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At least 883 records · Page 49

Direct Experimental Proof of the Principal Role of Reduced High-Mode Hydrodynamic Mix in Recent Ignition Success on NIF

This Letter details the role of reduced hydrodynamic mix in achieving the first fusion plasma to satisfy the Lawson criterion for ignition. Using novel 3D measurements of the temperature and density of the burning deuterium-tritium plasma across a series of experiments, we demonstrate that hydrodynamic mixing from small-scale capsule defects was a key degradation mechanism inhibiting ignition. A series of five layered deuterium-tritium experiments using 1.9 MJ of laser energy demonstrates a 2 × reduction of the thermonuclear yield when a lower quality capsule, typical of preignition experiments, is used. Radiation hydrodynamic calculations consistent with the observed mix profile show that the mixed fuel’s reduced compression and increased radiative loss explain the yield reduction. Furthermore, a hydroscaling argument suggests that a ∼ 3 MJ laser would be needed to reach ignition with such a capsule, well beyond the current capabilities of high energy laser systems. As such, this Letter gives critical insight into the physics of mix in self-heated fusion plasmas and establishes a foundation to evaluate capsule quality needs of future inertial fusion designs that aim at ignition and high gain.

High-energy-density plasmas↗

Evolution of texture and internal stresses within polycrystalline rock salt using in situ 3D synchrotron computed tomography and 3D X-ray diffraction

Over time rock salt caverns have been extensively used as reliable repositories for hazardous waste such as nuclear waste, oil or compressed gases. Undisturbed rock salt deposits in nature are usually impermeable and have very low porosity. However, rock salt formations under excavation stresses can develop crack networks, which increase their porosities; and in the case of a connected crack network within the media, rock salt may become permeable. Although the relationship between the permeability of rock salt and the applied stresses has been reported in the literature, a microscopic study that investigates the properties influencing this relationship, such as the evolution of texture and internal stresses, has yet to be conducted. This study employs in situ 3D synchrotron micro-computed tomography and 3D X-ray diffraction (3DXRD) on two small-scale polycrystalline rock salt specimens to investigate the evolution of the texture and internal stresses within the specimens. The 3DXRD technique measures the 3D crystal structure and lattice strains within rock salt grains. The specimens were prepared under 1D compression conditions and have shown an initial {111} preferred texture, a dominant {110}$\langle1\bar{1}0\rangle$ slip system and no fully connected crack network. The {111} preferred texture under the unconfined compression experiment became stronger, while the {111}$\langle1\bar{1}0\rangle$ slip system became more prominent. The specimens did not have a fully connected crack network until applied axial stresses reached about 30 MPa, at a point where the impermeability of the material becomes compromised due to the development of multiple major cracks.

36 MATERIALS SCIENCE↗

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION↗

On-Chip Batteries as Distributed Energy Sources in Heterogeneous 2.5D/3D Integrated Circuits

Energy efficiency in digital systems faces challenges due to the constraints imposed by small-scale transistors. Moreover, the growing demand for portable consumer electronics necessitates the use of compact energy sources. To address these challenges, heterogeneous 3D IC technology has emerged as a promising solution for the former. Regarding the latter, we propose the concept of distributed batteries within a heterogeneous 3D IC. This approach involves utilizing multiple smaller batteries with different specifications among different modules of 3D ICs. This approach optimizes performance and overcomes limitations associated with both 3D ICs and conventional power delivery methods. Distributed batteries play a vital role in effectively managing the heat generated by energy sources and modules within a 3D IC. Furthermore, they contribute to achieving a uniform distribution of heat throughout the entire structure, which ultimately ensures the optimal performance of the batteries and modules. The simulation results indicate a 40 percent enhancement in achieving a more even distribution of generated heat. Additionally, the proposed distributed battery techniques improve power delivery, enhance reliability, and enable optimized voltage regulation while improving efficiency. In addition to the primary benefits, alternative configurations of the proposed approach can offer extra energy storage capacity and act as efficient electromagnetic shields, resulting in an impressive reduction of external electromagnetic noises by 60 dB.

