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At least 37 records · Page 2

Optimal mitigation and control over power system dynamics for stochastic grid resilience

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.

30 DIRECT ENERGY CONVERSION↗

Control over emergence and alignment of transient blisters in thermo-responsive gels using hierarchically patterned substrates

Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.

42 ENGINEERING↗

Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

14 SOLAR ENERGY↗

Geometric control of emergent antiferromagnetic order in coupled artificial spin ices

Artificial spin ices (ASIs) composed of coupled nanomagnets offer the possibility to create designer geometrical frustration and manipulate inter-nanomagnet interactions. In particular, by using a dimer motif consisting of two strongly coupled single-domain nano magnets as a building block, we can control and realize intriguing antiferromagnetic physical states in which the magnetic charge is not conserved. Here we create a dimer kagome ASI system within which the antiferromagnetic order is controlled by tuning lattice geometry. Different disordered antiferromagnetic phases and the inter-nanomagnet interactions are visualized directly in demagnetized lattices with different lattice parameters. Monte Carlo simulations establish that the collective ground state consists of disordered antiferromagnetic dimers across the lattice when the intra-dimer interaction is dominant. However, for lattices governed by intra-triad-unit interactions, the ground state exhibits a longrange spin-ordered state in which the vertex magnetic charge is uniform across all triads.

36 MATERIALS SCIENCE↗

Emergent properties at oxide interfaces controlled by ferroelectric polarization

Abstract Ferroelectric materials are characterized by the spontaneous polarization switchable by the applied fields, which can act as a “gate” to control various properties of ferroelectric/insulator interfaces. Here we review the recent studies on the modulation of oxide hetero-/homo-interfaces by ferroelectric polarization. We discuss the potential applications of recently developed four-dimensional scanning transmission electron microscopy and how it can provide insights into the fundamental understanding of ferroelectric polarization-induced phenomena and stimulate future computational studies. Finally, we give the outlook for the potentials, the challenges, and the opportunities for the contribution of materials computation to future progress in the area.

Chemistry↗

Improving power grid transient stability and transfer capability using HVDC emergency power controls

In the future, with high levels of renewable energy sources penetration, the transmission corridors will have to be flexible to operate under faster transients and variable power flows. Fast power ramping and overloading capabilities of HVDC system can be utilized to ensure transient stability of the interconnected power grid. In this paper, HVDC auxiliary controllers have been studied that can provide the power grid with additional synchronizing torques through fast DC power changes in response to arising system conditions. The effectiveness of the auxiliary controllers in improving transient stability is demonstrated by performing dynamic simulations on the detailed model of the Western Interconnection system (WECC).

Sundaresh, Lakshmi↗

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗

VSC-HVDC Interties for Urban Power Grid Enhancement

Urban power grids are facing many operational and expansion challenges to meet further demand growth and increased reliability requirements. Advanced transmission technologies have been considered by the electric utilities to effectively increase the utilization of existing infrastructure and operational flexibility. The focus of this paper is on VSC-HVDC technologies for urban power grid enhancement and modernization. First, a potential technical scheme is proposed for converting an existing AC circuit to DC operation, which could boost the power transfer capability of the critical transmission corridor and increase network operational flexibility. Second, this paper proposes three operation modes for the VSC-HVDC interties in urban power grids corresponding to normal, emergency and island operating conditions, respectively. An integrated, adaptive emergency control strategy (AEC) is proposed that can enable adaptive power flow responses of the VSC-HVDC intertie under varying system operating conditions and critical contingencies. The flexibility and effectiveness of the proposed operational principles of urban VSC-HVDC intertie and the corresponding control strategies are verified in PSCAD/EMTDC using a realistic urban power grid in China.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultrafast Terahertz Field Control of the Emergent Magnetic and Electronic Interactions at Oxide Interfaces

Ultrafast electric-field control of emergent electronic and magnetic states at oxide interfaces offers exciting prospects for the development of the next generation of energy-efficient devices. Here, it is demonstrated that the electronic structure and emergent ferromagnetic interfacial state in epitaxial LaNiO3/CaMnO3 superlattices can be effectively controlled using intense, single-cycle THz electric-field pulses. A suite of advanced X-ray spectroscopic techniques is employed to measure a detailed magneto-optical profile and the thickness of the ferromagnetic interfacial layer. Then, a combination of time-resolved and temperature-dependent optical measurements is used to disentangle several correlated electronic and magnetic processes driven by ultrafast, high-field THz pulses. Sub-picosecond non-equilibrium Joule heating of the electronic system is observed, ultrafast demagnetization of the ferromagnetic interfacial layer, and slower dynamics indicative of a change in the magnetic state of the superlattice due to the transfer of spin-angular momentum to the lattice. These findings suggest a promising avenue for the efficient control of 2D ferromagnetic states at oxide interfaces using ultrafast electric-field pulses.

