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At least 55 records · Page 3

Stability and control of power systems with high penetrations of inverter-based resources: An accessible review of current knowledge and open questions

As power system renewable energy penetrations increase, the ways in which key renewable technologies such as wind and solar photovoltaics (PV) differ from thermal generators become more apparent. Many studies have examined the variability and uncertainty of such generators and described how generation and load can be balanced for a wide variety of annual energy penetrations, at timescales from seconds to years. Another important characteristic of these resources is asynchronicity, the result of using inverters to interface the prime energy source with the power system as opposed to synchronous generators. Unlike synchronous generators, whose frequency of alternating current (AC) injection is physically coupled to the rotation of the machine itself, inverter based asynchronous generators do not share the same physical coupling with the generated frequency. These subtle differences impact the operations of power systems developed around the characteristics of synchronous generators. In this paper we review current knowledge and open research questions concerning the interplay between asynchronous inverter-based resources (IBRs) and cycle- to second-scale power system dynamics, with a focus on how stability and control may be impacted or need to be achieved differently when there are high instantaneous penetrations of IBRs across an interconnection. This work does not seek to provide a comprehensive review of the latest developments, but is instead intended to be accessible to any reader with an engineering background and an interest in power systems and renewable energy. As such, the paper includes basic material on power electronics, control schemes for IBRs, and power system stability; and uses this background material to describe potential impacts of IBRs on power system stability, operational challenges associated with large amounts of distributed IBR generation, and modern power system simulation trends driven by IBR characteristics.

14 SOLAR ENERGY↗

Energy Transitions Initiative Partnership Project: City and Borough of Sitka, Alaska - Modeling and Controls Assistance and Renewable Energy Resource Assessment [Slides]

This presentation provides a summary of the ETIPP project objectives and findings for Sitka, Alaska, including sizing of wind penetration, dynamic models, and analysis of efficiency of load control, stability and grid control impacts of wind capacity expansions and locations, and wind-hydro control coordination.

17 WIND ENERGY↗

Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines

In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.

Maldonado Puente, Bryan↗

On Distributed Model-Free Reinforcement Learning Control with Stability Guarantee

Distributed learning can enable scalable and effective decision making in numerous complex cyber-physical systems such as smart transportation, robotics swarm, power systems, etc. However, the stability of the system is usually not guaranteed in most existing learning paradigms; and this limitation can hinder the wide deployment of machine learning in decision making of safety-critical systems. This paper presents a stability guaranteed distributed reinforcement learning (SGDRL) framework for interconnected linear subsystems, without knowing the subsystem models. While the learning process requires data from a peer-to-peer (p2p) communication architecture, the control implementation of each subsystem is only based on its local state. The stability of the interconnected subsystems will be ensured by a diagonally dominant eigenvalue condition, which will then be used in a model-free RL algorithm to learn the feedback control gains. The RL algorithm structure follows an off-policy iterative framework, with interleaved policy evaluation and policy update steps. We numerically validate our theoretical results by performing simulations on four interconnected sub-systems.

Mukherjee, Sayak↗

Stabilization and control of persistent current magnets using variable inductance

Ultra-stable, tunable magnetic fields are desirable for a wide range of applications in medical imaging, electron microscopy, quantum science, and atomic physics. Superconducting magnets operated in persistent current mode, with device current flowing in a closed superconducting loop disconnected from a power source, are a common approach for applications with the most stringent requirements on temporal field stability. In this work, we present a method for active control of this persistent current by means of dynamic inductance change within the superconducting circuit. For a first realization of this general technique, we consider a variable superconducting inductor placed in series with the main magnet. The inductor acts as a dynamic flux storage device capable of transferring flux to or from the main magnet through inductance change. This allows for fine and fast adjustments of the persistent current without the use of thermal switches that limit the speed and accuracy of many present-day methods. With first experiments employing this technique, we demonstrate stabilization of a 1.95 T Nb–Ti round lens for electron microscopy against decay resulting from residual losses in the superconducting circuit, and more generally show flexibility for precise control over the magnitude and waveform of the persistent current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Small-Signal Analysis of Current-Limiting Grid-Forming Inverters

