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At least 1,117 records · Page 62

Triadic Closure in Configuration Models with Unbounded Degree Fluctuations

The configuration model generates random graphs with any given degree distribution, and thus serves as a null model for scale-free networks with power-law degrees and unbounded degree fluctuations. For this setting, we study the local clustering c(k), i.e., the probability that two neighbors of a degree-k node are neighbors themselves. We show that c(k) progressively falls off with k and the graph size n and eventually for k=Ω(√n) settles on a power law c(k)∼n{sup 5−2τ}k{sup −2(3−τ)} with τ∈(2,3) the power-law exponent of the degree distribution. This fall-off has been observed in the majority of real-world networks and signals the presence of modular or hierarchical structure. Our results agree with recent results for the hidden-variable model and also give the expected number of triangles in the configuration model when counting triangles only once despite the presence of multi-edges. We show that only triangles consisting of triplets with uniquely specified degrees contribute to the triangle counting.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impact of truck electrification on air pollution disparities in the United States

Electrifying heavy-duty trucks reduces on-road diesel emissions but shifts the burden of supplying energy to power-generation facilities. The combined effect of Inflation Reduction Act investments in grid decarbonization and truck electrification will alter the magnitude and distribution of air pollution burdens across the United States. These investments are intended to facilitate a just energy transition, with 40% of the benefits flowing to disadvantaged communities per the Justice40 Initiative. Here we evaluate the combined effects of Inflation Reduction Act grid decarbonization and truck electrification investments on a national scale to determine whether the air pollution benefits would meet this 40% goal for both disadvantaged communities and the most exposed racial–ethnic groups. We find that truck electrification and decarbonization reduce air-pollution-related premature mortality in disadvantaged communities. However, the relative disparity between disadvantaged and non-disadvantaged communities increases, suggesting that a disproportionate share of benefits accrue to non-disadvantaged communities. Whereas absolute disparity in grid emissions decreases over time for all racial–ethnic groups, relative disparity remains largely unchanged, with Black populations being the most exposed. Electrifying drayage corridors would result in comparatively large health benefits for disadvantaged communities, suggesting that increasing targeted electrification investments in short-haul routes near urban areas (for example, ports) could be promising.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown (LS2) in 2018, and a new LAr Trigger Digitizer Board (LTDB) will be designed and installed. Several commercial-off-the-shelf (COTS) multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. Here, to evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition (DAQ) board, signal generator, external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clock distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC (FPGA Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital (MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of Metal Oxide Nanostructure-based Optical Sensors for Fossil Fuel Derived Gases Measurement at High Temperature

This final technical report details research works performed supported by a Department of Energy grant (DE-FE0003859), which was awarded under the University Coal Research Program administrated by National Energy Technology Laboratory. This research program studied high temperature fiber sensor for harsh environment applications. It developed two fiber optical sensor platform technology including regenerative fiber Bragg grating sensors and distributed fiber optical sensing based on Rayleigh backscattering optical frequency domain reflectometry. Through the studies of chemical and thermal regenerative techniques for fiber Bragg grating (FBG) fabrication, high-temperature stable FBG sensors were successfully developed and fabricated in air-hole microstructured fibers, high-attenuation fibers, rare-earth doped fibers, and standard telecommunication fibers. By optimizing the laser processing and thermal annealing procedures, fiber grating sensors with stable performance up to 1100°C have been developed. Using these temperature-stable FBG gratings as sensor platform, fiber optical flow, temperature, pressure, and chemical sensors have been developed to operate at high temperatures up to 800°C. Through the integration of on-fiber functional coating, the use of application-specific air-hole microstructural fiber, and application of active fiber sensing scheme, distributed fiber sensor for temperature, pressure, flow, liquid level, and chemical sensing have been demonstrated with high spatial resolution (1-cm or better) with wide temperature ranges. These include the demonstration of 1) liquid level sensing from 77K to the room temperature, pressure/temperature sensing from the room temperature to 800C and from the 15psi to 2000 psi, and hydrogen concentration measurement from 0.2% to 10% with temperature ranges from the room temperature to 700°C. Optical sensors developed by this program has broken several technical records including flow sensors with the highest operation temperature up to 750°C, first distributed chemical measurements at the record high temperature up to 700°C, first distributed pressure measurement at the record high temperature up to 800°C, and the fiber laser sensors with the record high operation temperature up to 700°C. The research performed by this program dramatically expand the functionality, adaptability, and applicability of distributed fiber optical sensors with potential applications in a number of high-temperature energy systems such as fossil-fuel power generation, high-temperature fuel cell applications, and potential for nuclear energy systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