47 OTHER INSTRUMENTATION↗

Secure and Cost-Effective Micro Phasor Measurement Unit (PMU)-Like Metering for Behind-the-Meter (BTM) Solar Systems using Blockchain-Assisted Smart Inverters

Recently, there is increasing interest in using behind-the-meter (BTM) solar systems for grid services. However, providing visibility and operational situational awareness of BTM solar systems mainly operated by small-scale solar inverters is challenging due to the requirement of relatively expansive networked observation tools (e.g., micro phasor measurement units (µPMUs)) and consequent cybersecurity threats through networks. This paper presents a secure, cost-effective, µPMUs-like metering method using a blockchain-assisted smart (BAS) inverters for a BTM solar system. The proposed BAS inverter consisting of an internet of things device as a node of a local blockchain network enables the secure provision of inverter measurement data for grid services. The BAS inverter sends the encrypted local measurement data with a timestamp to a local blockchain miner. Once the blockchain miner generates a tamper-resistant metering ledger including the measurements, it is used to assess the situational awareness of the BTM solar system. The concept of the proposed metering using the BAS inverters is validated by experimental studies.

behind the meter↗

On Stability of PQ-Controlled Grid-Following and Droop-Control Grid-Forming Inverters

In this paper, the nonlinearity impacts of PQ-control schemes and LCL filter parameter variations on the stability of grid-interactive inverters are studied under weak grid conditions. This work demonstrates that the control nonlinearity and parameter variations can cause unexpected instability at low power levels. This instability issue in the nominal operating range may occur under specific control parameters due to the shift of the low-frequency eigenvalues of PQ-controlled inverters. A full-order small-signal model for PQ-controlled inverters is applied to analyze this instability issue. Furthermore, the impacts of the droop coefficients on the stability of the droop-controlled grid-forming inverter are also investigated using the closed-loop inverter model. The findings are experimentally verified using a small-scale two-level 208 V, 5 kVA inverter feeding a 12 kW NHR 9410 power grid emulator and a hardware setup of a microgrid fed by two 5 kVA 208V inverters.

Hossen, Tareq↗

Encapsulation Residual Stress and Ferrite Loss in Inductive Coil Assemblies

As inductive wireless charging reaches higher power levels, thermal management and mechanical durability become more critical. To address these concerns, past works have demonstrated the benefit of encapsulating coil assemblies in thermally conductive materials. However, due to the sensitivity of the MnZn ferrites commonly used in coil assemblies to mechanical stress, care must be taken to avoid creating large stresses in the ferrite that cause higher hysteresis loss. The stress formation in the encapsulant curing process is overviewed and modeled and an experiment is performed to demonstrate the effect in a small-scale coil assembly. Finally, the effect is shown in the reduced coil-coil efficiency of a first generation high power inductive power transfer prototype using a stiff epoxy compared to better performance in a second prototype using a softer thermally-conductive silicone encapsulant.

Foote, Andrew↗

Implementation of Advanced Grid Support Functionalities by Smart Operation of Residential Loads with low Cost Converter Interface

This paper investigates a grid-supportive load concept for small-scale residential appliances, focusing on a residential refrigerator. Power consumption is adjusted based on grid conditions to achieve IEEE-1547 grid support functions. Two key aspects are presented: a low-cost refrigerator converter with Lyapunov energy function-based local controllers for speed control, and the impact on a standard microgrid system, demonstrating advanced grid support from the load side. This method enhances grid resilience and reliability and can be extended to other residential loads. The study contributes to efficient and robust grid-supportive load management systems, showing promising performance. This approach has the potential to improve overall grid stability and can be adapted for various types of residential appliances. The modeling and simulations in MATLAB/Simulink and PLECS confirm the feasibility and effectiveness of the proposed solution. Future work will explore real-world implementation and scalability of this concept for broader applications.

