Subcritical convective instability. II.
Subcritical convective instability, discussing effects of internal heat generation and spatial variation of gravity field on onset of thermal convection
SPATIAL DISTRIBUTION↗
SEARCH · Engineering Papers
Results for “Distributed Generation”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Coordinated operation of pumped-storage hydropower with power and water distribution systems
Small pumped-storage hydropower (PSH) units have gained popularity as distributed energy storage options that can provide flexibility to the operation of power distribution systems. Optimal operation of small PSH units is not only dependent on the energy storage provided to power distribution system, but also on the inflow and outflow of water from and to the water distribution system. Here, in this context, this paper develops an optimization model for coordinated operation of PSH units with power and water distribution systems. The proposed model optimizes the operation of water tanks, variable-speed pumps and PSH in pumping and generating modes to minimize the operation cost of power distribution system, while respecting the power flow constraints of power distribution and hydraulic constraints of water distribution system. Appropriate electricity tariffs are implemented to avoid additional expenses in water distribution system that can be enforced by its coordinated operation in favor of power distribution system. The proposed model is implemented on a 33-bus and a 123-bus test power distribution system connected to a 16-node test water distribution system. Results demonstrate the effectiveness of proposed model in tapping PSH flexibility to reduce the operation cost of power and water distribution systems, while meeting the power and water demands.
13 HYDRO ENERGY↗
A vortex wake capturing method for potential flow calculations
A method is presented for modifying finite difference solutions of the potential equation to include the calculation of non-planar vortex wake features. The approach is an adaptation of Baker's 'cloud in cell' algorithm developed for the stream function-vorticity equations. The vortex wake is tracked in a Lagrangian frame of reference as a group of discrete vortex filaments. These are distributed to the Eulerian mesh system on which the velocity is calculated by a finite difference solution of the potential equation. An artificial viscosity introduced by the finite difference equations removes the singular nature of the vortex filaments. Computed examples are given for the two-dimensional time dependent roll-up of vortex wakes generated by wings with different spanwise loading distributions.
Murman, E. M.↗
An Intelligent Distributed Ledger Construction Algorithm for IoT
Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.
multi-arm bandit↗
Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs
The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Bell-Curve Based Evolutionary Optimization Algorithm
The paper presents an optimization algorithm that falls in the category of genetic, or evolutionary algorithms. While the bit exchange is the basis of most of the Genetic Algorithms (GA) in research and applications in America, some alternatives, also in the category of evolutionary algorithms, but use a direct, geometrical approach have gained popularity in Europe and Asia. The Bell-Curve Based Evolutionary Algorithm (BCB) is in this alternative category and is distinguished by the use of a combination of n-dimensional geometry and the normal distribution, the bell-curve, in the generation of the offspring. The tool for creating a child is a geometrical construct comprising a line connecting two parents and a weighted point on that line. The point that defines the child deviates from the weighted point in two directions: parallel and orthogonal to the connecting line, the deviation in each direction obeying a probabilistic distribution. Tests showed satisfactory performance of BCB. The principal advantage of BCB is its controllability via the normal distribution parameters and the geometrical construct variables.
Sobieszczanski-Sobieski, J.↗
Induced Markov chain for wind farm generation forecasting
Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.
17 WIND ENERGY↗
Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects
We briefly review previous applications of machine learning (ML) in power grid analyses and introduce our ongoing effort toward developing a generative-adversarial (GA) model for fast and reliable grid contingency analyses. According to our review, the persisting limitation of traditional ML techniques in grid analyses is the need for an exhaustive amount of training data for model generalization and accurate predictions. GA models overcome this limitation by first learning true data distribution from a small training set, from which new samples assimilating true data are generated with some variations. Subsequently, GA models can transfer learn or super-generalize with increased accuracy, that is, accurately predict n - (k + 2) contingencies from a small n - k training set and generated n - (k + 1) data. The joint effort between Idaho National Lab and Florida State University strives to develop a zero-shot and deep learning-based contingency analysis tool, named Smart Contingency Analysis Neural Network (SCANN), by leveraging the aforementioned advantages of GA models. The basic architecture of SCANN stems from the Latent Encoding of Atypical Perturbations network combined with an adversarial network, and it is designed to generate imbalanced power flow data from learned true data distributions for prediction purposes. Here we also introduce the abstract concept of resilience-chaos plots, a new resilience characterization tool proposed to complement SCANN by aiding in the assessment of large amounts of high-order contingency predictions.
