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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗
DOE OSTI2020

Low-Frequency Stability Analysis of Inverter-Based Islanded Multiple-Bus AC Microgrids Based on Terminal Characteristics

For system planning of three-phase inverter-based islanded ac microgrids, the low frequency instability issue caused by interactions of inverter droop controllers is a major concern. When internal control information of procured commercial inverters is unknown, impedance-based small-signal stability criteria facilitate prediction of resonances in medium and high frequency ranges, but they usually assume the grid fundamental frequency as constant and thus they are incapable of analyzing the low-frequency oscillation of the fundamental frequency in islanded microgrids. Aiming at solving this issue, this paper proposes two stability analysis methods based on terminal characteristics of inverters and passive connection network including the dynamics of the fundamental frequency for analysis of low-frequency stability in islanded multiple-bus microgrids. Based on the Component Connection Method (CCM) to systematically separate inverters from the passive connection network, a general approach is developed to model the microgrid as a multiple-input-multiple-output (MIMO) negative feedback system in the common system d-q reference frame. By applying the generalized Nyquist stability criterion (GNC) to the return-ratio and return-difference matrices of the MIMO system model, the low-frequency stability related to the fundamental frequency can be analyzed using the measured terminal characteristics of inverters. Finally, analysis and simulation of a 37-bus microgrid verify the effectiveness of the proposed stability analysis methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Grid-Forming and Grid-Following Inverter Comparison of Droop Response

With the increase in penetration of inverter-based resources (IBRs) in the electrical power system, the ability of these devices to provide grid support to the system has become a necessity. With standards previously developed for the interconnection requirements of grid-following inverters (GFLI) (most commonly photovoltaic inverters), it has been well documented how these inverters “should” respond to changes in voltage and frequency. However, with other IBRs such as grid-forming inverters (GFMIs) (used for energy storage systems, standalone systems, and as uninterruptable power supplies) these requirements are either: not yet documented, or require a more in deep analysis. With the increased interest in microgrids, GFMIs that can be paralleled onto a distribution system have become desired. With the proper control schemes, a GFMI can help maintain grid stability through fast response compared to rotating machines. This paper will present an experimental comparison of commercially available GFMI and GFLI ' responses to voltage and frequency deviation, as well as the GFMI operating as a standalone system and subjected to various changes in loads.

Grid Support, Inverter, Droop Control, Volt-VAR, F↗
DOE OSTI2024

Engineering collinear magnetization in hexagonal LuFeO 3 and magnetoelectric control of skyrmions in hexagonal 2D epilayers

Cubic, perovskite-structure ABO 3- and A 1–x A’ x BO 3 -type oxides have been investigated extensively while their hexagonal structure versions have not, even though they are multiferroic and can form heterostructures with hexagonal 2D materials. In particular, multiferroic 2D epilayers may lead to strong magnetoelectric coupling. Hexagonal RFeO 3 ferrites, where R is a rare-earth element (Lu, Yb, etc.), are excellent candidates, but their ferromagnetism isweak. In this paper, we employ density-functional-theory (DFT) calculations and first show that heavy electron doping of hexagonal LuFeO 3 (h-LFO), namely Lu 1–x Hf x FeO 3 (h-LHFO), leads to spin-disproportionation of the Fe sublattices and, especially for x = 1/2 and 2/3, to robust, room-temperature, out-of-plane, collinear ferrimagnetism that is stabilized by a Jahn-Teller metal-to-insulator transition. We then show that h-LHFO/h-2D heterostructures, where h-2D is the FE/ FM monolayer MnSTe, stabilize skyrmions without an external magnetic field and control their chirality by an external electric field through the h-LHFO polarization, opening up a new realm for magnetoelectric applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Changing bioavailability of per- and polyfluoroalkyl substances ($\mathrm{PFAS}$) to plant in biosolids amended soil through stabilization or mobilization

