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At least 613 records · Page 34

Optimal Wind Turbine Design for H2 Production

NREL and industrial partners GE and Nel seek to advance affordable green hydrogen production by optimizing wind turbine design specifically for hydrogen production and validating designs using NREL's ARIES facilities. This project will couple wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources. It will then use gradient-based optimization with exact-analytic gradients to optimize wind turbine rotor diameter, hub height, and power rating for optimal hydrogen production. Finally, it will validate the optimal turbine designs using the ARIES research platform, where it will compare a baseline turbine to the optimal design for a variety of scenarios and resources.

electrolyzer↗

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗

A Comprehensive Review and Qualitative Analysis of Micro-Combined Heat and Power Modeling Approaches

Concurrent production of electrical and thermal energy from a Combined Heat and Power (CHP) device is an attractive tool to address the growing energy needs of the planet. Micro CHP (µCHP) systems can reduce a building’s primary energy consumption, reduce carbon footprint, and enhance resiliency. Modeling of the µCHP helps understand the system from multiple perspectives and helps discover errors earlier, improves impact analysis and simulation of system solutions for ease of integration with the building. Consequently, there is a need for analysis of the impact of µCHP modeling approach on its reliability and flexibility. The primary objective of this paper is to review the state-of-the art models in the µCHP space with a focus towards internal combustion engine as the primary mover (PM) and limit the study to system modeling, calibration, and validation methodologies. Based on the analysis, recommendations for further model considerations and refinements are presented.

42 ENGINEERING↗

Evolution of Energy Efficiency Programs Over Time: The Case of Standby Power

Issued in 2001, Presidential Executive Order 13221 directed federal agencies to purchase products with low standby power, with the goal of 1) reducing energy consumption in federal facilities, and 2) drawing attention to the problem of high standby power consumption, with guidance provided by the Federal Energy Management Program (FEMP). At that time, standby power was newly recognized as an increasing building energy load. Since then, procurement of products with low standby power have been set in place in acquisition processes, and the purchasing power of the federal government continues to influence manufacturers’ design decisions related to standby power. In recent years, FEMP has shifted effort from direct manufacturer outreach for data collection, to integrating low standby requirement into broader acquisition programs including Energy Star and Electronic Product Environmental Assessment Tool (EPEAT). Another milestone has been the labeling of low standby products on the GSA Advantage website to simplify and enhance compliance. Looking forward into the program’s future, this question arises “How do we design programs over time to reflect market and technology changes, by adjusting programmatic requirements while maintaining effectiveness?” This paper discusses that question for the case of standby power, which transitioned from covering a single to multiple environmental attributes, both in the context of the program’s past and future.

Payne, CT↗

Pro2R: Procurement of Ramping Product and Regulation in CAISO Using Probabilistic Solar Power Forecasts

This presentation summarizes the objectives and findings from the project titled, "Pro2R: Coordinated Procurement of Ramping Product & Regulation in CAISO Using Probabilistic Solar Power Forecasts," funded by DOE SETO. The goal is to develop cutting edge probabilistic solar power forecasting methods, and integrate them into ISO market operations. The team has integrated in two ways: 1) to procure ramping product and regulation requirements (ancillary services) in the California ISO market, and 2) to develop an open source visitation and ramp alert related situational awareness using probabilistic forecasts. This deck also summarizes the results from the use of machine learning methods to relate probabilistic solar forecasts to the the needs for flexible ramp product in the California ISO system.

