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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies

Changing power system configuration may result in load shed recovery (LSR) because topology change can provide power flow control in meshed network. Some topologies may favor generation redispatch as compared to others and can eliminate line congestion which leads to LSR. One of the known methods for topology change is called transmission switching (TS) and research conducted in the past showed that TS is an effective means of mitigating load shedding. Another method of topology control is intentional islanding (IIS). In this manuscript, we explore IIS as a potential solution for LSR. IIS based on generator coherency has been presented in literature for mitigating cascading failures. However, IIS has not been explored solely as a LSR mechanism. In this paper, we compare the LSR based on IIS with well known LSR algorithm based on TS. The comparison is performed for IEEE 39-bus system and IEEE 118- bus system. The results show that IIS has a potential to perform better than TS in terms of computational efficiency and LSR.

42 ENGINEERING↗

The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

Abstract A computationally improved algorithm is presented to find the best transmission switching (TS) candidate for boosting resilience of electricity grids subject to ( N ‐2) contingencies. Here, resilience is computed as the reduction in load shed after the above‐mentioned ( N‐ ) contingencies. TS is a planned line outage, and past research shows that changing the transmission system's topology changes the power flow and removes post contingency violations. Finding the best TS candidate in a computationally suitable time for effectively boosting resilience is a challenge. The best TS candidate is found using a novel heuristic method by decreasing the search space based on proximity to the bus with the maximum load shedding (LSB). The LSB algorithm is faster than existing algorithms in the literature; and, it is compatible with both the AC and DC optimal power flow formulations. To validate the authors' claims of speedup and accuracy, two metrics are used to analyze the results from the IEEE 39‐bus and 118‐bus systems. Finally, the inherent parallelism of the LSB algorithm is leveraged on a high‐performance computing platform and applied to the large‐scale Polish 2383‐bus test system to validate scalability in both size and speedup in computation time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Improved Transmission Switching Algorithm for Managing Post-(N-1) Contingencies in Electricity Networks

In this presentation, we detail the shortcomings of existing transmission switching (TS) methodologies for preventing post-contingency loss of load in wide area electric power networks. Following that, we present a bi-level algorithm as an improvement to the state of the art. We show proof-of-concept level results that indicate computational viability, fast solutions, and the ability to pick the same best candidate as non computationally viable methods. Further, our method also minimizes load shedding after the contingency, thus enhancing the reliability and security of electricity supply. We also include a futuristic scenario of increased renewables and decreased natural gas sourced generators to show promising results. We grant permission for our presentation to be recorded and uploaded by the conference organizers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power System Resilience Considering Hurricane Storms and Generator Step-up Transformers

Power system resilience describes the system’s ability to withstand and recover quickly from unexpected power outages due to extreme events. As society’s electrification continues at a rapid rate, it is imperative electric infrastructure is designed and operated with extra security. This work studies the impact of severe hurricane storms on the power system located along the United States’ Eastern Seaboard. Specific focus is designated to steady state system operation and loss of large generation step up power transformers. A series of phasor domain power system simulations are conducted to determine the critical point at which the system loses steady state operability. Additionally, active power load shedding and generator dispatching are studied as mitigation and recovery strategies. Results indicate generator dispatching as an effective proactive mitigation strategy and load shedding as an effective recovery strategy.

Liu, Yilu↗

Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters

Abstract—Grid following inverter-based renewable generation has replaced conventional generation in recent years, resulting in lower system inertia. The frequency resilience in such a lower inertia system is critical for emergency mitigation. In this paper, we propose a resilience metric based on frequency recovery to quantitatively represent system resilience in terms of the rate of change of frequency. Application of grid-forming converters provides a means to improve system resilience by providing virtual inertia. An under-frequency load shedding strategy is applied to further support frequency recovery in cases with high penetration of grid-forming inverters. Case studies are designed and performed in a modified IEEE 9-bus test system using the PSCAD/EMTDC platform. Simulation results demonstrate the validity of the proposed resilience metric and the effectiveness of the strategy for reducing frequency excursion in inverter-based power systems. citation: J. Gui, H. Lei, T. R. McJunkin and B. K. Johnson, "Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters," 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1-5, doi: 10.1109/ISGT51731.2023.10066357.

