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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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At least 1,135 records · Page 63

Revised Stellar Properties of Kepler Targets for the Q1-17 (DR25) Transit Detection Run

The determination of exoplanet properties and occurrence rates using Kepler data critically depends on our knowledge of the fundamental properties (such as temperature, radius, and mass) of the observed stars. We present revised stellar properties for 197,096 Kepler targets observed between Quarters 1–17 (Q1-17), which were used for the final transiting planet search run by the Kepler Mission (Data Release 25, DR25). Similar to the Q1–16 catalog by Huber et al., the classifications are based on conditioning published atmospheric parameters on a grid of Dartmouth isochrones, with significant improvements in the adopted method and over 29,000 new sources for temperatures, surface gravities, or metallicities. In addition to fundamental stellar properties, the new catalog also includes distances and extinctions, and we provide posterior samples for each stellar parameter of each star. Typical uncertainties are ∼27% in radius, ∼17% in mass, and ∼51% in density, which is somewhat smaller than previous catalogs because of the larger number of improved logg constraints and the inclusion of isochrone weighting when deriving stellar posterior distributions. On average, the catalog includes a significantly larger number of evolved solar-type stars, with an increase of 43.5% in the number of subgiants. We discuss the overall changes of radii and masses of Kepler targets as a function of spectral type, with a particular focus on exoplanet host stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗

Enhancement of Distribution System Resilience Through the Application of Volt-Var Regulation Devices

This paper discusses a practical implementation of locating and sizing dynamic reactive compensation using an impedance matrix (Zbus) approach to improve distribution system resilience in scenarios with high penetration of distributed resources. The modeled system is a 14.2 kV radial residential system modified to be fed by a combination of traditional sources and solar resources. Time-varying loads and PV sources are connected along the feeder to simulate the challenging operational voltage regulation scenarios faced by Modern Distribution Systems. Additionally, enhancement of the resilience of the electrical system is demonstrated through analyzing the effect of a topology change to the system. This study uses the GridLAB-D software.

42 ENGINEERING↗

Redesigning capacity market to include flexibility via ramp constraints in high-renewable penetrated system

Capacity markets can co-exist alongside the energy and ancillary markets to ensure the medium-term and long-term supply adequacy by remunerating the generation resources for their availability. With the substantially increasing deployment of renewable generation, the system needs more flexibility to quickly mitigate the variability and uncertainty caused by the renewable generation. However, the present capacity market model does not differentiate the flexibility of generating units, so it might not give appropriate pricing signals to more flexible units that are usually more expensive. This is particularly important considering the increasing penetration levels of renewable generation on the electric grid, which increases the need for flexible units. This paper proposes a novel capacity market model considering flexibility requirement (FR) under the high penetration levels of renewable generation. Therefore, the proposed model can give the market-clearing price (MCP) for not only peak load generation capacity but also flexibility requirement. Thus, flexible units will tend to receive more economic incentives than non-flexible units. In the case studies, the profitability of different generation resources under the proposed capacity market model is analyzed and compared to the present capacity market model. The results show that the proposed method can maintain system reliability with regard to both peak load and flexibility requirement efficiently.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluating switch lifetime in soft-switched single-stage differential-mode SST

The reliability of semiconductor switches in single-stage differential-mode solid-state transformers (DM-SSTs) has not been systematically evaluated under soft-switching operation and realistic grid conditions. This paper presents a switch-level reliability analysis for soft-switched and hard-switched DM-SST configurations by integrating converter-specific power loss modeling with empirical lifetime prediction. Analytical derivation of device current profiles specific to the DM-SST is used to characterize electrothermal stress, which is then mapped to lifetime using degradation models obtained from power cycling tests (PCTs). Applied to realistic SST load profiles and grid voltage variations, this approach provides a probabilistic prediction of switch lifetime for the DM-SST. Lifetime estimates for both SiC MOSFETs and Si IGBTs are presented, offering insight into device degradation under converter operating conditions. The results quantify the reliability benefits of soft switching in single-stage SSTs, highlighting how switching dynamics influence long-term switch degradation.

14 SOLAR ENERGY↗

Consequences of neglecting the interannual variability of the solar resource: A case study of photovoltaic power among the Hawaiian Islands

The interannual variability of the solar irradiance and meteorological conditions are often ignored in favor of single-year data sets for modeling power generation and evaluating the economic value of photovoltaic (PV) power systems. Yet interannual variability significantly impacts the generation from one year to another of renewable power systems such as wind and PV. Consequently, the interannual variability of power generation corresponds to the interannual variability of capital returns on investment. The penetration of PV systems within the Hawaiian Electric Companies' portfolio has rapidly accelerated in recent years and is expected to continue to increase given the state's energy objectives laid out by the Hawaii Clean Energy Initiative. We use the National Solar Radiation Database (1998-2015) to characterize the interannual variability of the solar irradiance and meteorological conditions across the State of Hawaii. These data sets are passed to the National Renewable Energy Laboratory's System Advisory Model (SAM) to calculate an 18-year PV power generation data set to characterize the variability of PV power generation. We calculate the interannual coefficient of variability (COV) for annual average global horizontal irradiance (GHI) on the order of 2% and COV for annual capacity factor on the order of 3% across the Hawaiian archipelago. Regarding the interannual variability of seasonal trends, we calculate the COV for monthly average GHI values on the order of 5% and COV for monthly capacity factor on the order of 10%. We model residential-scale and utility-scale PV systems and calculate the economic returns of each system via the payback period and the net present value. We demonstrate that studies based on single-year data sets for economic evaluations reach conclusions that deviate from the true values realized by accounting for interannual variability.

14 SOLAR ENERGY↗

Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Big data has a potential to unlock novel groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry are discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.