Grid-forming (GFM) inverters are equipped with a current limiter to protect the device during grid disturbances. Because the intervention of the current limiter can compromise the transient stability of the GFM inverter, various types of current limiter designs and additional frequency-stabilization control methods have been proposed in recent literature to aid in transient GFM inverter stability; however, the small-signal stability implications of adding these additional control blocks during, in particular, off-nominal conditions are not fully understood. To address this challenge, this paper presents a generic small-signal model of a GFM inverter that incorporates various types of current limiters and frequency stability-enhancing controls. With the proposed model, we analyze the root causes of inverter instability, which reveals two critical design trade-offs. First, due to current-limiter engagement caused by a disturbance, the GFM inverter dynamics are altered, which can lead to voltage oscillations. Second, additional frequency-stabilization controls can improve the small-signal stability of the GFM inverter, but at the cost of reduced power and voltage support to the grid. Comprehensive hardware experiments validate the theoretical concept and analysis. The findings in this work underscore the importance of incorporating both transient-response and small-signal dynamics requirements into the design procedure of GFM current limiters and frequency-stabilization controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hierarchical Control and Stability Analysis for a Nonisolated Grid-Tied DC Energy Router Integrating Energy Storage and Partial Distributed Generation

This article proposes a nonisolated dc converter-based energy router (dc-ER) and its operating strategy. Here, the intent is to integrate energy storage (ES), distributed generation (DG), local load, and dc power grid in an autonomous and more efficient way. The ES/DG power ports are coupled with each other in partial-type connections, which obtains higher voltage supply gain and direct input–output power transmission. High-voltage supply gain allows a wide solar power tracking range and the possibility of optimal battery charging/discharging. Direct input–output power transmission improves the energy conversion efficiency. In this article, the operating modes of dc-ER are first analyzed, followed by the optimal hardware design counting the DG current ripple minimization and the limitation caused by the power flow direction. Second, the mathematical model of dc-ER is deduced. The hierarchical control is then proposed to manage port energy in a flexible manner. The stability is analyzed by using impedance modeling. Finally, experimental and simulation results verify the superiorities of the proposed topology in terms of flexible operating mode transition and high-power conversion efficiency.

25 ENERGY STORAGE↗

Model Predictive Control for Urban Traffic Signals with Stability Guarantees

Traditional traffic signal control focuses more on the optimization aspects whereas the stability and robustness of the closed-loop system are less studied. This paper aims to establish the stability properties of traffic signal control systems through the analysis of a practical model predictive control (MPC) scheme, which models the traffic network with the conservation of vehicles based on a store-and forward model and attempts to balance the traffic densities. More precisely, this scheme guarantees the exponential stability of the closed-loop system under state and input constraints when the inflow is feasible and traffic demand can be fully accessed. Practical exponential stability is achieved in case of small uncertain traffic demand by a modification of the previous scheme. Simulation results of a small-scale traffic network validate the theoretical analysis.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Controlling the corrosion resistance of multi-principal element alloys

Multi-principal element alloys (MPEAs) offer the possibility of many degrees of freedom in the choice of alloying elements to produce either single phase solid solutions or more complex multiphase microstructures. Large ranges of material properties have been observed for MPEAs and mastery of the selection of elements and their compositions can enable novel combinations of properties not possible in traditional alloys. From the aqueous corrosion perspective, optimization of phase stability, control of heterogeneities, passive film identity and its protectiveness, as well as substrate properties such as metal-metal bond strength and activation energy associated with dissolution, can all be controlling factors governed by alloy composition and structure. These factors can mediate the electrochemical reactions controlling spontaneous corrosion. The quest for superior properties based on well-informed element choice is suggested as a path forward guiding MPEA formulations for corrosion performance. However, gaps in fundamental knowledge exist regarding (a) the specific functions of each element, (b) the behavior of elements in unusual combinations, and (c) the formation of complex protective oxides. These issues currently hold back progress in optimization of corrosion properties.

Scully, John R.↗

Pericytes control vascular stability and auditory spiral ganglion neuron survival

The inner ear has a rich population of pericytes, a multi-functional mural cell essential for sensory hair cell heath and normal hearing. However, the mechanics of how pericytes contribute to the homeostasis of the auditory vascular-neuronal complex in the spiral ganglion are not yet known. In this study, using an inducible and conditional pericyte depletion mouse (PDGFRB-CreER T2 ; ROSA26iDTR) model, we demonstrate, for the first time, that pericyte depletion causes loss of vascular volume and spiral ganglion neurons (SGNs) and adversely affects hearing sensitivity. Using an in vitro trans-well co-culture system, we show pericytes markedly promote neurite and vascular branch growth in neonatal SGN explants and adult SGNs. The pericyte-controlled neural growth is strongly mediated by pericyte-released exosomes containing vascular endothelial growth factor-A (VEGF-A). Treatment of neonatal SGN explants or adult SGNs with pericyte-derived exosomes significantly enhances angiogenesis, SGN survival, and neurite growth, all of which were inhibited by a selective blocker of VEGF receptor 2 (Flk1). Our study demonstrates that pericytes in the adult ear are critical for vascular stability and SGN health. Cross-talk between pericytes and SGNs via exosomes is essential for neuronal and vascular health and normal hearing.

