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At least 613 records · Page 34

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System

Frequency control from photovoltaic (PV) power plants has great potential to address the frequency response challenge of the power system with high penetrations of renewable generation. Using model-based approaches to determine the optimal PV headroom reserve, however, requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic 1-day operation profile of the WECC system and demonstrates a savings of more than 40% PV headroom compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

frequency control↗

Tuning Structural and Electronic Configuration of FeN 4 via External S for Enhanced Oxygen Reduction Reaction

The Fe–N–C material represents an attractive oxygen reduction reaction electrocatalyst, and the FeN 4 moiety has been identified as a very competitive catalytic active site. Fine tuning of the coordination structure of FeN 4 has an essential impact on the catalytic performance. Herein, we construct a sulfur‐modified Fe–N–C catalyst with controllable local coordination environment, where the Fe is coordinated with four in‐plane N and an axial external S. The external S atom affects not only the electron distribution but also the spin state of Fe in the FeN 4 active site. The appearance of higher valence states and spin states for Fe demonstrates the increase in unpaired electrons. With the above characteristics, the adsorption and desorption of the reactants at FeN 4 active sites are optimized, thus promoting the oxygen reduction reaction activity. This work explores the key point in electronic configuration and coordination environment tuning of FeN 4 through S doping and provides new insight into the construction of M–N–C‐based oxygen reduction reaction catalysts.

25 ENERGY STORAGE↗

Final Technical Report: Distributed Controls for High Penetrations of Renewables

The goal of this effort was to apply four potential control analysis/design approaches to the design of distributed grid control systems to address the impact of latency and communications uncertainty with high penetrations of photovoltaic (PV) generation. The four techniques considered were: optimal fixed structure control; Nyquist stability criterion; vector Lyapunov analysis; and Hamiltonian design methods. A reduced order model of the Western Electricity Coordinating Council (WECC) developed for the Matlab Power Systems Toolbox (PST) was employed for the study, as well as representative smaller systems (e.g., a two-area, three-area, and four-area power system). Excellent results were obtained with the optimal fixed structure approach, and the methodology we developed was published in a journal article. This approach is promising because it offers a method for designing optimal control systems with the feedback signals available from Phasor Measurement Unit (PMU) data as opposed to full state feedback or the design of an observer. The Nyquist approach inherently handles time delay and incorporates performance guarantees (e.g., gain and phase margin). We developed a technique that works for moderate sized systems, but the approach does not scale well to extremely large system because of computational complexity. The vector Lyapunov approach was applied to a two area model to demonstrate the utility for modeling communications uncertainty. Application to large power systems requires a method to automatically expand/contract the state space and partition the system so that communications uncertainty can be considered. The Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) design methodology was selected to investigate grid systems for energy storage requirements to support high penetration of variable or stochastic generation (such as wind and PV) and loads. This method was applied to several small system models.

14 SOLAR ENERGY↗

Optimal detumbling of a large manned spacecraft using an internal moving mass

The use of a movable mass control system to stabilize an arbitrarily tumbling asymmetric vehicle about the maximum inertia axis is considered. A first-order gradient optimization technique is used to minimize angular velocity components along the intermediate and minimum inertia axes. This method permits a wide range of initial guesses for mass position history. Motion of the control mass is along a linear track fixed in the vehicle. The control variable is taken as mass acceleration with respect to body coordinates. Motion is limited to defined quantities and a penalty function is used to insure a given range of positions. Numerical solutions of the optimization equations verify that minimum time detumbling is achieved with the largest permissible movable mass, length of linear track, and positions of the mass on the two coordinates perpendicular to the linear motion.

Kunciw, B. G.↗

TU-CD-304-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Trajectory Modulated Arc Therapy: Development of Novel Arc Delivery Techniques Integrating Dynamic Table Motion for Extended Volume Treatments

Purpose: Integration of coordinated robotic table motion with inversely-planned arc delivery has the potential to resolve table-top delivery limitations of large-field treatments such as Total Body Irradiation (TBI), Total Lymphoid Irradiation (TLI), and Cranial-Spinal Irradiation (CSI). We formulate the foundation for Trajectory Modulated Arc Therapy (TMAT), and using Varian Developer Mode capabilities, experimentally investigate its practical implementation for such techniques. Methods: A MATLAB algorithm was developed for inverse planning optimization of the table motion, MLC positions, and gantry motion under extended-SSD geometry. To maximize the effective field size, delivery trajectories for TMAT TBI were formed with the table rotated at 270° IEC and dropped vertically to 152.5cm SSD. Preliminary testing of algorithm parameters was done through retrospective planning analysis. Robotic delivery was programmed using custom XML scripting on the TrueBeam Developer Mode platform. Final dose was calculated using the Eclipse AAA algorithm. Initial verification of delivery accuracy was measured using OSLDs on a solid water phantom of varying thickness. Results: A comparison of DVH curves demonstrated that dynamic couch motion irradiation was sufficiently approximated by static control points spaced in intervals of less than 2cm. Optimized MLC motion decreased the average lung dose to 68.5% of the prescription dose. The programmed irradiation integrating coordinated table motion was deliverable on a TrueBeam STx linac in 6.7 min. With the couch translating under an open 10cmx20cm field angled at 10°, OSLD measurements along the midline of a solid water phantom at depths of 3, 5, and 9cm were within 3% of the TPS AAA algorithm with an average deviation of 1.2%. Conclusion: A treatment planning and delivery system for Trajectory Modulated Arc Therapy of extended volumes has been established and experimentally demonstrated for TBI. Extension to other treatment techniques such as TLI and CSI is readily achievable through the developed platform. Grant Funding by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Proposal to Localize Fermi GBM GRBs Through Coordinated Scanning of the GBM Error Circle via Optical Telescopes