X-ray spectroscopy and scattering↗

Quantum coherence tomography of light-controlled superconductivity

The coupling between superconductors and oscillation cycles of light pulses, i.e., lightwave engineering, is an emerging control concept for superconducting quantum electronics. Although progress has been made towards terahertz-driven superconductivity and supercurrents, the interactions able to drive non-equilibrium pairing are still poorly understood, partially due to the lack of measurements of high-order correlation functions. In particular, the sensing of exotic collective modes that would uniquely characterize light-driven superconducting coherence, in a way analogous to the Meissner effect, is very challenging but much needed. Here we report the discovery of parametrically driven superconductivity by light-induced order-parameter collective oscillations in iron-based superconductors. The time-periodic relative phase dynamics between the coupled electron and hole bands drives the transition to a distinct parametric superconducting state out-of-equalibrium. This light-induced emergent coherence is characterized by a unique phase–amplitude collective mode with Floquet-like sidebands at twice the Higgs frequency. We measure non-perturbative, high-order correlations of this parametrically driven superconductivity by separating the terahertz-frequency multidimensional coherent spectra into pump–probe, Higgs mode and bi-Higgs frequency sideband peaks. We find that the higher-order bi-Higgs sidebands dominate above the critical field, which indicates the breakdown of susceptibility perturbative expansion in this parametric quantum matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery

Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.

42 ENGINEERING↗

Virtual Synchronous Generator Control of Multi-port Autonomous Reconfigurable Solar Plants (MARS)

Multi-port autonomous reconfigurable solar power plant (MARS) is an integrated concept for integration of solar photovoltaic (PV) and energy storage systems (ESS) to transmission alternating current (ac) grid and high-voltage direct current (HVdc) links. The integrated development incorporates advanced control methods to provide enhanced grid ancillary services such as fast frequency responses and dynamic voltage support. In this paper, the virtual synchronous generator (VSG) control algorithm of MARS is discussed. The proposed VSG-based control enables enhanced synthetic inertial response and flexible frequency response characteristics of hybrid PV and ESS power plants in accordance with grid ancillary service requirements. Multi-port power electronics interface allows controlled emergency power support from MARS to local transmission ac grid and remote grid through the HVdc link. The performance of VSG control is validated using a reduced-order model of MARS in Simulink. Methods for estimating grid ancillary service capabilities of MARS are also discussed.

Pan, Jiuping↗

Development of a molecularly informed biogeochemical framework for reactive transport modeling of subsurface carbon inventories, transformations and fluxes (Final Report)

The overall objective of the project was to combine new molecular-level characterization strategies with soil carbon flux measurements to develop and evaluate model representations of subsurface carbon cycling. We expanded on existing studies in the East River watershed, Colorado, in collaboration with the Berkeley Lab Watershed Function Scientific Focus Area (SFA), SLAC Groundwater Quality SFA, and Rocky Mountain Biological Laboratory (RMBL) to develop an elevation and vegetation gradient that is now the subject of long-term monitoring by the USGS. To achieve the overall objective, we combined field studies of soil respiration with laboratory analyses, ranging from spectroscopy to incubation studies. This combination of techniques enabled us to develop a new understanding of the drivers of high-elevation soil respiration. In the process, we developed three new modeling approaches that improve our ability to conceptualize and ultimately to represent soil respiration in numerical models. The first approach is a plot-scale transient inverse model that can be used to determine in situ CO 2 production rates from measured concentration profiles and surface fluxes. Application of this method revealed the importance of plant phenology and deep CO 2 production in moderating CO 2 fluxes to the atmosphere. The second modeling approach is a molecular-scale tool that enables spectroscopic and elemental data for carbon speciation to be transformed into functional group abundances, or the ‘SOC-fga model’. This method uniquely enables carbon speciation to be tracked within a reactive transport framework to partition carbon among different pathways and storage zones within the soil. The third modeling tool builds strongly on the previous approaches and captures the microbial processes driving heterotrophic respiration. This ‘dormancy model’ allows the native soil microbial population to respond transiently to the presence or absence of water in order to catalyze carbon respiration. This approach was also compared to the simpler and more widely used first-order model using two experimental datasets with different temporal and spatial resolutions. Our results illustrate that the simpler first order model provides a robust and efficient representation of deep (>1 meter) soil respiration, but that shallow soils, where most respiration occurs, require explicit representation of moisture-dependent activation and dormancy rates. By assessing soil organic carbon turnover at multiple scales, we see a complex array of controls emerge. Atte scale of a hillslope, spatial heterogeneity in soil respiration rates dominates and is uncorrelated with instantaneous soil moisture and plant community. At the profile scale, the balance between plant inputs and water availability is the dominant control. At the microbial to molecular scale, physiological processes associated with carbon use and carbon speciation are important controls. These scale-dependent controls emphasize the need for new modeling approaches that examine their interactions and hierarchies.

