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At least 1,009 records · Page 56

Thermodynamics of a Dual Stage Sodium Thermo-Electro-Chemical Converter

The need for reliable and distributable energy is evident, but one prominent obstacle is the lack of an efficient direct heat-to-electricity converter. The sodium thermo-electro-chemical converter (Na-TECC) is a highly efficient thermally regenerative electrochemical system (TRES) that can fill this void. This electrochemical technology uses an ion-selective solid-electrolyte called beta-alumina that is highly conductive to sodium cations. The Na-TECC generates electric power by allowing high pressure sodium cations to expand isothermally through the solid-electrolyte. Theoretically, a device interacting with thermal reservoirs at 1150 K and 550 K should operate above 45% efficiency, but actual devices have not surpassed efficiencies of 20%. The maximum potential voltage in these previous devices was substantially reduced by the kinetic limitations of the charge transfer in the cathode (referred to as the overpotential) and by Joule heating losses due to the solid-electrolyte resistance, electrode resistance, and current collector resistance. To overcome this discrepancy, a dual stage conversion process is being proposed. Rather than using one isothermal expansion step, the dual cycle will employ two separate electrolytes to allow two separate expansion steps: one at the high temperature, and another at an intermediate temperature. This new cycle is thermodynamically favorable as it allows for regeneration from the isobaric cooling of the first expansion step, and reheat to complete the expansion in the second step. This allows the engine to reach a lower condenser temperature than its single stage counterpart for a given heat input, resulting in an increased overall efficiency. The temperature drop across each electrolyte in the dual stage device (e.g., ~ 400 K) is smaller than the temperature drop across a comparable single stage device (e.g., ~ 800 K). This makes the device amenable to better thermal management and allows for less heat loss. Also, the intermediate stage will mitigate the thermal shock across the very thin (< 1 mm) solid electrolyte, reduce crack propagation, limit the percolation of the molten dendrites, and ultimately increase the lifetime of the device. A dual stage concept for the Na-TECC has never been demonstrated in literature, so it is necessary to properly re-define the thermodynamic parameters such as heat loss, maximum power, and optimal current density. Certain drawbacks from a dual stage concept will also be addressed, such as the need for larger electrochemical area and the increased pressure losses. It will be demonstrated that the dual stage device must have lower thermal losses than a single stage device if it is to have a higher efficiency. The improved operation of the Na-TECC can have a transformational effect on small combined heat and power (CHP) systems at the 1-5 kW range.

14 SOLAR ENERGY↗

Dual Stage Sodium Thermo-Electro-Chemical Converter (Na-TEC)

The need for reliable and distributable energy is evident, but one prominent obstacle is the lack of an efficient direct heat-to-electricity converter. The sodium thermo-electro-chemical converter (Na-TECC) is a highly efficient thermally regenerative electrochemical system (TRES) that can fill this void. This device uses an ion-selective solid-electrolyte called beta”-alumina that is highly conductive to sodium cations. The Na-TECC generates electric power by allowing high pressure sodium cations to expand isothermally through the solid-electrolyte. Theoretically, a device interacting with thermal reservoirs at 1150 K and 550 K should operate above 45% efficiency, but actual devices have not surpassed efficiencies of 20%. The maximum potential voltage in these previous devices was substantially reduced by the kinetic limitations of the charge transfer in the cathode, by pressure losses through the porous electrodes, and by Joule heating losses caused by the solid-electrolyte, electrode, and current collector resistances. To overcome these low efficiencies, a dual stage conversion process is being proposed. Rather than using one isothermal expansion step, the dual cycle will employ a second electrolyte to allow two separate expansion steps: one at the high temperature, and another at an intermediate temperature. This new cycle is thermodynamically favorable as it allows for regeneration from the isobaric cooling of the first expansion step, and reheat to complete the expansion in the second step. This allows the engine to reach a lower condenser temperature than its single stage counterpart for a given heat input, resulting in an increased overall efficiency. The temperature drop across each electrolyte in the dual stage device (e.g., ~ 400 K) is smaller than the temperature drop across a comparable single stage device (e.g., ~ 600 K). This makes the device amenable to better thermal management and allows for less heat loss. Also, the intermediate stage will mitigate the thermal shock across the very thin (< 1 mm) solid electrolyte, reduce crack propagation, limit the percolation of the molten dendrites, and ultimately increase the lifetime of the device. A dual stage concept for the Na-TECC has never been demonstrated in literature, so it is necessary to properly re-define the thermodynamic parameters such as heat loss, maximum power, and optimal current density. Certain drawbacks from a dual stage concept will also be addressed, such as the need for larger electrochemical area and the increased pressure losses. It will be demonstrated that the dual stage device must have lower thermal losses than a single stage device if it is to have a higher efficiency. The improved operation of the Na-TECC can have a transformational effect on small combined heat and power (CHP) systems at the 1-5 kW range.