14 SOLAR ENERGY↗

Barrier Function-based Reinforcement Learning for Emergency Control of Power Systems

Under voltage load shedding has been considered as a standard and effective measure to recover the voltage stability of the electric power grid under emergency and severe conditions. However, this scheme usually trips a massive amount of load which can be unnecessary and harmful to customers. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach that can significantly reduce the amount of load shedding. However, like most existing machine learning (ML)-based control techniques, RL control usually cannot guarantee the safety of the systems under control. In this paper, we introduce a novel safe RL method for load shedding of power systems, that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Unlike standard RL method, the safe RL method integrates a Barrier function into the reward function. Consequently, the optimal control policy can render the power system to avoid the safety bounds. This method is general and can be applied to other safety-critical control problems. Numerical simulations on the 39-bus IEEE benchmark is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.

Vu, Thanh Long↗

Safe Reinforcement Learning for Emergency Load Shedding of Power Systems

The paradigm shift in the electric power grid necessitates a revisit of existing control methods to ensure the grid’s security and resilience. In particular, the increased uncertainties and rapidly changing operational conditions in power systems have revealed outstanding issues in terms of either speed, adaptiveness, or scalability of the existing control methods for power systems. On the other hand, the availability of massive real-time data can provide a clearer picture of what is happening in the grid. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach leveraging massive data for fast and adaptive grid control. However, like most existing machine learning (ML)- based control techniques, RL control usually cannot guarantee the safety of the power systems. In this paper, we introduce a novel method for safe RL-based load shedding of power systems that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Numerical simulation on the IEEE 39-bus testcase is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.

reinforcement learning, emergency control, power g↗

Freestream turbulence effects on unsteady wind turbine loads and wakes: An IDDES study

We investigate numerically the effects of freestream turbulence on the unsteady aerodynamics and wakes of the National Renewable Energy Laboratory Phase VI wind turbine rotor for increasing wind speed. Turbulence is modeled using the Improved Delayed Detached-Eddy Simulation (IDDES) method. As a first step, a detailed mesh resolution study is conducted with the decaying freestream turbulence model at turbulence intensity of 0.5%. Our blade-resolved IDDES simulations show that grid-independent average torque and thrust results can be achieved with relatively coarse meshes, whereas dramatically higher mesh resolution is required for grid-independent results for power spectral densities of thrust force, especially in the deep-stall regime. Comparing the loads with the Shear-Stress Transport model demonstrates the superiority of IDDES in predicting massively separated flows. The aerodynamic performance and wake predictions with the decaying freestream turbulence model are compared with the synthetic freestream turbulence model. Both models predict nearly the same loads, spectral energy content, and wake characteristics. The properties of both the near- and far-wake regions are then examined. Furthermore, we show that separated boundary layers accelerate turbulent mixing and entrainment of the external flow, which results in faster wake recovery. The effect of increasing turbulence intensity to 6% is investigated using the synthetic freestream turbulence model. In contrast with the fully attached boundary layer, higher freestream turbulence in deep stall does not significantly affect the loads and vortex-shedding characteristics. However, the turbulent mixing in the wake is enhanced, which further hastens the recovery of the self-similar velocity profile. In general, increasing the wind speed at high turbulence intensity shifts the recovery farther upstream and increases the wake width.

17 WIND ENERGY↗

Photovoltaic Inverter Momentary Cessation: Recovery Process is Key

Momentary cessation refers to an inverter control mode. When the inverter terminal voltage falls below (or exceeds) a certain level, the inverter ceases to output any current, but attempts to maintain (or quickly regain) phase-locked loop synchronization to allow for quick reinjection of current when the voltage recovers to a certain point. This paper presents a photovoltaic (PV) momentary cessation model developed in PSS/E. Simulations are presented for a high voltage transmission line fault contingency in the Hawaiian island of Oahu power system on a validated PSS/E model, modified to include a custom distributed PV inverter model, and different near-future distributed PV penetration levels. Simulations for the island power system include different penetration levels of PV, and different recovery times (ramp rates and delays) after momentary cessation. The results indicate that during low voltage events, such as faults, momentary cessation can produce severe under frequency events, causing significant load shed and shortly thereafter, in some cases, over frequency events that cause generation to trip offline. The problem is exacerbated with higher penetration levels of PV. If momentary cessation is used (as is typically the case for distribution-connected resources), the recovery process after momentary cessation should be carefully considered to minimize impacts to bulk power system stability.

