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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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Nondissipative dc to dc regulator converter - magnetic study, pulse width and frequency modulation, square wave sources, power losses in saturated transformers, and output filter
Ship-tracks are produced by ship-emitted aerosols interacting with low clouds. Here, we apply deep learning models on satellite data to produce the first global climatology map of ship-tracks. We show that ship-tracks are at the nexus of cloud physics, maritime shipping, and fuel regulation. Our map captures major shipping lanes while missing others because of background conditions. Ship-track frequency is more than 10 times higher than a previous survey, and its interannual fluctuations reflect variations in cross-ocean trade, shipping activity, and fuel regulations. Fuel regulation can alter both detected frequency and shipping routes due to cost. The 2020 fuel regulation, together with the coronavirus disease 2019 pandemic, reduced ship-track frequency to its lowest level in recent decades across the globe and may have ushered in an era of low frequency. The regulation reduces the aerosol indirect forcing from ship emissions by 46% or between 0.02 and 0.27 W m −2 given its current estimates.
Increasing renewable penetration in the bulk power systems has resulted in declining inertial response of the generation during system disturbances. This results in larger frequency deviations and oscillations during such events. This paper proposes a strategy for controlled dispatch of electrolyzers as loads to improve the system’s frequency response. A droop based controller with constraints based on electrolyzer operating limits has been developed to regulate its load. Consecutively, a localized frequency based control strategy has been developed to support the bulk system during disturbances. The impact of the electrolyzer support has been demonstrated using the 23-bus SAVNW system, and the 240-bus WECC system for baseline, 25% and 50% renewable penetration. The impact of changing droop settings and the available controllable electrolyzer capacities on the system’s frequency response has also been presented. Overall, the dispatchable electrolyzers helps improve (reduce) both the maximum frequency deviation and the settling times during common disturbances like loss of load/generation, and line faults. Systems with lower inertia were seen to benefit more from the controlled electrolyzer dispatch.
In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.
This paper elucidates the novel concept of using distributed dynamic voltage restorers (DVRs), which are traditionally used to compensate for voltage sags, to improve the frequency stability of low-inertia networked microgrids. During frequency transients, the distributed DVRs rapidly regulate load voltages within an acceptable range, resulting in a fast change of load power consumption and helping improve frequency stability. To enable large-scale network simulation, a phasor-based model of DVRs is developed and validated against real data from a commercially available device. Finally, simulation results of a modified IEEE 123-node test feeder that comprises three microgrids and six DVRs verify the effectiveness of the proposed method.
Solid-state transformer (SST) and hybrid transformer (HT) are promising alternatives to the line-frequency transformer (LFT) in smart grids. The SST features medium-frequency isolation, full controllability for voltage regulation, reactive power compensation, and the capability of battery energy storage system (BESS) integration with multiport configuration. The HT has a partially-rated converter for fractional controllability and can integrate a small BESS. Fast grid-edge voltage fluctuations from increased solar photovoltaic (PV) and electric vehicle (EV) penetration are difficult to manage for mechanical load tap changers. Hence, along with the trend towards more BESS in the grid, the controllability and the storage integration capability of the SST and HT are of strong interest. However, a review of literature shows existing SST and HT research is mostly at converter level, while system-level assessments are scarce. Assessing technical and economic impacts is critical to understanding the benefits and role of the SST and HT to guide future research, which is presented for the first time in this article. Experimental results from medium-voltage (MV) SST and MV HT prototypes are shown to confirm equipment-level feasibility, where the voltage controllability waveforms of a MV HT prototype are reported for the first time. Comparative simulations are performed on a modified IEEE 34-bus system. Here, a grid-model-less decentralized grid-edge voltage control method and a day-ahead BESS dispatch method are proposed for the SST and HT. The simulations show that the SST and HT with integrated storage can host more PV, achieve peak shaving, mitigate voltage fluctuation and reverse power flow, and support energy arbitrage for operational cost reduction, as compared to the LFT. Moreover, comprehensive analyses of net present value (NPV) and internal rate of return (IRR) are performed under different installed PV capacities, HT’s partial converter ratings, and BESS capacities. Sensitivities to future cost reductions of the PV and BESS are studied. Although the NPV and IRR are currently negative, 60% capital cost reduction or 150% revenue increase will make the SST and HT economically viable in the use case studied.
To fulfill the auxiliary grid services such as load regulation, spin and non-spin reserve, and frequency support during emergencies, power system operators often require certain wind farms to operate in de-loaded modes. By leveraging the fast response capability of wind farms, the reserved power in deloaded modes can significantly enhance the stability and reliability of power grids. This paper presents a novel methodology that incorporates wind turbines into reinforcement learning-based solutions for frequency response. The proposed approach employs the state-of-the-art reinforcement learning algorithm, surrogategradient- based evolution strategy (GSES), for continuous control of the wind farm output. Our methodology is tested on a modified IEEE-39 bus system, and simulation outcomes demonstrate that the proposed approach can reliably support the frequency of the power system and prevent unnecessary load shedding.
