation was avoided even at low lean loading (0.18 mol/mol) in the absence of a trim cooler for the lean solvent between the absorber and the cold cross exchanger. Optimal CO 2 removal was always higher than the design case removal of 90% and achieved a peak of 93.6% for 4.4 ºC ambient temperature. Lean solvent rate was a significant driver of profitability. The maximum capacity of the compressor was a significant constraint on profitability. Increasing compressor capacity by 20–30% could increase variable profit by about 21% in the case of 0.18 lean loading at 4.4 °C ambient temperature. Furthermore, this increase in profit was lower at higher ambient temperature and higher lean loading. The breakeven gas price was $\$4.6$/MMBtu at high lean loading of 0.22 mol/mol. Below this value, profit was maximized by increasing the boiler heat rate. Above this value, profit could not be increased by burning additional natural gas, requiring a reduction in boiler heat rate and consequently, specific heat duty. At lower lean loading (0.2, 0.18 mol/mol), this transition in heat duty was not observed due to the lower heat duty. As the ambient temperature increased, a similar trend in heat duty was observed at 0.22 lean loading, but the transition to lower heat duty occurred earlier at $\$4$/MMBtu. This was because of the lower CO 2 production at higher ambient temperature, making the process unprofitable at a gas price higher than $\$3$/MMBtu unless the heat duty of the stripper and natural gas boiler is steeply decreased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimizing Desalination Operations for Energy Flexibility

Despite the value of energy optimization in desalination processes, modeling dynamic operations for monthly billing periods has remained a computational challenge. This work proposes a framework for energy flexibility optimization, which includes new modeling features for independent operation of parallel skids, start-up delays associated with chemical stabilization, the consideration of industrial energy tariff structures, and inclusion of hourly electrical carbon intensities. This is done using a modular and computationally efficient formulation that guarantees a globally optimal solution with standard optimization solvers. In this study, the approach is demonstrated in two distinct case studies: a seawater desalination plant in Santa Barbara, CA, and an indirect potable reuse facility in San Jose, CA. Trends predicted from the model are validated against operational facility measurements from a demand response shutdown event. Preliminary results show that optimizing energy flexibility can result in 18.51% monthly cost savings over energy efficiency-optimized operation. The value extracted from a facility-wide shutdown during peak electricity price hours is hampered by start-up delays in post-treatment chemical stabilization. In cases in which a facility does not have much excess capacity, using a flow equalization tank or operating over a wide recovery range may be cost-effective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The value of long-duration energy storage under various grid conditions in a zero-emissions future

Long-duration energy storage (LDES) is a key resource in enabling zero-emissions electricity grids but its role within different types of grids is not well understood. Using the Switch capacity expansion model, we model a zero-emissions Western Interconnect with high geographical resolution to understand the value of LDES under 39 scenarios with different generation mixes, transmission expansion, storage costs, and storage mandates. We find that a) LDES is particularly valuable in majority wind-powered regions and regions with diminishing hydropower generation, b) seasonal operation of storage becomes cost-effective if storage capital costs fall below US$\$$5 kWh −1 , and c) mandating the installation of enough LDES to enable year-long storage cycles would reduce electricity prices during times of high demand by over 70%. Given the asset and resource diversity of the Western Interconnect, our results can provide grid planners in many regions with guidance on how LDES impacts and is impacted by energy storage mandates, investments in LDES research and development, and generation mix and transmission expansion decisions.

25 ENERGY STORAGE↗
DOE OSTI2026

Evaluating technology upgrades as a complement to traditional bill assistance programs

State programs to improve energy affordability and reduce energy burden (the share of income spent on energy) could mitigate concerns about rising electricity prices. Many states offer bill assistance and rebates for weatherization and rooftop solar to income-qualifying households. Here, we analyse how these approaches may complement one another to improve energy affordability. Results illustrate trade offs between program costs and energy burden reduction, as well as between a program’s upfront and ongoing costs. Generally, the three strategies complement one another to improve energy affordability at lower net present cost than bill assistance alone, with varying effects across regions. Weatherization can reduce the solar installation capacity needed, and both together can reduce or eliminate ongoing reliance on bill assistance. Under full uptake among cost-effective households, fully rebated weatherization and solar rebated at $0.48/Watt, combined with bill assistance, yield the same modelled net present cost as bill assistance alone while reducing the share of low-income owner-occupied households with high energy burdens from 66% to 19%, compared with 34% under bill assistance alone. Absent tax credits, weatherization still reduces energy burden and bill assistance program costs, whereas solar may not be cost-competitive.