grid supportive loads (GSL)↗

On Projection of Safe Operation for Grid-Following Inverters - Grid Parameter Estimation

This work investigates the projection of safe operation for grid-following inverters using a reference model. This work applies recursive-least square and model reference adaptive estimation techniques to estimate the unknown grid parameters. The estimated grid parameters are used in a dynamic reference model to project the safe operation of the inverter. This work also demonstrates that the controller nonlinearity and parameter variations can cause unsafe operations, such as unexpected instability at low power levels, namely hidden mode of instability. This instability issue in the nominal operating range may occur for given control parameters in a weak-grid condition. The dynamic reference model for PQ-controlled inverters is applied to analyze this instability issue using the estimated grid parameters. Both adaptive identification techniques can estimate the unknown parameters accurately, and the dynamic reference model can safeguard inverters from an unsafe operation, i.e., hidden instability, by examining the incoming new power setpoints before engaging them to the local controller. The findings are experimentally verified using a small-scale two-level 208 V, 5 kVA inverter feeding a 12 kW NHR 9410 power grid emulator.

Hossen, Tareq↗

Real-World Cyber Security Demonstration for Networked Electric Drives

In this article, we present the design and implementation of a cyber-physical security testbed for networked electric drive systems, aimed at conducting real-world security demonstrations. To our knowledge, this is one of the first security testbeds for networked electric drives, seamlessly integrating the domains of power electronics and computer science, and cybersecurity. By doing so, the testbed offers a comprehensive platform to explore and understand the intricate and often complex interactions between cyber and physical systems. The core of our testbed consists of four electric machine drives, meticulously configured to emulate small-scale but realistic information technology (IT) and operational technology (OT) networks. This setup both provides a controlled environment for simulating a wide array of cyber-attacks, and mirrors potential real-world attack scenarios with a high degree of fidelity. The testbed serves as an invaluable resource for the study of cyber-physical security, offering a practical and dynamic platform for testing and validating cybersecurity measures in the context of networked electric drive systems. As a concrete example of the testbed's capabilities, we have developed and implemented a Python-based script designed to execute step-stone attacks over a wireless local area network (WLAN). This script leverages a sequence of target IP addresses, simulating a real-world attack vector that could be exploited by adversaries. To counteract such threats, we demonstrate the efficacy of our developed cyber-attack detection algorithms, which are integral to our testbed's security framework. Furthermore, the testbed incorporates a real-time visualization system using InfluxDB and Grafana, providing a dynamic and interactive representation of networked electric drives and their associated security monitoring mechanisms. This visualization component not only enhances the testbed's usability but also offers insightful, real-time data for researchers and practitioners, thereby facilitating a deeper understanding of cyber-physical security dynamics in networked electric drive systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multicarrier Energy Systems: Shaping Our Energy Future

Multicarrier energy systems (MCESs) are characterized by strong coordination in operation and planning across multiple energy vectors and/or sectors to deliver reliable, cost-effective energy services to end users/customers with minimal impact on the environment. They have efficiency and flexibility benefits and are deployed in large and small scales on the supply and demand sides and at the network level but are more complex to control and manage. Here, MCESs are reviewed in the context of future low carbon energy systems based on electrification and very high variable renewable energy penetrations. Fully exploiting these systems requires some cost reductions, more sophisticated operations enabled by standardized communications and control capabilities detailed planning paradigms, and addressing their corresponding economic challenges. All these point toward the direction of analysis, markets, and technology research and development coupled with better policy and regulatory frameworks. One futuristic vision of a very low carbon energy system is proposed that illustrates potential pathways to an MCES-dominated energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Machine Learning Pattern Recognition Algorithm With Applications to Coherent Laser Combination

Herein we analyze a new kind of machine learning algorithm designed to feedback stabilize coherently combined lasers. This algorithm learns differential, rather than absolute, values of action in phase space, in order to facilitate learning on initially unstable systems. Experiments have shown that this approach can control small-scale spatial beam combination with high stability. In this paper we analyze the algorithm's performance and limitations in depth, showing that it can continuously learn during operation in order to track changes. Using simulation, we extend the application to temporal combination, and show that it scales to more complex instances by combining 81 beams.