14 SOLAR ENERGY↗

Geometry Optimization of Cable-Based Actuation for Small-Scale Model Testing of a Floating Marine Turbine: Preprint

This research aims to apply combined wave and tidal current loads to a small-scale floating marine current turbine in a wave tank, where an actuation system applies hydrodynamic and mooring forces on the hardware based on results from a simulation. We use a real-time hybrid test setup with physical wave forcing from the wave tank and simulated current and mooring forces implemented through a tensioned cable array. For this paper, we developed an optimization algorithm that adjusts the hardware geometry of the cable array to achieve more efficient tension allocation across the cables for the loads that need to be actuated. By adjusting the points where the cables are attached to the floating platform and the angles between the platform and the winches, an optimal cable geometry can be found to minimize tension variations in the lines, maintain the desired pretension, and prevent excessive tensions. We present the optimization problem formulation, the actuation system evaluation approach, and optimization results that show effective cable actuation setups that are being considered for implementation in the wave tank tests.

cable-based actuation↗

Presentation of the MERC work-flow for the computation of a 2D radial reflector in a PWR

This paper presents a work-flow for computing an equivalent 2D radial reflector in a pressurized water reactor (PWR) core, in adequacy with a reference power distribution, computed with the method of characteristics (MOC) of the lattice code APOLLO2. The Multi-modelling Equivalent Reflector Computation (MERC) work-flow is a coherent association of the lattice code APOLLO2 and the core code COCAGNE, structured around the ADAO (Assimilation de Donnees et Aide a l'Optimisation) module of the SALOME platform, based on the data assimilation theory. This study leads to the computation of equivalent few-groups reflectors, that can be spatially heterogeneous, which have been compared to those obtained with the OPTEX similar methodology developed with the core code DONJON, as a first validation step. Subsequently, the MERC work-flow is used to compute the most accurate reflector in consistency with all the R and D choices made at Electricite de France (EDF) for the core modelling, in terms of number of energy groups and simplified transport solvers. We observe important reductions of the power discrepancies distribution over the core when using equivalent reflectors obtained with the MERC work-flow. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Optimal Low-Thrust Limited-Power Transfers between Arbitrary Elliptic Coplanar Orbits

In this work, a complete first order analytical solution, which includes the short periodic terms, for the problem of optimal low-thrust limited-power transfers between arbitrary elliptic coplanar orbits in a Newtonian central gravity field is obtained through Hamilton-Jacobi theory and a perturbation method based on Lie series.

daSilvaFernandes, Sandro↗

Coherent magnetic nanoinclusions induce charge localization in half-Heusler alloys leading to high- T c ferromagnetism and enhanced thermoelectric performance

Performance improvement traditionally realized through a combination of power factor optimization via electronic doping and lattice thermal conductivity reduction using nanostructuring have reached their optimal limits in many leading thermoelectric materials, making further enhancement in the thermoelectric figure of merit extremely challenging. Here, a novel approach to electronic transport engineering using coherent magnetic nanoinclusions is demonstrated. It was found that the incorporation of coherent magnetic full-Heusler (FH) nanoinclusions (Ti(Ni 4/3 Fe 2/3 )Sn) into a half-Heusler (HH) matrix (Ti 0.25 Zr 0.25 Hf 0.5 NiSn 0.975 Sb 0.025 ) with optimal doping level and lattice thermal conductivity leads to high Curie temperature ferromagnetism (T c ~ 650 K) along with a large reduction in the effective carrier density within the HH matrix. It is believed that the embedded magnetic FH nanoinclusions interact with the spin of itinerant carriers, leading to charge localization and the formation of overlapping bound magnetic polarons (BMPs). This gives rise to significant enhancements of both carrier mobility and thermopower, which minimizes the reduction in the overall power factor, simultaneously with a large drop in the total thermal conductivity owing to the reduction of the electronic contribution to the thermal conductivity. Here, whe implementation of the magnetic nanoinclusions strategy in a variety of state-of-the-art thermoelectric materials could pave the way towards even larger figures of merit.

36 MATERIALS SCIENCE↗

Coordinated Optimization and Control of Residential Solid State Power Substations in Electrical Distribution Network

This paper proposes a computationally efficient mixed integer linear programming (MILP) model for the coordinated optimization of solid-state power substations (SSPSs) in a feeder considering the full unbalanced three-phase structure of the distribution grid and its characteristics. The proposed model determines the optimal real and reactive power of each SSPS at the point of common coupling (PCC) that minimizes the operating cost and maximizes the system performance, e.g., voltage regulation and phase balancing. To improve the computational efficiency, an inscribed octagon is introduced to approximate the quadratic capacity constraints of components. Numerical simulation results show the effectiveness of the proposed model and significant improvements in voltage profiles and power imbalance between phases.

Liu, Guodong↗

Community Project for Accelerator Science and Simulation (ComPASS)

After concluding our initial exercise (solving a simplified statistical inverse problem with unknown parameter laser intensity) of coupling Vorpal and our parallel statistical library QUESO, we shifted the application focus to DLA. Our efforts focused on developing a Gaussian process (GP) emulator within QUESO for efficient optimization of power couplers within woodpiles. The smaller simulation size (compared with LPA) allows for sufficient “training runs” to develop a reasonable GP statistical emulator for a parameter space of moderate dimension.