The Routh approximation technique for reducing the complexity of system models was applied in the frequency domain to a 16th order, state variable model of the F100 engine and to a 43d order, transfer function model of a launch vehicle boost pump pressure regulator. The results motivate extending the frequency domain formulation of the Routh method to the time domain in order to handle the state variable formulation directly. The time domain formulation was derived and a characterization that specifies all possible Routh similarity transformations was given. The characterization was computed by solving two eigenvalue-eigenvector problems. The application of the time domain Routh technique to the state variable engine model is described, and some results are given. Additional computational problems are discussed, including an optimization procedure that can improve the approximation accuracy by taking advantage of the transformation characterization.
Investigation of circadian rhythms in a number of variables related to sleep, EEG, temperature, and motor activity in rhesus monkeys on an LD 12:12 schedule. Circadian rhythms were found to appear in each of 15 variables investigated. Statistical procedures assessed the variables for evidence of common regulation in these aspects of their circadian rhythms: acrophase (timing), amplitude (extent of change), and level (24-hr mean value). Patterns appearing in the data suggested that the circadian rhythms of certain variables are regulated in common. The circadian modulation of activity in the beta and sigma frequency bands of the EEG was correlated with statistical significance in acrophase, level, and amplitude. The delta frequency band appeared to be under circadian rhythm regulation distinct from that of the other bands. The circadian rhythm of REM stage sleep was like that of beta activity in level and amplitude. The data indicate that REM stage may share some common regulation of circadian timing with both stage 3-4 sleep and with temperature. Generally, however, the circadian rhythm of temperature appeared to bear little relation to the circadian rhythms of motor activity, EEG, or sleep.
Here we present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E’s Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E’s GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.
The electricity sector is vulnerable to numerous hazards that are being exacerbated by climate change, which can cause an increase in the hazards' frequency and intensity. Consumers, system regulators, system operators, and communities are now preparing to mitigate the increased risks posed by climate change. New York State's energy infrastructure resilience can be increased with targeted investments including but not limited to installing emergency backup systems, integrating microgrid solutions, weatherizing buildings, increasing energy efficiency, adding redundancy, investing in restoration and recovery, and hardening critical components. Such investments can reduce the likelihood, impact, and consequences of disruptive events but can also increase capital and operating costs. A barrier to prioritizing investments in resilience is that there is no widely established method for quantifying and assigning the benefits of resilience investments across various stakeholders. Decision-makers need better information detailing the value of resilience improvements. Developing methods to quantify, value, and price resilience helps meet resilience needs in an effective manner that also supports broader societal welfare. This report lays out considerations for quantifying and valuing resilience, discusses the current state of resilience valuation tools, and provides case studies of resilience projects that demonstrate how resilience attributes could be measured while highlighting broader, project-specific challenges to increasing resilience. Further, we present insights into methods and challenges to measuring, valuing, and enacting resilience investments.
Automatic-gain-control (AGC) circuit regulates gain of intermediate-frequency and radio-frequency signals over wide dynamic range with high linearity and very low phase shift. Device has potential uses in radio and television receivers, signal distribution systems, and test and measurement instruments.
Susceptibility modeling, prediction of radio frequency interference from satellites, operational radio frequency interference control, and international regulations are considered. The existing satellite interference prediction program DSIP2 is emphasized. A summary status evaluation and recommendations for future work are given.
Power-supply circuit regulates output voltage by adjusting frequency of chopper circuit according to variations. Currently installed in battery charger for electric wheelchair, circuit is well suited to other uses in which light weight is important - for example, in portable computers, radios, and test instruments.
Differential adding circuit (or, equivalently, subtracting circuit) faster and consumes less power because it contains only one differential amplifier. Suitable for use in high-frequency-switching, high power-regulating circuit.
Portable transistorized circuit pulse frequency modulation /PFM/ simulator with power supply regulator
The electron-ion collider crab Cavities will present a significant transverse impedance to the beam. The low-level radio frequency system will have to reduce the crab cavity impedance to prevent transverse instabilities, while regulating the crabbing voltage and minimizing the radio frequency noise levels injected into the beam. This work presents an estimate of the crab cavity impedance in the presence of feedback and the resulting stability margins using simplified stability criteria. Generalized stability criteria are also presented in this work and are used to more accurately estimate stability margins.
The Electron-Ion Collider Crab Cavity Low-Level Radio Frequency system will have to reduce the Crab Cavity impedance to prevent transverse instabilities, while regulating the crabbing voltage and minimizing the Radio Frequency noise levels injected to the beam. These are challenging and partly conflicting requirements. This works summarizes the specifications to achieve these requirements and investigates the possible trade-offs in the architecture.