97 MATHEMATICS AND COMPUTING↗

Mining Smart Meter Data to Enhance Distribution Grid Observability for Behind-the-Meter Load Control: Significantly improving system situational awareness and providing valuable insights

Distributed Energy Resources (DERs) are playing an increasingly important role in power systems. In 2023, five categories of DERs-distributed solar, electric vehicles (EVs), energy storage, residential smart thermostats, and small-scale combined heat and power-are expected to contribute about 104 GW to the U.S. summer peak (see GTM, 2018). With the increasing integration of DERs in power distribution systems, distributed load control is imperative to smooth the fluctuations that they introduce. However, a main challenge is that distribution systems lack systematic situational awareness because of their limited sensors. Furthermore, most customer-level behind-the-meter (BTM) DERs, such as rooftop photovoltaics (PVs), are being integrated into distribution systems, which complicates the system monitoring and control. Furthermore, enhanced electric grid monitoring is needed to promote renewable integration while ensuring reliability, but current approaches rely on expensive sensors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Optimization Approaches with Discrete Variables in the Power Distribution Systems

Traditionally, centralized approaches have predominantly been used for the power system operation and control. With increasing penetration of small-scale distributed energy resources (DERs) in the distribution network, especially independently owned renewable resources, distributed algorithms can serve as a potential alternative for improving scalability, resiliency and addressing privacy concerns. However, the complexity of distributed algorithms significantly increases with the integration of the legacy devices, the operation of which depend on discrete control variables. This paper aims to provide a review of the distributed optimization algorithms incorporating discrete control variables for the power distribution system. While the research in this domain is still at its nascence, an extensive comparison of the approaches in the literature for applying quadratic penalty, branch and bound,ordinal optimization and proximal operator to handle discrete variables in the framework of ADMM and dual decomposition have been addressed. Future research direction in this field have been also provided.

Adan, Jannatul↗

Self-Powered Autonomous Sensing System for Arctic Ocean using a Frequency-multiplied Cylindrical Triboelectric Nanogenerator

An autonomous sensing system for collecting environmental observations in the Arctic region is critical for the estimation and prediction of climate change. Ocean waves are a great source of energy for these sensing systems but there has been limited research done on small-scale energy harvesting applications in the Arctic Ocean (subsea or surface). The available wave energy in the Arctic Ocean is lower than the typical ocean wave energy due to the low wave frequency, height, and operating months. Although the available wave energy depends on the specific location in the Arctic Ocean, the wave height decreases everywhere during the winter (Jan-March) [1]. Our target location in this work is the Beaufort and Chukchi Seas, which are ice covered for about 195 days per year leaving only a few months (June-November) for wave energy harvesting [2]. During these few months, the average wave frequency is 0.2 Hz and the most common wave frequency is around 0.15 Hz. Many energy harvesting methods are unsuitable for use in the Arctic Ocean because of to the cold temperature, low wave frequency, and low wave height. Triboelectric nanogenerators (TENG) are one of the few energy harvesting methods that excel in these conditions. Zhong et al. [3] designed a stacked pendulum-structured TENG for low-frequency ocean wave energy and reported the device generated a peak power density of 11.2 W/m3 under the low wave frequency of 0.2 Hz. The autonomous sensing system we developed for the Arctic Ocean, the Arctic-TENG, is based on a frequency-multiplied cylindrical TENG (FMC-TENG) which is an optimized TENG configuration for Arctic Ocean conditions due to the high power density under low-frequency wave conditions [4]. Figure 1 shows an FMC-TENG with multiple pairs of free-standing triboelectric-layer mode materials (Aluminum and FEP). The mass and magnet attached to the rotor store gravitational potential energy which is released as kinetic energy when the potential energy overcomes the repulsive magnetic force generated by the opposing magnet attached to the stator. This force unbalance triggers a sudden rotation and swinging motion of the mass which increases the angular velocity of the system and therefore enhances the output power of the TENG system. The main components of the Arctic-TENG are a 3D-printed rotor and stator, electric and dielectric material adhesive tape, and bearings. All these materials were cold-soaked and tested at -40 °C in a chest freezer. Both the 3D-printed parts and adhesives were confirmed to have a minimal effect from the cold temperature. Multiple bearings were tested and the starting torque of each one was compared both at room temperature and -40 °C. The bearing with the lowest starting torque at -40 °C was selected for use in the Arctic-TENG. The Arctic-TENG was tested using an out-of-water motor-driven wave simulator (Figure 2). The wave simulator allows for controlled testing at a wave height of 0.2 m and frequencies between 0.1 Hz to 0.5 Hz. This wave simulator was used for both room temperature and -40 °C testing. The Arctic-TENG generated significantly more power at -40 °C compared to room temperature for each frequency tested. The system stored energy in a supercapacitor via a power management circuit, and the amount of energy stored per day was calculated at different wave frequencies. Based on the conditions at the proposed deployment location (days of non-ice-covered ocean and wave frequency), the amount of stored energy per year from Arctic-TENG was calculated to be enough energy for two transmissions every day. Durability testing was completed on the Arctic-TENG at room temperature to determine the lifetime. The rotor of the Arctic-TENG was attached to a DC motor and spun continuously for several millions of cycles without degradation of the electrical output, demonstrating the feasibility for long-term operation.