We investigate the feasibility of implementing a system that will coordinate ground-based optical telescopes to cover the Fermi GBM Error Circle (EC). The aim of the system is to localize GBM detected GRBs and facilitate multi-wavelength follow-up from space and ground. This system will optimize the observing locations in the GBM EC based on individual telescope location, Field of View (FoV) and sensitivity. The proposed system will coordinate GBM EC scanning by professional as well as amateur astronomers around the world. The results of a Monte Carlo simulation to investigate the feasibility of the project are presented.

Ukwatta, T. N.↗

Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources

The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-Time Optimization and Control of Next-Generation Distribution Infrastructure

This presentation highlights the key developments of the ARAP-e NODES project, including the innovative real-time optimal power flow (RT-OPF) algorithm for distributed energy resource (DER) management, trip planning for T+D coordination, and extensive validation of the RT-OPF algorithm in NREL ESIF laboratory with 100+ physical hardware devices, controller-hardware-in-the-loop test at Southern California Edison (SCE), and two field demonstrations.

hardware-in-the-loop↗

Computational fluid dynamic design of rocket engine pump components

Integration of computational fluid dynamics (CFD) for design and analysis of turbomachinery components is needed as the requirements of pump performance and reliability become more stringent for the new generation of rocket engine. A fast grid generator, designed specially for centrifugal pump impeller, which allows a turbomachinery designer to use CFD to optimize the component design will be presented. The CFD grid is directly generated from the impeller blade G-H blade coordinates. The grid points are first generated on the meridional plane with the desired clustering near the end walls. This is followed by the marching of grid points from the pressure side of one blade to the suction side of a neighboring blade. This fast grid generator has been used to optimize the consortium pump impeller design. A grid dependency study has been conducted for the consortium pump impeller. Two different grid sizes, one with 10,000 grid points and one with 80,000 grid points were used for the grid dependency study. The effects of grid resolution on the turnaround time, including the grid generation and completion of the CFD analysis, is discussed. The impeller overall mass average performance is compared for different designs. Optimum design is achieved through systematic change of the design parameters. In conclusion, it is demonstrated that CFD can be effectively used not only for flow analysis but also for design and optimization of turbomachinery components.

Chen, Wei-Chung↗

FES 2023 Theory & Simulation Performance Target

The Report for the 2023 Theory & Simulation Performance Target (TSPT) is presented herein. The 1st, 2nd and 3rd Quarter Reports are given in Sec. I, Sec. II and Sec. III. These are unchanged from those previously submitted, except that in this final document the equations, figures and citations have been automatically renumbered. The 4th Quarter Report is given in Sec. IV. The following material presents verification calculations of several widely used three-dimensional (3D) magnetohydrodynamic (MHD) equilibrium codes in strongly shaped configurations; for both fixed and free-boundary equilibria; for the so-called vacuum case and for the case of high plasma pressure; and, for magnetic fields that have nested magnetic surfaces and for fields that have a magnetic island. The configurations studied includes the recently discovered “precise-QA” case [Phys. Rev. Lett., 128, 035001 (2002)] and other highly optimized configurations. Because of the strong (extreme) shaping, the latter of these pose challenges to the 3D MHD codes. A new method is introduced for constructing coordinates in arbitrarily shaped toroidal domains, and this can improve the robustness of 3D equilibrium calculations. Beyond the equilibrium calculation, this report demonstrates the capability of performing non-linear extended-MHD modelling of optimized stellarator equilibria. This capability allows the assessment not only of linear stability thresholds but also of the nonlinear evolution of unstable equilibria to new configurations that might be far from the original configuration, with significantly different transport properties and magnetic topology. They also enable the self-consistent determination of pressure profiles in non-integrable magnetic topology through the use of highly anisotropic thermal-transport equations. The calculations presented here represent the first demonstration of extended-MHD calculations in strongly-shaped, optimized quasi-symmetric configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Water Resources Utilization and Protection in the Coal Mining Area of Northern China

This study investigates multiple types of water resources in the western mining area in China, their supply-demand balance by using the same dimension gray recurrence dynamic model GM (1, 1), and water content coefficients of mines to ease water supply-demand contradiction. A multi-objective programming model is proposed for optimal water resources allocation management. Optimal technical schemes for water resources allocation among different users are obtained. The optimization model improves upon the previous studies by using water demand and water supply forecast. Coordinated development for mining safety, mine water utilization, and remediation and control of water environment is achieved.