41 EE - Solar Energy Technologies Office (EE-4S)↗

TEAMER: Water Tunnel Data from Testing the Pterofin Skimmer Concept

Pterofin's Skimmer concept relies on a flapping and pitching hydrofoil to extract hydrokinetic energy from water flows. The concept aims to utilize unsteady fluid dynamics phenomena (added mass, shed vorticity, and unsteady boundary layer development) to achieve higher lift coefficients, enabling increased power density of the hydrokinetic device and a fundamental shift in the rpm/torque scaling of the power take off compared with turbines. The Applied Research Laboratory at Penn State, in collaboration with Pterofin, designed and built a proof-of-concept flapping/pitching mechanism which was subsequently tested in ARL's 12-inch water tunnel facility. The mechanical power supplied to or extracted from the mechanism was measured for a range of hydrofoils provided by Pterofin over operating conditions including reduced frequency, Reynolds number, and the ratio between pitching and flapping amplitudes. The power lost to friction in the mechanism was removed from the net power measurement by means of a bare hub tare, with the resultant hydrodynamic power being used to calculate a mechanism-independent and non-dimensional power coefficient. The product of this effort is a dataset describing the power coefficient of a hydrofoil having simultaneous pitching and flapping motions, both of which are approximately sinusoidal. Power coefficients were collected for a range of primary design variables including: - Reduced frequency: 0.01 to 0.95 - Pitching/flapping peak angle ratio: 1.5 to 3.0 - Chord-based Reynolds number: 60,000 to 560,000 Secondary design variables relating to the hydrofoil geometry were explored including: - Aspect ratio - Planform shape - Section thickness distribution - Hydrofoil position relative to the pitching axis - Hydrofoil sweep angle relative to the pitching axis Measured data are provided in mean and time series formats. MATLAB scripts are provided which can be used to generate figures of time-averaged and phase-averaged hydrodynamic power coefficients calculated from the measured data. A complete description of the experiment and data reduction can be found in the Post Access Report for the Pterofin Skimmer test effort which will be available on the TEAMER website. This work was supported by the Pacific Energy Ocean Trust via a TEAMER award.

16 TIDAL AND WAVE POWER↗

Solar-driven liquid metal magnetohydrodynamic generator

A solar oven heated by concentrated solar radiation as the heat source of a liquid metal magnetohydrodynamic (LMMHD) power generation system is proposed. The design allows the production of electric power in space, as well as on Earth, at high rates of efficiency. Two types of the solar oven suitable for the system are discussed.

Lee, J. H.↗

Valve Packing

"S Glass" yarn was originally developed by NASA for high temperature space and aeronautical applications. When John Crane, Inc. required material that would withstand temperatures higher than 1,200 degrees Fahrenheit, they contacted Owens-Corning, which had developed a number of applications for the material. John Crane combines the yarn with other components to make Style 287-I packing. The product can be used in chemical processing operations, nuclear power stations, petroleum products, etc. Advantages include increased service life and reduced maintenance costs.

Source record↗

Dual-mode Propulsion System Enabling Cubesat Exploration of the Solar System

It is apparent the cost of planetary exploration is rising as mission budgets are declining. Currently small scientific beds geared to performing limited tasks are being developed and launched into low earth orbit (LEO) in the form of small-scale satellite units, i.e., CubeSats. These micro- and nano-satellites are gaining popularity among the university and science communities due to their relatively low cost and design flexibility. To date these small units have been limited to performing tasks in LEO utilizing solar-based power. If a reasonable propulsion system could be developed, these CubeSat platforms could perform exploration of various extra-terrestrial bodies within the solar system engaging a broader range of researchers. Additionally, being mindful of mass, smaller cheaper launch vehicles (~1,000 kg to LEO) can be targeted. This, in effect, allows for beneficial exploration to be conducted within limited budgets.Researchers at the Center for Space Nuclear Research (CSNR) are proposing a low mass, radioisotope-based, dual-mode propulsion system capable of extending the exploration realm of these CubeSats out of LEO.The proposed radioisotope-based system would leverage the high specific energies [J/kg] associated with radioisotope materials and enhance their inherent low specific powers [W/g]. This is accomplished by accumulating thermal energy from nuclear decay within a central core over time. This allows for significant amounts of power to be transferred to a flowing gas over short periods of time. In the proposed configuration the stored energy can be utilized in two ways: (1) with direct propellant injection to the core, the energy can be converted into thrust through the use of a converging-diverging nozzle and (2) by flowing a working fluid through the core and subsequent Brayton engine, energy within the core can be converted to electrical energy. The first scenario achieves moderate ranges of thrust, but at a higher Isp than traditional chemical-based systems. The second scenario allows for the production of electrical power, which is then available for electric-based propulsion. Additionally, once at location the production of electrical power can be dedicated to the payload's communication system for data transfer. Ultimately, the proposed dual-mode propulsion platform capitalizes on the benefits of two types of propulsion methods the thrust of thermal propulsion ideal for quick orbital maneuvers and the specific impulse of electric propulsion ideal for efficient interplanetary travel. Overall, the system is functioning as a radioisotope thermal rocket (RTR).In this study the RTR concept is being developed as an in-space propulsion system to deliver a 6U CubeSat payload to the orbit of the Saturnian moon - Enceladus. Additionally, this study will develop an entire mission architecture for Enceladus targeting a total allowable launch mass of 1,000 kg.