Biosolids containing per- and polyfluoroalkyl substances (PFAS) could contaminate the receiving environments once they are land applied. In this report, we evaluated the feasibility of controlling the bioavailability of PFAS in biosolids to timothy-grass through stabilization or mobilization approaches. Stabilization was accomplished by adding a sorbent (i.e. granular activated carbon (GAC), RemBind, biochar) to biosolids, while mobilization was achieved by adding a surfactant, sodium dodecyl sulphate (SDS), to biosolids. The results showed that the ΣPFAS concentration in grass shoots grown in biosolids amended soil treated by GAC or RemBind at 2% was only 2.77% and 3.35% of the ΣPFAS concentration detected in shoots grown in biosolids amended soil without a sorbent, respectively, indicating the effectiveness of GAC and RemBind for stabilizing PFAS and reduce their bioavailability. On the other hand, mobilization by adding SDS to biosolids at a dose range of 10–100 mg/kg significantly increased the plant uptake of ΣPFAS by 15.48%–108.57%. Thus, mobilization by adding SDS could be a valuable approach for enhancing the PFAS removal if phytoremediation is applied. Moreover, higher rate of PFAS uptake took place after grass cutting was observed in this study. Thus, proper mowing and regrowth of timothy-grass could lead to efficient and cost-effective removal of PFAS from biosolids amended soil through phytoremediation and leave the site clean to be used for other purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Functional stimuli-responsive polymers on micro- and nano-patterned interfaces

Micro- and nano-patterned surfaces offer precise control over morphology and chemical composition, enhancing the stability, durability, and functionality of coating materials. When combined with stimuli-responsive polymers, these surfaces gain dynamic adaptability, enabling reversible binding, reusable sensing, and selective molecular capture. Furthermore, while recent review articles have explored various aspects of stimuli-responsive materials, from hydrogel patterns for bioanalytical applications to shape-morphing hydrogels for soft robotics and sensors, a comprehensive review focused on the integration of smart polymers with micro- or nano-patterned interfaces remains absent. This review addresses key surface patterning techniques, including soft lithography, colloidal lithography, and polymer brush photolithography, as well as advances in surface-initiated polymerization methods, such as surface-initiated controlled radical polymerization (SI-CRP). In addition, we discuss recent progress in integrating stimuli-responsive polymers with patterned surfaces to create advanced, functional materials.

Colloidal lithography↗
DOE OSTI2024

Frozen Freedom: Unleashing Grocery Store Demand Flexibility: Preprint

Grocery stores consumed approximately 3% of total electricity used by commercial buildings in the U.S. in 2018 (EIA 2018), representing a unique end-use load profile characterized by the critical use of refrigerated display cases. Exploring demand response (DR) scenarios in grocery stores presents an opportunity to enhance the efficiency and sustainability of surrounding communities. In addition, recent studies demonstrate that implementing control algorithms considering demand flexibility strategies can lead to load and peak reductions in standalone refrigerated display cases. Because small business grocery stores operate on thin margins, the energy bill cost savings DR might provide could make a positive difference toward continued operations. Still, uncertainty remains about the extent of demand flexibility potential controls could provide when coupling refrigeration with whole building operation. To enhance economic viability and grid stability, it is essential to quantify the load flexibility capability of grocery stores. Advanced controls can optimize energy consumption by responding to load shedding, shifting, and DR events, as well as daily Time-of-Use (TOU) rates without compromising food safety. Using both quantitative data and interviews with community-based organizations, we developed a full-size store model and two small store models with controlled refrigerated cases, HVAC, and lighting systems based on actual grocery store properties. Through simulations, we have assessed load flexibility strategies with varied DR events. The results highlight potential for energy and peak reduction with advanced or basic controls. However, interviews and data indicate that more support is needed to make DR strategies consistently accessible to small grocery stores.

demand flexibility↗
DOE OSTI2025

Directed Synthesis of Gold Nanoparticle Superstructures Using Self-Assembling Peptoids Containing Metal-Bonding N-Heterocyclic Carbenes