24 POWER TRANSMISSION AND DISTRIBUTION↗
An Investigation of the Effects of a Vortex-Generator Configuration on the Aerodynamic Characteristics of a 1/4-Scale Model of the X-1 Airplane (10-Percent-Thick Wing)
An investigation of a vortex-generator configuration on the wings of a l/4-scale model of the X-1 airplane having a 10-percent-thick wing was conducted in the Langley 16-foot transonic tunnel. The effect of the vortex generators was determined by comparing the model aerodynamic characteristics, wing-pressure distributions, and wing-wake patterns for model configurations with and without vortex generators on the wings. Results are presented from tests at 0.1 increments in Mach number from about 0.69 to 0.99, at Reynolds numbers of about 4.1 x 10(exp 6) to 4.7 x 10(exp 6), and through an angle-of-attack range up to 1.5 deg at lower speeds and up to 5 deg at the highest speed. In general, little difference in the aerodynamic characteristics was observed, except at a Mach number of 0.90 where a rearward movement of the shock on the upper surface of the wing with the vortex generators installed resulted in less separation.
Runckel, Jack F.↗
Evaluation of GIS Technology in Assessing and Modeling Land Management Practices
There is an increasing concern of land owners to protect and maintain healthy and sustainable agroecosystems through the implementation of best management practices (BMP). The objectives of this study were: (1) To develop and evaluate the use of a Geographic Information System (GIS) technology for enhancing field-scale management practices; (2) evaluate the use of 2-dimensional displays of the landscape and (3) define spatial classes of variables from interpretation of geostatistical parameters. Soil samples were collected to a depth of 2 m at 15 cm increments. Existing data from topographic, land use, and soil survey maps of the Winfred Thomas Agricultural Research Station were converted to digital format. Additional soils data which included texture, pH, and organic matter were also generated. The digitized parameters were used to create a multilayered field-scale GIS. Two dimensional (2-D) displays of the parameters were generated using the ARC/INFO software. The spatial distribution of the parameters evaluated in both fields were similar which could be attributed to the similarity in vegetation and surface elevation. The ratio of the nugget to total semivariance, expressed as a percentage, was used to assess the degree of spatial variability. The results indicated that most of the parameters were moderate spatially dependent Biophysical constraint maps were generated from the database layers, and used in multiple combination to visualize results of the BMP. Understanding the spatial relationships of physical and chemical parameters that exists within a field should enable land managers to more effectively implement BMP to ensure a safe and sustainable environment.
Archer, F.↗
SIDIS-RC EvGen: A Monte-Carlo event generator of semi-inclusive deep inelastic scattering with the lowest-order QED radiative corrections
SIDIS-RC EvGen is a C++ standalone Monte-Carlo event generator for studies of semi-inclusive deep inelastic scattering (SIDIS) processes at medium to high lepton beam energies. In particular, the generator contains binary and library components for generating SIDIS events and calculating cross sections for unpolarized or longitudinally polarized beam and unpolarized, longitudinally or transversely polarized target. The structure of the generator incorporates transverse momentum-dependent parton distribution and fragmentation functions, whereby we obtain multi-dimensional binned simulation results, which will facilitate the extraction of important information about the three-dimensional nucleon structure from SIDIS measurements. In order to build this software, we have used recent elaborate QED calculations of the lowest-order radiative effects, applied to the leading order Born cross section in SIDIS. Here, in this paper, we provide details on the theoretical formalism as well as the construction and operation of SIDIS-RC EvGen, e.g., how we handle the event generation process and perform multi-dimensional integration. We also provide example programs, flowcharts, and numerical results on azimuthal transverse single-spin asymmetries.
97 MATHEMATICS AND COMPUTING↗
The intrinsic luminosity and initial period of pulsars
The observed properties of pulsars are modeled on the assumption that they evolve by emitting magnetic dipole radiation and have exponentially decaying magnetic fields. The models are constructed by using Monte Carlo techniques to generate a Galactic sample of pulsars having particular distributions of initial periods, magnetic dipole moments, and positions. By choosing a relationship between the radio luminosity L(r), the period (P), and the P derivative, it is determined which pulsars of the generated sample could be detected by one of the major pulsar surveys. Detailed account is taken of known selection effects in these surveys. Models in which the size of the pulsar emission cone is dependent on the period are considered. The properties of the detectable pulsars are compared with the properties of the observed pulsars, and the initial distributions and luminosity relation of the model are adjusted until a satisfactory agreement is obtained. A crucial point is that the observed relation between L(r) and P, P derivative is affected by selection effects and does not apply to the actual pulsar population. It is found that the best fits are obtained with models in which the pulsars are injected with relatively long periods, about 0.5 sec.