59 BASIC BIOLOGICAL SCIENCES↗

Manipulating Retained Austenite Fraction and Stability With Controlled Chemical Heterogeneities in Q&P Steels

Advanced high-strength steels go through complex heat treatment processes with the goal of retaining austenite to enhance the mechanical properties. Martensite start temperature predictions are generally based on bulk composition when designing heat treatments, so compositional heterogeneities are not considered. Here, the effects of compositional heterogeneities on retained austenite fractions in a quenching and partitioning steel are investigated. In conclusion, the results show that Mn banding from solidification can be used to change retained austenite fractions.

36 MATERIALS SCIENCE↗

Surface Equilibration Mechanism Controls the Stability of a Model Codeposited Glass Mixture of Organic Semiconductors

While previous work has identified the conditions for preparing ultrastable single-component organic glasses by physical vapor deposition (PVD), little is known about the stability of codeposited mixtures. Here, we prepared binary PVD glasses of organic semiconductors, TPD (N,N'-Bis(3-methylphenyl)-N,N'-diphenylbenzidine) and m-MTDATA (4,4',4"-Tris[phenyl(m-tolyl)amino]triphenylamine), with a 50:50 mass concentration over a wide range of substrate temperatures (T sub ). The enthalpy and kinetic stability are evaluated with differential scanning calorimetry and spectroscopic ellipsometry. Binary organic semiconductor glasses with exceptional thermodynamic and kinetic stability comparable to the most stable single-component organic glasses are obtained when deposited at T sub = 0.78–0.90T g (where T g is the conventional glass transition temperature). When deposited at 0.94T g , the enthalpy of the m-MTDATA/TPD glass equals that expected for the equilibrium liquid at that temperature. Thus, the surface equilibration mechanism previously advanced for single-component PVD glasses is also applicable for these codeposited glasses. Furthermore, these results provide an avenue for designing high-performance organic electronic devices.

36 MATERIALS SCIENCE↗

A Guanidine-Degrading Enzyme Controls Genomic Stability of Ethylene-Producing Cyanobacteria

Recent studies have revealed the prevalence and biological significance of guanidine metabolism in nature. However, the metabolic pathways used by microbes to degrade guanidine or mitigate its toxicity have not been widely studied. Here, via comparative proteomics and subsequent experimental validation, we demonstrate that Sll1077, previously annotated as an agmatinase enzyme in the model cyanobacterium Synechocystis sp. PCC 6803, is more likely a guanidinase as it can break down guanidine rather than agmatine into urea and ammonium. The model cyanobacterium Synechococcus elongatus PCC 7942 strain engineered to express the bacterial ethylene-forming enzyme (EFE) exhibits unstable ethylene production due to toxicity and genomic instability induced by accumulation of the EFE-byproduct guanidine. Co-expression of EFE and Sll1077 significantly enhances genomic stability and enables the resulting strain to achieve sustained high-level ethylene production. These findings expand our knowledge of natural guanidine degradation pathways and demonstrate their biotechnological application to support ethylene bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

Physics basis for the reference flat-top plasma scenario in the ST–E1 fusion power plant

As part of the U.S. Department of Energy’s Milestone-Based Fusion Energy Development Program, Tokamak Energy has completed the pre-concept design of the ST–E1 fusion power plant. ST–E1 is envisaged to operate in two phases: a pilot plant phase, targeting sustained net power production of 300 - 500 MWe for a duration >1 hr, followed by a commercial power plant phase targeting steady-state operations and a normalised overnight capital cost of ⩽12 000 $\$$/kWe. The design process adopted was highly iterative, integrating all major plant systems and progressing in a phased fidelity approach. At the pre-conceptual stage, the emphasis has been on exploring the design space, identifying the main system-level trade-offs, and making the key decisions that define the overall plant concept, rather than optimising a single operating point. This paper, part of a focused collection detailing the ST–E1 pre-concept design, addresses the development of a series of reference flat-top plasma operating points for the pilot plant phase. A modelling workflow was established to develop and assess candidate plasma design points and explore key dependencies. The workflow includes integrated core plasma modelling, magnetohydrodynamic (MHD) stability assessment, equilibrium generation, scrape-off-layer and exhaust modelling, heating & current drive design and optimisation, and turbulent transport modelling. Using this framework, the impact of several key parameters on the flat-top operating space was investigated, including the density limit, core radiation fraction and divertor power loading, level of external heating and curent drive power and assumed pedestal characteristics. The MHD stability, controllability and micro-stability characteristics of these plasmas were also analysed. These investigations informed the definition of a set of fully non-inductive, flat-top reference operating points that satisfy the high-level ST–E1 mission, including a low and high density case, a case that is stable to resistive wall modes and a case with reduced divertor power loading.

ST–E1↗

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↗