54 ENVIRONMENTAL SCIENCES↗

Structure of a seeded palladium nanoparticle and its dynamics during the hydride phase transformation

Palladium absorbs large volumetric quantities of hydrogen at room temperature and ambient pressure, making the palladium hydride system a promising candidate for hydrogen storage. Here, we use Bragg coherent diffraction imaging to map the strain associated with defects in three dimensions before and during the hydride phase transformation of an individual octahedral palladium nanoparticle, synthesized using a seed-mediated approach. The displacement distribution imaging unveils the location of the seed nanoparticle in the final nanocrystal. By comparing our experimental results with a finite-element model, we verify that the seed nanoparticle causes a characteristic displacement distribution of the larger nanocrystal. During the hydrogen exposure, the hydride phase is predominantly formed on one tip of the octahedra, where there is a high number of lower coordinated Pd atoms. Our experimental and theoretical results provide an unambiguous method for future structure optimization of seed-mediated nanoparticle growth and in the design of palladium-based hydrogen storage systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the capabilities of optical pump X-ray probe NEXAFS spectroscopy to track photo-induced dynamics mediated by conical intersections

X-ray spectroscopy is gaining a growing interest in the scientific community, as it represents a versatile and powerful experimental toolbox for probing the dynamics of both core and valence electronic excitations, nuclear motions and material structure, with element and site specificity. Among the various X-ray based techniques, near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, which investigates the energy and probability of resonant core-to-valence transitions, has started to be applied to organic molecules: a recent UV-pump X-ray probe time-resolved NEXAFS experiment [Wolf et al., Nat. Commun., 2017, 8, 1] has shown the capability of the technique to provide information about the ultrafast internal conversion between the bright ππ* and the dark nπ* electronic states of the nucleobase thymine. In the present contribution we introduce an accurate theoretical approach for the simulation of NEXAFS spectra of organic molecules, employing azobenzene as a test case. The electronic structure calculations, which provide both energy levels and transition probabilities of core-to-valence excitations, were here performed with a high level multiconfigurational method, the restricted active space self consistent field (RASSCF/RASPT2). GS- and nπ*-NEXAFS spectra were obtained on the top of key molecular geometries (as the optimized cis, trans and conical intersection(s) structures) as well as along the fundamental isomerization coordinates (namely, symmetric and asymmetric bendings of the phenyl rings, and torsion around the central dihedral). We eventually characterize and explain the origin of the simulated signals, highlighting the specific signatures that make it possible to follow the excited state evolution from the nπ* Franck–Condon point, towards the conical intersection(s).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive Reinforcement Learning Control for Power Distribution in Multi-Output Resonant Converters

This paper presents an adaptive reinforcement learning (ARL)-based control framework for efficient power distribution in a multi-output resonant converter for UAV applications. The proposed system is based on a high-frequency isolated resonant architecture, where a single energy source supplies multiple propulsion loads through independently controlled output rectifiers, addressing the need for coordinated multi-motor power management. The ARL framework dynamically allocates output power by learning optimal phase-shift control actions under varying load demands and operating conditions. The agent autonomously determines control parameters that maximize conversion efficiency while ensuring accurate power sharing among multiple outputs. In addition, the proposed approach enables adaptive operation without requiring detailed system modeling or manual tuning. Experimental results demonstrate stable and efficient performance over a wide range of operating conditions, confirming the effectiveness and robustness of the learning-based control strategy for multi-output resonant converter system.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗

Algorithms for Mathematical Programming with Emphasis on Bi-level Models (Final Scientific/Technical Report)

The research supported by this grant was focused primarily on first-order methods for solving large scale and structured convex optimization problems and convex relaxations of nonconvex problems. These include optimal gradient methods, operator and variable splitting methods, alternating direction augmented Lagrangian methods, and block coordinate descent methods.

97 MATHEMATICS AND COMPUTING↗

Minimum fuel horizontal flightpaths in the terminal area

The problem of minimum fuel airplane trajectories from arbitrary initial states to be fixed final state is considered. There are four state variables (two position coordinates, heading, and constrained velocity) and two constrained controls (thrust and bank angle). The fuel optimality of circular and straight line flightpaths is examined. Representative extremals (trajectories satisfying the necessary conditions of the minimum principle) of various types are computed and used to evaluate trajectories generated by an on line algorithm. Attention is paid to the existence of Darboux points (beyond which an extremal ceases to be globally optimal). One fuel flow rate model includes a term quadratic in thrust; hence, the optimal thrust is continuous and nonsingular. The other fuel flow rate model is linear in thrust, and consequently the optimal thrust is discontinuous and singular.

Kreindler, E.↗