54 ENVIRONMENTAL SCIENCES↗

Hybridized magnonic materials for THz frequency applications

The capability of magnons to hybridize and strongly couple with diverse excitations offers a promising avenue for realizing and controlling emergent properties that hold significant potential for applications in devices, circuits, and information processing. In this Letter, we present recent theoretical and experimental developments in magnon-based hybrid systems, focusing on the combination of magnon excitation in an antiferromagnet with other excitations, namely, plasmons in a topological insulator, phonons in a 2D antiferromagnetic (2D AFM), and photons. Here, the existence of THz frequency magnons, plasmons, and phonons makes magnon-based hybrid systems particularly appealing for high-operating-speed devices. In this context, we explore several directions to advance magnon hybrid systems, including strong coupling between a surface plasmon and magnon polariton in a topological insulator /AFM bilayer, a giant spin Nernst effect induced by magnon–phonon coupling in 2D AFMs, and control of magnon–photon coupling using spin torque.

36 MATERIALS SCIENCE↗

Hole-Trapping-Induced Stabilization of Ni 4+ in SrNiO 3 /LaFeO 3 Superlattices

Creating new functionality in materials containing transition metals is predicated on our ability to control the associated charge states. For a given metal, forming lower oxidation states is typically easier than generating higher values, and there is an upper limit on valence that is not exceeded under normal conditions. Here we demonstrate that we can exceed the normal upper limit of 3+ for Ni and Fe via synthesis of (SrNiO 3 )m/(LaFeO 3 )n superlattices by tuning n and m. The Goldschmidt tolerance constraints are lifted and SrNi 4+ O 3 with holes on adjacent O anions can be stabilized as a perovskite at the single unit cell level (m = 1). Spectroscopy reveals that the n = 1 superlattice contains Ni 3+ and Fe 4+ , whereas Ni 4+ and Fe 3+ are observed in the n = 5 superlattice. Here, our results show that the B-site cation valences can be tuned by controlling the magnitude of the FeO6 octahedral rotations which in turn drive the energy balance between Ni 3+ /Fe 4+ and Ni 4+ /Fe 3+ , thus controlling emergent electrical properties such as the band alignment and resulting hole confinement. We suggest that this approach may be generally useful for synthesizing novel, metastable layered structures with new functionalities.

36 MATERIALS SCIENCE↗

Boosting the sodium storage behaviors of carbon materials in ether-based electrolyte through the artificial manipulation of microstructure

The porous carbon blacks rationally designed by a facile yet efficient NH 3 thermal etching route have been investigated as anode materials in an ether-based electrolyte for sodium-ion batteries. The as-synthesized CBN35 carbon black with a 35% weight loss after NH3 thermal etching exhibited a large specific charge capacity of 352 mAh g -1 at 50 mA g -1 and a superior rate capability of 101 mAh g -1 at 16000 mA g -1 , due to its highest microporosity, an appropriate surface area, a desirable microstructure, and a promising hybrid intercalation mechanism. Impressively, even cycled at 1600 mA g -1 over 3200 cycles, an outstanding reversible capacity of 103 mAh g -1 with a negligible 0.0162% capacity loss per cycle can still be achieved. Based on the multimodal characterizations including the structural probes of phase evolution for carbon materials, the electrochemical techniques, and the surface-sensitive XAS measurements, the exceptional electrochemical properties should stem from several merits of modified carbon black system. While the particular microporous structure provides relatively more accessible sodium storage sites, a novel hybrid intercalation mechanism in ether-based electrolyte would incorporate the sodium ion insertion into the disordered structure with the solvated sodium ion species co-intercalation into the graphitic phase. In addition to the diffusion-controlled redox reactions, the noticeable surface-induced pseudocapacitive reactions also significantly contribute to the charge storage upon sodiation and guarantee the rapid migrations of sodium ions/solvated compounds. In conclusion, this system further features a controlled emergence of a robust but thin solid electrolyte interphase layer, which could suppress the side reactions of active electrode with reactive electrolyte, maintain the fragile porous structure upon cycling, and facilitate the migrations of sodium ions and solvated sodium ion compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