43 PARTICLE ACCELERATORS↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An inverter/controller subsystem optimized for photovoltaic applications

Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. Optimization of the inverter/controller design is discussed as part of an overall photovoltaic power system designed for maximum energy extraction from the solar array. The special design requirements for the inverter/ controller include: a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy.

Pickrell, R. L.↗

Assessment of Model-Based Schemes for Accelerating Optimization by RAVEN

Nuclear-Renewable Hybrid Energy Systems (N-R HES) combine different energy technologies in a synergistic way with the objective of achieving a more economical energy production. In this report the particular hybrid system dealt with includes a PWR nuclear reactor, the associated Rankine-based energy conversion cycle (Balance of Plant, BOP), an Industrial Process (IP) for hydrogen production, a gas turbine (Second Energy Source, SES), and a battery (Energy Storage, ES). The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the N-R HES. HYBRID solves the coupled capacity planning-economic and dispatch optimization problem with the objective of minimizing the Levelized Cost of Electricity (LCOE). In the optimization of the power dispatch strategy, the HYBRID framework takes into account the time-dependent dynamics of each subsystem by including a Dymola object-oriented model of the process dynamics. To ease the computational burden of the optimization process, an initial guess for the dispatch optimization problem is provided by a preconditioner. The solution guess is calculated by means of a least-marginal cost approach which applies the same criterion behind the screening curve method. Though this algorithm allows evaluating an economically adapted generation mix for a target load duration curve within a few seconds, it neglects the constraints due to the single component dynamics, and it is not able to adequately represent the ES. An improved treatment of the pre-conditioner problem was addressed by introducing a Monte Carlo based optimization algorithm. The new approach takes into account limits on power rates for the system subcomponents, which was not previously done. Additionally, this new Monte-Carlo based preconditioner addresses the problem with the ES component through improved modeling of that component. The new algorithm has been implemented in the HYBRID framework and tested to assess its performance. The results obtained with the new Monte Carlobased preconditioner were benchmarked against those obtained through the reference deterministic approach. The comparison shows that the Monte-Carlo based approach provides improved solution accuracy to the power dispatch optimization problem. Also in this report, the treatment of the penalty function on LCOE is discussed, and an improved penalty function for missed demand is suggested and tested.

Maronati, Giovanni↗

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power-Water-Heat Systems

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex-concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bonded Interfaces for High-Temperature Power Electronics

Wide-bandgap devices have pushed the operational limit of semiconductor devices in automotive power electronics packages to higher temperatures (>200 degrees C). While a higher efficiency can be achieved through the use of wide-bandgap devices, the entire package must be re-designed with components that can withstand the higher temperature limits. Sintered silver and transient liquid phase bonds are potential candidates as bonded materials for use in higher temperatures however, the underlying mechanics of deformation under thermal loads and the resulting failure mechanisms in these materials are not well understood. Furthermore, thermomechanical modeling plays a key role in understanding the degradation behavior of bonded interface materials and for design optimization of power electronics packages.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.

36 MATERIALS SCIENCE↗

Next Generation RivGen Power System: Kvichak River, AK Overwinter Ice Study

The University of Alaska Fairbanks (UAF) Alaska Hydrokinetic Energy Research Center was tasked with developing a real-time data telemetry / remote power generation system to monitor frazil ice conditions in the Kvichak River in support of the U.S. Department of Energy funded "Next Generation MHK River Power System Optimized for Performance, Durability and Survivability" project. A real-time telemetry system was requested because of the short time span between the end of the frazil ice season when the instruments would be recovered, limited vessel availability and the project end-date. To meet the project objectives, UAF designed and assembled a remote power/real-time data telemetry system that included an auto start propane generator, a small PV array, a small battery bank and line-of-sight radios as well as two sonar systems to monitor river velocity and water column acoustic backscatter strength. Both sonars included internal batteries for powering the instruments in case of failure of the shore based power system. The sonars, deployed in ~5 m of water on the bed of the Kvichak River, adjacent to the Village of Igiugig, Alaska were tethered to shore via a waterproof armored cable that conveyed power to the subsurface instruments and data from the instruments to the shore based telemetry system. The instruments were programmed to record data internally as well as to transmit data serially over the cables to the shore based system. The system was in-place between November, 2016 and June, 2017. While the real-time data telemetry system was not successful and the remote power generation power system was only partially successful, the system design included sufficient redundant power in the form of internal instrument batteries to enable the collection of nearly three months of overlapping velocity and backscatter data (from November through February) and a record of acoustic backscatter strength spanning the entire ~150 day frazil ice season between November, 2016 and ~April, 2017. This submission includes the overwinter ice study plan, raw data, and report.

16 TIDAL AND WAVE POWER↗