13 HYDRO ENERGY↗

Analysis of Initial Performance of Solergy's HCPV/T System at Rome-Fiumicino International Airport

A commercial HCPV/T system, developed by Solergy, is installed at the airport of Rome, in Italy, as part of a prototype smart grid. The system is rated at 15 kW AC electric and 20 kW thermal and is used to provide both electricity for charging electric vehicles and heat for a conventional thermal power plant. This paper presents an analysis of the performance of the system, operating since March 2017, which achieves a combined peak efficiency of 48%. This study incorporates also an investigation on the improvements that can benefit the system, including a new type of receiver with improved heat dissipation.

14 SOLAR ENERGY↗

Suppression of phase separation in AlGaInAs compositionally graded buffers for 1550 nm photovoltaic converters on GaAs

We investigate strategies to suppress phase separation and reduce threading dislocation density (TDD) in AlGaInAs compositionally graded buffers (CGBs) that span the lattice constant range from GaAs to InP. Combining the results from high resolution x-ray diffraction, cathodoluminescence, transmission electron microscopy, and photovoltaic device measurements, we correlate the choices of epitaxial growth conditions with the defect structure of the CGBs and subsequent device performance. Both the use of substrates with high misorientation off (100) toward the (111)A plane and Zn doping instead of Si doping are shown to suppress phase separation and reduce TDD. We demonstrate a 0.74 eV GaInAs device grown on a GaAs substrate offcut 19.5° toward (111)A using a Zn-doped AlGaInAs CGB with TDD = 3.5 ± 0.2 × 10 6 cm -2 that has a bandgap-open circuit voltage offset of only 0.434 V measured under the AM1.5G solar spectrum. We characterized this device under high-intensity irradiance from a 1570 nm laser and measured a 31.9% peak laser power conversion efficiency at 3.6 W/cm 2 irradiance. These results provide a roadmap to the manufacture of laser- and thermal-power conversion devices with the performance and cost-effectiveness needed to drive adoption of these technologies at scale.

14 SOLAR ENERGY↗

Energy Storage for Frequency Control in High Photovoltaic Power Grids

Frequency stability of power systems becomes more vulnerable with the increase of solar photovoltaic (PV). Energy storage provides an option to mitigate high PV impact. Using the United States Eastern Interconnection (EI) and Texas Interconnection (ERCOT) power grid models, this paper investigates the capabilities of using energy storage to improve frequency stability of high PV power grids. The study result helps to identify the potential and impact factors in utilizing energy storage to regulate frequency in high renewable power grids.

14 SOLAR ENERGY↗

Switching-cycle-based Startup for Grid-connected Inverters

Conventional inverter startups, or grid synchronization, are hindered by slow dynamics and inrush current issues, which impede the integration of more renewable energy resources into the power grid. This paper overcomes the barriers by introducing a novel switching cycle-based startup approach for grid-connected inverters, eliminating the need for voltage sensors and phase-locked loops (PLLs). The proposed method surpasses the bandwidth constraints of traditional PLL-based techniques and achieves grid synchronization in just two switching cycles. Relying solely on sensed three-phase currents, synchronization is accomplished without inrush currents or the need for additional hardware or increased software complexity, resulting in a faster inverter startup. The paper also presents a sensitivity analysis to discuss the impact of critical parameters on the method's accuracy. As a result, the effectiveness of the proposed technique is demonstrated through simulation and experimental results.

14 SOLAR ENERGY↗

Quantifying Dynamic On-State Resistance of GaN HEMTs for Power Converter Design via a Survey of Low and High Voltage Devices

Designing and optimizing high switching frequency, ultra-efficient converters requires detailed knowledge of the behavior and parasitic parameters for both active and passive components. Recently, wide bandgap transistors have enabled simultaneous increases in both switching frequency and efficiency due to higher maximum operating junction temperature limits, lower dc on-state resistances, and reduced parasitic inductances and capacitances. Yet, the early acceptance of gallium-nitride (GaN) switches was plagued by detrimental dynamic on-state resistance effects. This complex phenomenon for GaN devices is characterized by deviations in on-state resistance from dc operating characteristics based on design choices such as the magnitude and duration of both voltage and current stress, switching mode, and junction temperature. While device manufacturers have made improvements compared to early generation devices, experimental evidence from a survey of commercial GaN transistors highlight measurable change in on-state resistance still exists due to variations in voltage stress during hard-switching operation. After sharing insights for obtaining low noise measurements, an analysis method along with two metrics are proposed to characterize dynamic on-state resistance measurements for power electronics designers. Furthermore, quantifying the performance of GaN devices with standardized metrics facilitates a fair comparison between different GaN device technologies during converter development, enables manufacturing qualification for GaN switches, and provides a benchmark to catalyze improvement for the next generation of GaN device development.

14 SOLAR ENERGY↗

Impact of Floating PV (FPV) System on Water Evaporation: Case Study of an Open Loop Reservoir in North Carolina

Fresh water scarcity is becoming one of the important concerns worldwide. This situation of water scarcity is further exacerbated by the increase in water evaporation due to climate change. This manuscript will address this concern by considering the impact of floating photovoltaics (FPVs) systems on water evaporation. The installation of PV modules on the water bodies can help reduce the water evaporation rate from reservoirs by reducing the evaporating area of the water surface. This work evaluates the effect of FPV on water evaporation rates in the TuckerTown reservoir located in North Carolina state of United States. Meteorological data, such as mean temperature and dew-point, are used to calculate the rate of the water evaporation by Linacre method. The simulation results for the TuckerTown case study showed that the aggregated avoided evaporated volume for one year is 9 million gallons.

14 SOLAR ENERGY↗