Cubesats↗

Towards Integrated Pulse Detonation Propulsion and MHD Power

The interest in pulse detonation engines (PDE) arises primarily from the advantages that accrue from the significant combustion pressure rise that is developed in the detonation process. Conventional rocket engines, for example, must obtain all of their compression from the turbopumps, while the PDE provides additional compression in the combustor. Thus PDE's are expected to achieve higher I(sub sp) than conventional rocket engines and to require smaller turbopumps. The increase in I(sub sp) and the decrease in turbopump capacity must be traded off against each other. Additional advantages include the ability to vary thrust level by adjusting the firing rate rather than throttling the flow through injector elements. The common conclusion derived from these aggregated performance attributes is that PDEs should result in engines which are smaller, lower in cost, and lighter in weight than conventional engines. Unfortunately, the analysis of PDEs is highly complex due to their unsteady operation and non-ideal processes. Although the feasibility of the basic PDE concept has been proven in several experimental and theoretical efforts, the implied performance improvements have yet to be convincingly demonstrated. Also, there are certain developmental issues affecting the practical application of pulse detonation propulsion systems which are yet to be fully resolved. Practical detonation combustion engines, for example, require a repetitive cycle of charge induction, mixing, initiation/propagation of the detonation wave, and expulsion/scavenging of the combustion product gases. Clearly, the performance and power density of such a device depends upon the maximum rate at which this cycle can be successfully implemented. In addition, the electrical energy required for direct detonation initiation can be significant, and a means for direct electrical power production is needed to achieve self-sustained engine operation. This work addresses the technological issues associated with PDEs for integrated aerospace propulsion and MHD power. An effort is made to estimate the energy requirements for direct detonation initiation of potential fuel/oxidizer mixtures and to determine the electrical power requirements. This requirement is evaluated in terms of the possibility for MHD power generation using the combustion detonation wave. Small scale laboratory experiments were conducted using stoichiometric mixtures of acetylene and oxygen with an atomized spray of cesium hydroxide dissolved in alcohol as an ionization seed in the active MHD region. Time resolved thrust and MHD power generation measurements were performed. These results show that PDEs yield higher I(sub sp) levels than a comparable rocket engine and that MHD power generation is viable candidate for achieving self-excited engine operation.

Litchford, Ron J.↗

Methods for the photochemical utilization of solar energy

The paper considers the 'ground rules' which govern the efficiency of photochemical solar energy conversion and then summarizes the most promising approaches in each of three categories: photochemically assisted thermal systems for the heating and/or cooling of structures; photogalvanic systems for the production of electrical power in applications, such as photorechargeable batteries or inexpensive 'solar cells'; and photochemical formation of fuels for combustion and for use as chemical feedstocks or foods. Three concepts for the photochemical utilization of solar energy in space are found to be particularly promising: (1) photochemical trans-cis isomerization of indigold dyes for photoassisted heating or cooling, (2) the redox stabilized photoelectrolysis cell for the production of hydrogen (and/or oxygen or other useful chemicals), and (3) the liquid-junction photovoltaic cell for the production of electrical power.

Schwerzel, R. E.↗

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Life cycle assessment of biochar produced from forest residues using portable systems

Forest fires are getting extreme and more frequent because of increased fuel loads in the forest and extended dry conditions. Fuel treatment (i.e., thinning) methods to mitigate forest fires will generate large volumes of forest residues together with available logging residues that can be used to produce biochar. It has been proposed that portable biochar systems are economical means to utilize forest residues as an alternative to slash burning. In this study, the environmental impacts of biochar produced from forest residues using three portable systems [1. Biochar Solutions Incorporated (BSI), 2. Oregon Kiln, and 3. Air-curtain Burner] were evaluated using a cradle-to-gate life-cycle assessment approach. Environmental impacts were analyzed considering the various quality of feedstock, biomass collection methods, different production sites, and various sources of power used in the production of biochar. The results illustrate that the global warming potential (GWP) of biochar production from forest residues through BSI, Oregon Kiln, and Air-Curtain Burner were 0.25–0.31, 0.11, and 0.16 tonne CO 2 eq./tonne of fixed carbon in biochar respectively. Compared to pile burn, biochar production from forest residues with a portable system at the landing, reduced global warming potential (GWP) by 1.92–2.83, 2.7, and 1.9 tonnes CO 2 eq./tonne of biochar through BSI, Oregon Kiln, and Air-Curtain Burner respectively. The Air-Curtain Burner and Oregon Kiln have minimal feedstock preparation, thus have lower environmental impacts than the BSI system. The BSI system requires feedstock preparation and power to operate the system. The use of the biomass-gasifier generator improved the environmental performance substantially (16–280%) compared with a diesel generator in biochar production. Overall, the net GWP in biochar produced (0.10–1.63 tonne CO 2 eq./tonne of residues) from forest residues can reduce environmental impacts (2–40 times lower net CO 2 eq. emissions) compared to slash burning.