Jung, Hyunjun↗

DSP Implementation of a Novel Recurrent Neural Network Controller into a TI Solar Microinverter

Single-phase grid-tied inverters are widely used to integrate small-scale renewable energy sources and distributed generations to the utility grid. A novel Recurrent Neural Network (RNN) current controller is introduced to solve the resonant problem associated with LCL based inverters. The well-trained RNN controller was validated through a Texas Instruments (TI) LCL filter based solar microinverter kit that contains a C2000 TI microcontroller. The inverter closed current loop test without the grid connection was conducted in a laboratory setup to verify the RNN contoller functionality. The laboratory waveform results verified that the RNN current controller produced the strong tracking of the measured inverter AC current to its reference value even at a low sampling frequency of 5KHz. The proposed RNN current controller also proved to perform better than the built-in three-pole-three-zero (3P3Z) current controller provided by TI and produce lower values of Total Harmonic Distortion (THD).

digital signal processor↗

Dynamic Shaping of Grid Response of Multi-Machine Multi-Inverter Systems Through Grid-Forming IBRs

We consider the problem of controlling the frequency response of weakly-coupled multi-machine multi-inverter low-inertia power systems via grid-forming inverter-based resources (IBRs). In contrast to existing methods, our approach relies on dividing the larger system into multiple strongly-coupled subsystems, without ignoring either the underlying network or approximating the subsystem response as an aggregate harmonic mean model. Rather, through a structured clustering and recursive dynamic shaping approach, the frequency response of the overall system to load perturbations is shaped appropriately. We demonstrate the proposed approach for a three-node triangular configuration and a small-scale radial network. Furthermore, previous synchronization analysis for heterogeneous systems requires the machines to satisfy certain proportionality property. In our approach, the effective transfer functions for each cluster can be tuned by the IBRs to satisfy such property, enabling us to apply the shaping control to systems with a wider range of heterogeneous machines.

frequency-shaping control↗

Joint Expansion Planning of Power and Water Distribution Networks

This research considers the joint expansion planning of power and water distribution networks, which are interdependent at various levels. We consider the dependency arising through the power consumption of pumps and develop models for integrating new components into existing networks. Then, we formulate the joint expansion planning as a Mixed Integer Nonlinear Program (MINLP). Applying this MINLP to a small-scale test network, we illustrate the advantages offered by joint expansion planning, such as increased flexibility and reduced costs and redundancy, over independently expanding power and water distribution networks.

expansion planning↗