N-Heterocyclic carbene (NHC) ligands, with strong metal-binding affinity, offer a robust platform for constructing organic–inorganic nanohybrids with high stability and tunable properties. However, achieving precise structural control in a simple manner remains challenging. Here, we report a one-pot synthesis of nanohybrids using self-assembling peptoids functionalized with histidine-2-ylidene, which simultaneously enable peptoid assembly and NHC–metal binding. Histidine-2-ylidene-functionalized peptoids were designed to self-assemble and provide NHC binding sites, while AuNPs served as the inorganic component due to NHCs’ strong affinity for gold surfaces. The resulting peptoid-NHC@AuNPs form well-defined vesicles that are characterized by UV–vis spectroscopy, X-ray photoelectron spectroscopy, and electron microscopy. Importantly, the vesicle size and morphology can be tuned via the peptoid sequence or environmental conditions. Further experiments highlight the crucial role of the NHC sites in the formation and stabilization of these nanohybrids. This modular strategy offers a versatile route to fabricating functional NHC-based nanohybrids for potential applications in sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enhanced Frequency Support Scheme of Generic Inverter-Based Resource Models for Renewable-Dominated Power Grids

The frequency response of SG-dominated power grids is predictable ahead of an occurrence of a frequency event because the frequency response of SGs is consistent, and it can be inferred from the swing equation [1]. However, increasing the portion of IBRs in an SG-dominated power grid might make the characteristics of the conventional power grids no longer valid because this changing resource mix affects grid dynamics and controls [2]. Thus, maintaining these characteristics greatly benefits the control and operation of the power grids with high penetration of IBRs. To maintain these characteristics in IBR-dominated power grids, IBRs should have frequency response capability similar to that of an SG. The WECC modeling validation subcommittee has developed generic IBR models for large system planning [3]-[5]. These models can represent various vendors' dynamic behavior for WTG, PV, and ESS [5]. The current generic IBR models approved by WECC can provide frequency response only from droop control loops in REPC models [6], [7]. The contribution of the loops is proportional to the frequency deviation from the nominal frequency. Thus, it presents an insufficient contribution to arrest frequency variation compared to the frequency response of SGs because it allows a high ROCOF in the early stage of frequency events. This shortfall will become greater as the PL of IBRs increases in power grids. Controller enhancement for the generic IBR models is required to secure the frequency stability under high PL of IBRs as in the SG-dominated power grids. This paper proposes a control extension for the generic IBR models to enhance the frequency support capabilities and discusses the classification of frequency support for the different types of IBR considering their operating constraints. An inertial control scheme is implemented in the REPC and REEC models of the generic IBR models to achieve these objectives. The inertial control scheme includes the following stages: Control area data acquisition, inertia time constant estimation, IBR-related constraint check, IBR contribution determination, and inertial response provision. In the scheme, a REPC acquires control area data from a system operator and estimates a total inertia time constant for the control area the applicable IBR power plant belongs. Then, the estimated inertial time constant is transferred to each IBR controller—REEC—within the power plant. Each REEC checks the availability of applicable IBR for inertial response participation. If the IBR is available, the REEC amplifies the estimated inertial time constant to utilize it for inertial response provision. In this way, the proposed inertial response scheme extends the functionality of the generic IBR models to provide SG-like frequency response within their constraints. Various scenarios considering different IBR types, IBR penetration levels, and frequency control schemes were simulated and compared in an IEEE 39-bus system using PSCAD simulator to verify the effectiveness of the proposed scheme.

Kim, Jinho↗
DOE OSTI2020

Anomaly Detection and Mitigation for Wide-Area Damping Control using Machine Learning

In an interconnected multi-area power system, wide-area measurement based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power flows below to their transmission capacity. The effect of wide-area damping control (WADC) significantly depends on both power and cyber systems. At the cyber system layer, an adversary can inflict the WADC process by compromising either measurement signals, control signals or both. Stealthy and coordinated cyber-attacks may bypass the conventional cybersecurity measures to disrupt the seamless operation of WADC. This paper proposes an anomaly detection (AD) algorithm using supervised Machine Learning and a model-based logic for mitigation. The proposed AD algorithm considers measurement signals (input of WADC) and control signals (output of WADC) as input to evaluate the type of activity such as normal, perturbation (small or large signal faults), attack and perturbation-and-attack. Upon anomaly detection, the mitigation module tunes the WADC signal and sets the control status mode as either wide-area mode or local mode. The proposed anomaly detection and mitigation (ADM) module works inline with the WADC at the control center for attack detection on both measurement and control signals and eliminates the need for ADMs at the geographically distributed actuators. Here, we consider coordinated and primitive data-integrity attack vectors such as pulse, ramp, relay-trip and replay attacks. The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for 2-area 4-machine power system. The ADM module shows effective performance with 96:5% accuracy to detect anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