14 SOLAR ENERGY↗

Custom Controls for Improved Demand Response from Heat Pump Water Heaters

As part of a Grid Modernization Laboratory Consortium (GMLC) project looking at defining grid services for a range of devices, NREL used a custom controller to investigate the ability of a HPWH to provide load add and load shed in hybrid and electric resistance mode using standard set point control. Based on those results, changes were made to the controls to increase the amount of grid services delivered, especially in the load-add case, and speed up the recovery from those events. The custom controls also include less common methods, such as duty cycling of the heat pump or elements. The improved controls led to an increase the amount of demand response that could be provided and enabled faster recovery. Results from the laboratory experiments will be presented, along with details about the custom controls that were implemented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in real-world power systems under contingencies. However, existing emergency control schemes are rule-based and cannot be adaptively applied to uncertain and floating operating conditions. Here, we propose an adaptive UVLS algorithm for emergency control via deep reinforcement learning (DRL) and expert systems. We first construct dynamic components for picturing the power system operation as the environment. The transient voltage recovery criteria, which poses time-varying requirements to UVLS, is integrated into the states and reward function to advise the learning of deep neural networks. The proposed method has no tuning issue of coefficients in reward functions, and this issue was regarded as a deficiency in the existing DRL-based algorithms. Case studies illustrate that the proposed method outperforms the traditional UVLS relay in both the timeliness and efficacy for emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal Network Reconfiguration and Scheduling With Hardware-in-the-Loop Validation for Improved Microgrid Resilience

With the increased occurrence of various major extreme weather events, power outages and prompt power system restorations have recently drawn more attention to the resilience and recovery of power systems. From the perspective of a more resilient power delivery at the distribution grid, system restoration using network topology reconfiguration together with optimal scheduling of distributed energy resources are adopted in this paper. The proposed optimization model aims at minimizing the total load shedding cost and other operational costs, in which linearized topological constraints borrowed from graph theory and linearized DistFlow models are respectively used to maintain the radial network topology and power flow balance after system contingencies. To demonstrate the applicability of the proposed strategy, a real-world case study of a networked three-microgrid system in Adjuntas, Puerto Rico, is used with the consideration of different independent/interconnected microgrid scenarios, contingencies, and fairness settings. Furthermore, hardware-in-the-loop testing is conducted for the same three-microgrid network, where the closely matched results with the simulated ones have validated the effectiveness of the proposed restoration strategy, which is now ready to move one step forward towards field deployment. Finally, to test the proposed restoration strategy in a larger networked system, the modified IEEE-33 bus test distribution system is considered, and the results show a more resilient power delivery for critical loads under three and four line outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

In Situ Nano-Indentation of a Gold Sub-Micrometric Particle Imaged by Multi-Wavelength Bragg Coherent X-ray Diffraction

The microstructure of a sub-micrometric gold crystal during nanoindentation is visualized by in situ multi-wavelength Bragg coherent X-ray diffraction imaging. The gold crystal is indented using a custom-built atomic force microscope. A band of deformation attributed to a shear band oriented along the (221) lattice plane is nucleated at the lower left corner of the crystal and propagates towards the crystal center with increasing applied mechanical load. After complete unloading, an almost strain-free and defect-free crystal is left behind, demonstrating a pseudo-elastic behavior that can only be studied by in situ imaging while it is invisible to ex situ examinations. The recovery is probably associated with reversible dislocations nucleation/annihilation at the side surface of the particle and at the particle-substrate interface, a behavior that has been predicted by atomistic simulations. The full recovery of the particle upon unloading sheds new light on extraordinary mechanical properties of metal nanoparticles obtained by solid-state dewetting.