Forrester, Sydney P↗
DOE OSTI2024

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO 2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

09 BIOMASS FUELS↗
DOE OSTI2024

Market optimization and technoeconomic analysis of hydrogen-electricity coproduction systems

Decarbonization efforts across North America, Europe, and beyond rely on variable renewable energy sources such as wind and solar, as well as alternative fuels, such as hydrogen, to support the sustainable energy transition. These advancements have prompted a need for more flexibility in the electric grid to complement non-dispatchable energy sources and increased demand from electrification. Integrated energy systems are well suited to provide this flexibility, but conventional technoeconomic modeling paradigms neglect the time-varying dynamic nature of the grid and thus undervalue resource flexibility. In this work, we develop a computational optimization framework for dynamic market-based technoeconomic comparison of integrated energy systems that coproduce low-carbon electricity and hydrogen (e.g., solid oxide fuel cells, solid oxide electrolysis) against technologies that only produce electricity (e.g., natural gas combined cycle with carbon capture) or only produce hydrogen. Our framework starts with rigorous physics-based process models, built in the open-source Institute for the Design of Advanced Energy Systems (IDAES) modeling and optimization platform, for six energy process concepts. Using these rigorous models and a workflow to optimally design each technology, the framework is shown to be capable of evaluating new and emerging technologies in varying energy markets under a plethora of future scenarios (i.e., renewables penetration, carbon tax, etc.). Ultimately, our framework finds that solid oxide fuel cell-based coproduction systems achieve positive profits for 85% of the analyzed market scenarios. From these market optimization results, we use multivariate linear regression (R 2 values up to 0.99) to determine which electricity price statistics are most significant to predict the optimized annual profit of each system. The proposed framework provides a powerful tool for directly comparing flexible, multi-product energy process concepts to help discern optimal technology and integration options.

08 HYDROGEN↗
DOE OSTI2022

Robust Solution Approach for Bilevel Demand Response Game at Distribution Level

In this paper, a bilevel electricity pricing and demand response game between a distribution system operator (DSO) and load aggregators (LAs) is considered, and a robust decision model is proposed for the DSO to deal with the uncertainties from the wholesale market prices and demand consumptions of LAs. With the max-min objective at the upper level, the robust bilevel model is converted into a single level model by the Karush-Kuhn-Tucker (KKT) conditions and prime-dual transformation. Several groups of experiments have been conducted based on different preferences on uncertainty gaps and peak load reductions to show its effectiveness. After-the-fact scenario analysis has indicated that the robust solution is more beneficial in reducing the risk of inaccurate predictions as compared to the risk neutral strategy.

Chen, Yang↗
DOE OSTI2026

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗
DOE OSTI2021

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗
DOE OSTI2021

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗
DOE OSTI2021

Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Feb. 2021 Electricity Blackouts and Natural Gas Shortages in Texas

An extreme winter storm and extended cold weather event hit Texas and the central United States February 8–19, 2021. This led to both exceptional energy demands and issues with electricity and natural gas supplies over several days. Residential space heating drove the increases in demand, with over 60% of Texas homes using electric heat pumps and 35% using natural gas furnaces. Supply issues were caused by freezing equipment and supply lines, impacting both natural gas supplies and most forms of electricity generation. [1] Natural gas supplies were especially important because natural gas also supplied about 50% of the electricity generating capacity in ERCOT, the primary grid operator in Texas. [2] Due to the supply shortages, wholesale electricity prices were forced to the ERCOT maximum of $\$9,000$ /MWh for over three days (recent range $\$20$–40/MWh), [3] and natural gas prices for physical delivery exceeded $\$400$ /MMBtu in some areas (recent range $\$3$–4/MMBtu). [4]

03 NATURAL GAS↗