54 ENVIRONMENTAL SCIENCES↗

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗

Application of FARM to an IES scenario within the FORCE ecosystem

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON software module in the evaluation of the optimal dispatch by evaluating feasible set-points for the different IES unit components. Set-points are required to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). This problem is addressed by adopting a two-stage approach. First, the HERON power dispatcher determines set-points that meet the constraints on the former variables (e.g., power levels and power ramp rate limits). These constraints are called explicit constraints. Then, FARM adjusts these set-points to ensure the respect of the limits on the latter variables given the knowledge of the system physics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). The original version of the FARM software module (FARM-Alpha) was released by Argonne National Laboratory in January 2021. In the latest version of the code released in July 2022 (FARM-Delta), the Reference Governor (RG) algorithm was upgraded to a Multi-Input Multi-Output version from its original Single-Input Single-Output form. The RG algorithm acts to enforce constraints. With this improvement an IES unit is now treated as a single dynamic system from the standpoint of control. The crosstalk among components in an IES unit is now fully considered thereby ensuring a true optimization is obtained for those units that have multiple set-points. In this report, the capabilities of FARM-Delta operating within the FORCE ecosystem are demonstrated for an IES test case. The specific configuration of IES unit for this case was selected by the IES team with consultation from the Advanced Reactor IES Expert Group. A full TEA analysis that invoked HERON, HYBRID, FARM, and RAVEN was performed and serves to demonstrate how the latest modification to FARM algorithms (i.e., state variable selection, state-space matrices derivation, set-point verification) can shape setpoints that might otherwise compromise the health of equipment through accelerated wear and tear. In this specific test case, it was demonstrated that these algorithms ensure a more efficient utilization of steam resources to be shared by two different subsystems, namely Balance of Plant (BOP) and High-Temperature Steam Electrolysis (HTSE). Finally, some code improvements that can further enhance the user-friendliness are suggested.

97 MATHEMATICS AND COMPUTING↗

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗

Implementation of a feature selection algorithm in FARM to identify important state variables and time-invariant matrices

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM aids the HERON software module in the evaluation of the optimal dispatch for the different IES components. Set-point trajectories are required to meet limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To evaluate the feasibility of HERON generated set-points and to do so in an acceptable time, FARM employs reduced order models to represent the dynamic behavior of the systems to be dispatched. These surrogate models take the form of a linear dynamic system with sets of Linear Parameter Varying (LPV) matrices that are mapped to the system operating space. These matrices are derived from the trajectories of system state variables and system output variables during transients. The accuracy of LPV matrices depends on the selection of state variables. In previous reports, state variables were selected by adopting a complicated workflow requiring multiple software licenses and an advanced level of user expertise. In this report, a new workflow that automates the state variable selection process is presented. It significantly reduces the frequency of user interventions and does not require multiple software licenses. Each module in the new workflow is described in detail, and the input / output examples in each step of the workflow are provided. It was demonstrated that this workflow can greatly reduce the complexity of the state variable selection process, and that the updated FARM-Gamma and FARM-Delta validators can benefit from this workflow when solving the power dispatch problem of a representative IES test case. Finally, some code improvements that can further enhance the efficiency are suggested.

42 ENGINEERING↗

Evaluating Impacts of Sustainable Aviation Fuel Production with CO2-to-Fuels Technologies on High Renewable Share Power Grids

This paper investigates the impact of Sustainable Aviation Fuel production using CO2-to-Fuels technologies on a future power grid with a high share of renewable energy. We focus on understanding the implications of the 2050 SAF production goal on the U.S. power system's long-term planning, encompassing generation, transmission, and cost analysis. Via the Regional Energy Deployment System (ReEDS) model, we developed a detailed SAF electricity demand model based on a low-temperature electrolysis-syngas fermentation-ethanol pathway. Four SAF target scenarios which aims to meet 10%, 15%, 20%, and 27% of SAF demand by 2050. These scenarios are exhaustively simulated to assess their impact on the power grid. Our results reveal that increasing SAF demand will result in higher electricity requirements, as well as expanded generator and transmission capacities, leading to an overall rise in system costs. However, these impacts are manageable within the broader context of U.S. capacity expansion plans. This study provides valuable insights into incorporating the CO2-to-Fuels electricity demand model and other carbon capture technologies in power system planning, emphasizing their significance in shaping a sustainable energy future.

BIOMASS FUELS,POWER TRANSMISSION AND DISTRIBUTION↗