GE Research and its partner Prolec GE have designed, built and deployed in the field the world’s first flexible power transformer. The flexible power transformer is a transmission class 3-phase autotransformer configurable in impedance and in voltage which allows it to serve as a universal spare for multiple units in a given fleet. However, the key innovation in this new concept is the online adjustable leakage impedance which allows the transformer to change its impedance without interrupting the transmission line operation. The flexible power transformer can be designed with up to three low voltage transmission class ratings and up to 12 impedance values changeable both online and offline. This report provides an overview of the design, manufacturing, testing, and commissioning of the 165kV, 60MVA prototype built including the results of the field performance validation tests. The prototype was specified in collaboration with Cooperative Energy, the utility host. It was designed and tested in the factory according to IEEE standard C57.12.00 and followed all protocols for transportation, installation, and commissioning of a power transformer. In addition to the prototype, a flexible protection system capable of automatically adjusting its settings upon the transformer impedance was also developed and deployed in the for testing and validation. On September 3, 2021 the prototype was energized in Cooperative Energy’s substation in Columbia, Mississippi to become the world’s first flexible power transformer in operation. Its performances and impact on the grid operation were demonstrated through different field tests. Results obtained confirm that the impedance of the flexible transformer can be varied under load through its full range, from 4.3% to 9.3%, without adverse impacts on the line operation, the protection system, the transformer stability and health condition. Results also proved that the flexible transformer is very effective in controlling power transfer through the line or load sharing between units operating in parallel. Indeed, it was proven that higher impedances decrease the thruput power of the transformer while lower impedances increase it. Up to 26MW was controllable on a line loading of 45MVA. It was also possible to demonstrate that the variation of the transformer impedance has no effect on the circulating current between units in parallel, except a minor transient during the impedance change. It was also proven that the flexible protection relay can update its protection settings automatically when the impedance change was detected. The prototype has operated continuously for more than 12 months now with a peak load exceeding 50MVA corresponding to >80% of its ONAN power rating. No alarm, trip or sign of failure has been reported by the utility. In addition to the development and deployment of the flexible transformer prototype, investigations were carried out on new nanodielectric fluids to replace the mineral oil used in power transformers with the goal of reducing their footprint and weight. The key parameters that were targeted for improvement included the breakdown voltage to reduce clearances between windings and tank hence the footprint; viscosity and thermal conductivity to increase the cooling efficiency and therefore to reduce the winding material. Several nanodielectric mixtures with mineral oil including with alumina (Al2O3), titania (TiO2) and Borum Nitrate (BN) with different surfactants have been analyzed and tested. Unfortunately, despite encouraging results no nanofluid candidate has been found viable to replace mineral oil. With the formulations tested, breakdown voltages are generally similar to mineral oil at lower particle contents and worse at higher particle contents. Viscosity appreciably increased at particles concertation over 2 wt% and thermal conductivity increased slightly at 5wt% and appears to be 10-15% higher at 10 wt% particle content. It is recommended to continue investigations to find solutions that can help increase the power density of future flexible power transformers. Flexible power transformers can significantly help the future power grid by providing more flexibility and resiliency. Indeed, by providing voltage and impedance flexibility, flexible power transformers reduce the need for multiple spares, hence inventory costs for utilities. With their online controllable impedance, they can provide support to the grid and help manage short-circuit currents, power flow, line congestion, and grid stability which will become more important with higher penetrations of intermittent renewable resources. During the field validation tests, it was demonstrated that up to 26MW was controllable on a line loading of 45MVA when the transformer impedance was varied from its minimum to its maximum range. Also, with the impedance range, the short-circuit currents could be reduced by up to 38% at the load side of the transformer. With its controllable impedance, flexible transformers can be used in future strategies of grid resilience to help better prepare the grid to face forecasted severe events including storms, heat waves and contingencies. The flexible power transformers can also find role in other applications including high voltage transmission cables such as offshore wind farms where solutions for energizing the cables and managing the reactive power are of critical importance. The designed flexible power transformer is now fully validated and ready for commercialization. Further analysis on the benefits of flexible power transformers for grid stability and short-circuit management including current limiting capability, reclosure and line restoration, control of inrush current, sizing of flexible AC components (FACTS) would help its rapid adoption by the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Machine‐learning‐based construction of barrier functions and models for safe model predictive control