Emmering, Robert T.↗
Compressed Gas Energy Storage Integrated with Combined Heat and Power Plant
A new energy storage technology, Comrpessed Gas Energy Storage (CGES), seeks to achieve low-cost, long-duration eenrgy storage by combining mature commercially-available technology (compressors, high-pressure gas storage, expander generators) and utilizing existing infrastructure for transportation and distribution of industrial gases. CGES utilizes existing compressors to transform electricity into potential energy (pressure), existing pipelines or underground storage to store said potential energy, and adds new expander generators at pressure reduction points in the networkm to recover part of the energy used in compression and transform it into electricity. By adapting itself to widely available existing infrastructure, CGES recovers energy that is otherwise wasted in the gas value chain, reduces the cost of new facilities, and avoids many of the development huddles typically associated with other long-duration energy storage technologies (e.g., Compressed Air Energy Storage, CAES). This paper discusses the performance and economics associated with CGES as a standalone project and in combination with a thermal power plant, based on a concept for integration of the technology over an existing lateral pipeline transporting natural gas to an 85 MW combined heat and power plant that feeds power to a grid with increasing share of renewable power generation.
03 NATURAL GAS↗
Inclusive photon production at forward rapidities in pp and p–Pb collisions at $\sqrt{{{s}}_{\textrm{NN}}}={5.02}$ TeV
A study of multiplicity and pseudorapidity distributions of inclusive photons measured in pp and p–Pb collisions at a center-of-mass energy per nucleon–nucleon collision of $\sqrt{s_{NN}}$ = 5.02 TeV using the ALICE detector in the forward pseudorapidity region 2.3 < η lab < 3.9 is presented. Measurements in p–Pb collisions are reported for two beam configurations in which the directions of the proton and lead ion beam were reversed. The pseudorapidity distributions in p–Pb collisions are obtained for seven centrality classes which are defined based on different event activity estimators, i.e., the charged-particle multiplicity measured at midrapidity as well as the energy deposited in a calorimeter at beam rapidity. The inclusive photon multiplicity distributions for both pp and p–Pb collisions are described by double negative binomial distributions. The pseudorapidity distributions of inclusive photons are compared to those of charged particles at midrapidity in pp collisions and for different centrality classes in p–Pb collisions. The results are compared to predictions from various Monte Carlo event generators. None of the generators considered in this paper reproduces the inclusive photon multiplicity distributions in the reported multiplicity range. The pseudorapidity distributions are, however, better described by the same generators.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Smart sensor for online situational awareness in power grids
Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.
Dehghanian, Payman↗
Estimation of distributed acoustic lasers
The purpose of this paper is to present the results of a preliminary investigation of an indirect method which can be used to generate a set of equivalent point loads approximating an applied distributed acoustic load. The method combines the source information with the structure's modal characteristics and forces which give the same response as the applied acoustic load. The technique is demonstrated by predicting a set of point forces acting on a thin aluminum panel which simulate a normally-incident random pressure. The technique is verified by comparing measured strain autospectrums with estimated strain autospectrums generated using the predicting forces. Strain errors within 5 dB were achieved. A limited amount of information about the acoustic load could be deduced using the predicted force autospectrums and phase differences between these forces.
Elliott, K. B.↗
High-frequency waves generated by auroral electrons
Measurements of marginally unstable electron distribution functions and high-frequency plasma waves were made on a sounding rocket flight through a quiet auroral arc. The waves appeared near the electron plasma frequency and had a large parallel electric field component such that k-parallel is greater than k-perpendicular. The appearance of these waves was correlated with the presence of marginally unstable parallel electron distributions. Analysis has shown that the waves were produced by parallel electron distribution function greater than 0 rather than the small perpendicular electron distribution function greater than 0 features. Wave levels and growth rates inside the arc were small, and nonlinear wave-wave and wave-particle interactions appear to have been minimal.
Mcfadden, J. P.↗
Impact-generated atmospheres over Titan, Ganymede, and Callisto
The current distribution of atmospheres among Ganymede, Titan, and Callisto are presently accounted for by a process of competition between impact erosion and impact-furnished supply of atmosphile-laden late veneers. Titan's lower impact velocities have allowed it to accommodate an atmosphere, while Callisto and Ganymede remain barren. The model applied entails that the threshold impact velocity for atmospheric cratering by icy impactors be in the 10-14 km/sec range, consistent with the implications of the Schmidt and Housen (1987) crater-energy scaling for nonporous targets.
Zahnle, Kevin↗