36 MATERIALS SCIENCE↗

Recyclable Cellulose Fiber Reinforced Vitrimer Composite

Vitrimer is an innovative class of polymeric materials which demonstrates traditional thermoset-like mechanical and chemical resilience while still being able to flow on demand like a traditional thermoplastic through covalently adaptive dynamic linkages. Herein, high-performance cellulose fiber reinforced vitrimer composites are developed using an epoxy-based vitrimer and natural cellulose paper. The reinforced vitrimer composite was fabricated by impregnating the porous structure of cellulose paper with two curable monomers, followed by in-situ polymerization of the monomers inside the fibrous scaffold. The introduction of hydroxyl group present on the cellulosic framework assisted in a faster topological rearrangement of the crosslinked matrix through transesterification exchange reaction, thus imparting various sought-after properties like shape recovery and recyclability via simple thermal reprocessing. Moreover, the reinforced vitrimer composite exhibits superior tensile properties as high as 90 MPa with 15-25 volume% vitrimer loading due to the interfacial adhesion via ester exchange reaction between the epoxy matrix and functionalities on the cellulosic fibers. Noteworthily, the key ingredients of the resulting composite (i.e., epoxy-based vitrimer and cellulose fibers) can be comfortably recycled without using aggressive chemical treatment, enabling composite to be easily recycled or disposed of at the end of service life and assist in reducing the subsequent manufacturing cost. This study would shed light on the development of a recyclable polymer composite with exceptional mechanical properties while simultaneously demonstrating self-healing and shape memory capabilities.

Rohewal, Sargun Singh↗

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↗

Dynamic flow stress of pure polycrystalline aluminum: Pressure-shear plate impact experiments and extension of dislocation-based modeling to large strains

The dynamic thermo-mechanical behavior of pure aluminum has attracted renewed interest lately due to experimental observations of an anomalous increase in Hugoniot Elastic Limit (HEL) at incipient plasticity and elevated temperatures in polycrystalline pure metals. In context of current dislocation-mediated plasticity models for metals, this increase in dynamic strength is indicative of a transition in the rate controlling mechanism for dislocation glide from being thermally assisted to phonon-drag restricted due to increase in phonon viscosity at elevated temperatures. Though these studies have helped to shed light on these important mechanisms operative in FCC metals at incipient plasticity, the extent to which they contribute to flow stress, particularly at larger strains, remains unclear. Here, we address these questions through a combined experimental and modeling effort focused on investigating the evolution of dynamic flow stress in polycrystalline aluminum using experimental data gathered from a series of combined pressure-and-shear plate impact (PSPI) experiments designed to reveal the flow stress of pure aluminum at strain rates ~ 10 5 /s, plastic strains of up to 40% and temperatures ranging from room to 866 K. In all cases, the flow stress of aluminum, as inferred from the measured transverse particle velocity histories at the free surface of an elastic tungsten carbide target plate, reveals saturation with increasing plastic strains at stress levels that decrease with increasing test temperatures. Numerical simulations are performed to correlate the experimentally observed temperature and strain rate dependence of flow stress at small and large plastic strains using the Austin-McDowell dislocation-mediated plasticity model parametrized to normal plate impact experiments conducted in an earlier study by Zaretsky and Kanel (2012). Extensions to the model are made to better represent dynamic behavior of pure aluminum at larger plastic strains as observed in elevated temperature split Hopkinson Pressure bar (SPHB) experiments of Samanta (1971) and Lindholm and Yeakly (1965), and the combined pressure-and-shear plate-impact experiments conducted in the present study. The main theoretical extension to the Austin-McDowell model made in this paper is the introduction of a new rate- and temperature- dependent dynamic recovery function, which can potentially allow for an effective reduction in the rate of accumulation of dislocations at large plastic strains. The numerical predictions of the revised and re-calibrated plasticity model are brought into agreement with the experimental observations, correlating sufficiently well with dynamic yield stress at incipient plasticity and the flow stress levels at larger plastic strains, plastic strain rates in the range 10 3 – 10 6 /s, and elevated temperatures up to near melt. The model, in concert with the experimental measurements, suggests that at incipient plasticity the rate governing mechanism for plastic flow is phonon-drag restricted dislocation glide, whereas, at higher magnitudes of plastic strain, it transitions to stress-assisted thermally activated glide. The transition between these two rate governing mechanisms is controlled by the evolution of dislocations throughout the deformation process.

36 MATERIALS SCIENCE↗