Abstract In this paper, we propose a control Lyapunov‐barrier function‐based model predictive control method utilizing a feed‐forward neural network specified control barrier function (CBF) and a recurrent neural network (RNN) predictive model to stabilize nonlinear processes with input constraints, and to guarantee that safety requirements are met for all times. The nonlinear system is first modeled using RNN techniques, and a CBF is characterized by constructing a feed‐forward neural network (FNN) model with unique structures and properties. The FNN model for the CBF is trained based on data samples collected from safe and unsafe operating regions, and the resulting FNN model is verified to demonstrate that the safety properties of the CBF are satisfied. Given sufficiently small bounded modeling errors for both the FNN and the RNN models, the proposed control system is able to guarantee closed‐loop stability while preventing the closed‐loop states from entering unsafe regions in state‐space under sample‐and‐hold control action implementation. We provide the theoretical analysis for bounded unsafe sets in state‐space, and demonstrate the effectiveness of the proposed control strategy using a nonlinear chemical process example with a bounded unsafe region.

Chen, Scarlett↗
DOE OSTI2022

Hole Trapping in Halide Perovskites Induces Phase Segregation

Metal halide perovskites have garnered a great deal of attention for their applications in photovoltaics, LEDs, and radiation detection. The ease of solution processing high-quality perovskite semiconductors with large absorption coefficients and tolerance to native defects is decidedly attractive. Additionally, the ability to precisely tune the band gap of halide perovskites through compositional alloying of the halide ion is of particular interest for a range of applications, especially for tandem solar cells. However, under steady state light irradiation, an initially homogeneous mixed halide perovskite (MHP) will form local domains that are rich in one halide ion (e.g., Br or I). This light-induced phase segregation in MHPs forms iodide-rich domains that act as charge carrier traps and lowers the efficiency of perovskite-based devices. Thus, phase segregation poses a serious challenge to the implementation of MHPs in real-world device settings. Interestingly, when a phase segregated MHP film is placed in the dark, entropic driving forces become dominant and the segregated perovskite remixes and returns to its initially homogeneous state. Several key mechanistic details of phase segregation have been elucidated over the years. However, there are still aspects of halide segregation that are not clear, and there is ongoing debate in the literature as to what are the key factors that contribute to the mechanism. This Account discusses recent results that point to the specific role of hole trapping in phase segregation. Interestingly, generation of holes through above-band-gap excitation or through electrochemical injection increases ion migration and leads to phase segregation. The thermodynamic and redox properties of halide perovskites provide a strong driving force for hole trapping and oxidation of iodide species in MHPs. However, mobile halide species within the perovskite lattice take time to migrate and generate halide-rich domains. When in contact with a nonpolar solvent, the migration of iodine species is further extended to expulsion of iodine from the perovskite film. Thus, the mobility of halides and their susceptibility to hole-induced oxidation play a crucial role in determining the long-term stability of metal halide perovskites. Strategies to gain kinetic control over ion migration to slow phase segregation are needed to overcome these hurdles and achieve stable mixed halide perovskites. Modification of the perovskite composition through introduction of different cations or halide ions, or introduction of low-dimensional perovskite phases may suppress phase segregation. Furthermore, in achieving stability and improving the efficiency of perovskite solar cells and light emitting devices with minimal impacts, suppression of segregation remains the key factor.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2024

Focus on monitoring and control of complex supply systems

The ongoing rapid transformation of our energy supply challenges the operation and stability of electric power grids and other supply networks. This focus issue comprises new ideas and concepts in the monitoring and control of complex networks to address these challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Damping inter-area oscillation using reinforcement learning controlled TCSC

Appropriate damping control of the inter-area oscillation would ensure the grid stability and maintain the tie-line power transfer capability. In this paper, we proposed a novel reinforcement learning (RL) based power oscillation damping (POD) controller that uses Thyristor Controlled Series Compensators (TCSC) to damp inter-area oscillations. By leveraging the unbiased gradient direction estimation of the natural evolution strategy (NES), we successfully regulated the power flows on the tie-lines and damped inter-area oscillations through dynamically modulating the inserted reactance of the TCSC. The proposed RL-based POD controller has been tested on both two-area four-machine system and North American Minni-WECC system. Extensive studies have demonstrated the excellent performance of the proposed RL-based TCSC POD controller in damping inter-area oscillations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Transforming the electronic properties of phosphorene through charge transfer superatomic doping

Phosphorene is a two-dimensional electron poor p-type semiconductor with great promise for applications in electronics and optoelectronics. Here, in this work, we propose how the two most important properties of a semiconductor, the band gap energy and the nature of carriers, can be controlled by changing the dimensionality or through charge transfer doping with metal-chalcogenide superatoms. Our studies on nanoribbons examine how the band gap can be changed by controlling the width of the ribbons. We investigate the stability and properties of bare and H-terminated nanoribbons. We show that small non-passivated ribbons can be metallic while the passivated ribbons show variation in the band gap energy as a function of the width of the ribbon. We next investigate an alternative approach to band gap and carrier control via doping with ligated metal-chalcogenide superatom clusters whose redox properties can be changed by ligand exchange. Our results obtained from deposition of Co 6 S 8 (PH 3 ) 5-n (CO) n clusters on a phosphorene support showed that the band gap energy can be controlled by exchanging the electron donating phosphine ligands with electron withdrawing CO. We then show that by depositing Re 6 Se 8 (PH 3 ) 5-n Cl n clusters, phosphorene can be converted into a p- or n- type semiconductor as the relative composition of ligands is changed. Our studies provide a novel approach to controlling carrier type and band gap in phosphorene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Atomic-Scale Imaging Reveals Polar-π Interactions in Two-Dimensional Molecular Superlattices

Controlling coassembly of synthetic oligomers into binary superlattices at the atomic level is challenging. Here, we report a strategy for programming polar-π interactions in oligomeric peptoids, a class of sequence-defined peptidomimetics, facilitating the formation of homogeneous two-dimensional (2D) superlattices. N-2-phenylethyl and N-(2-perfluorophenyl)ethyl side chains, similar in size, but with contrasting electrostatic characteristics, were introduced at defined sequence positions to generate favorable dipolar aromatic interactions. The resulting nanosheets exhibit different crystal motifs depending on the side chain interactions: systems containing only one type of aromatic side chain form a parallel V-shaped motif driven by π-π interactions, whereas a combination of both types of aromatic side chains, either within one backbone or through the coassembly of two distinct peptoids, adopt an antiparallel V-shaped superlattice with higher thermal stability, driven by polar-π interactions. Cryogenic transmission electron microscopy directly resolved the packing arrangement of perfluorophenyl and phenyl rings in individual nanosheet superlattices, confirming that intermolecular polar-π interaction dominates the superlattice motifs and increases lattice stability. Molecular dynamics simulations and density functional theory calculations further substantiate the energetic favorability of polar-π interactions over π-π interactions, rationalizing the formation of homogeneous superlattices with enhanced thermal stability. Our discoveries establish a design principle for binary coassembly using sequence-defined oligomers, which enables control over unit cell geometry, lattice stability, and molecular registration through aromatic side chain polarization and sequence control. This ability to program atomic-scale binary superlattices opens new avenues for designing functional 2D soft materials.

Lee, Yen Jea [Lawrence Berkeley National Laborator↗