SMUD Community Renewable Energy Deployment Final Report

This report summarizes the completion of four renewable energy installations supported by California Energy Commission (CEC) grant number CEC Grant PIR-11-005, the US Department of Energy (DOE) Assistance Agreement, DE-EE0003070, and the Sacramento Municipal Utility District (SMUD) Community Renewable Energy Deployment (CRED) program. The funding from the DOE, combined with funding from the CEC, supported the construction of a solar power system, biogas generation from waste systems, and anaerobic digestion systems at dairy facilities, all for electricity generation and delivery to SMUD’s distribution system. The deployment of CRED projects shows that solar projects and anaerobic digesters can be successfully implemented under favorable economic conditions and business models and through collaborative partnerships. This work helps other communities learn how to assess, overcome barriers, utilize, and benefit from renewable resources for electricity generation in their region. In addition to reducing GHG emissions, the projects also demonstrate that solar projects and anaerobic digesters can be readily implemented through collaborative partnerships. This work helps other communities learn how to assess, overcome barriers, utilize, and benefit from renewable resources for electricity generation in their region.

09 BIOMASS FUELS↗

FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets

This paper presents a novel, automated, generative adversarial networks (GAN) based synthetic feeder generation mechanism, abbreviated as FeederGAN. FeederGAN digests real feeder models represented by directed graphs via a deep learning framework powered by GAN and graph convolutional networks (GCN). Information of a distribution feeder circuit is extracted from its model input files so that the device connectivity is mapped onto the adjacency matrix and the device characteristics, such as circuit types (i.e., 3-phase, 2-phase, and 1-phase) and component attributes (e.g., length and current ratings), are mapped onto the attribute matrix. Then, Wasserstein distance is used to optimize the GAN and GCN is used to discriminate the generated graphs from the actual ones. A greedy method based on graph theory is developed to reconstruct the feeder using the generated adjacency and attribute matrices. Furthermore, our results show that the GAN generated feeders resemble the actual feeder in both topology and attributes verified by visual inspection and by empirical statistics obtained from actual distribution feeders.

42 ENGINEERING↗

Market and Modeling Uncertainty in Distributed Solar Deployment Projections: A Multi-Model Comparison

Distributed solar photovoltaic (DPV) systems that generate energy in behind-the-meter (BTM) applications for residential, commercial, and other end-user sectors are a growing and contentious development in the U.S. power system. While less than one percent of all electricity generation in the United States came from DPV systems in 2016 (EIA, April 2017), this technology has experienced rapid growth in recent years and, as of the start of 2017, over 1.3 million DPV systems had been installed (Munsell 2017). Thus, projecting the feasibility and potential timing of mass-market breakout of distributed solar is increasingly pertinent - yet projections remain highly uncertain.

14 SOLAR ENERGY↗

A Geospatial Cost Comparison of CO2 Plume Geothermal (CPG) Power and Geologic CO2 Storage

CO 2 Plume Geothermal (CPG) power plants can use gigatonne-levels of CO 2 sequestration to generate electricity, but it is unknown if the resources that support low-cost CPG power align with the resources that support low-cost CO 2 sequestration. Here, we estimate and compare the geospatially-distributed cost of CPG and CO 2 storage across a portion of North America. We find that the locations with lowest-cost CO 2 storage are different than the locations with lowest-cost CPG. There are also locations with low-cost CO 2 storage (<$5/tCO 2 ) that do not support CPG power generation due to insufficient reservoir transmissivity or temperature. Thus, CPG development may require electricity prices that are greater than the levelized cost of electricity (LCOE) to offset the increased cost of sequestration. We introduce the “Additional Cost of Electricity (ACOE)” metric to account for this cost and add it to the LCOE to calculate breakeven electricity prices that are required for CPG development. We find that breakeven prices are lower when new CO 2 injection wells are drilled specifically for CPG (i.e., “greenfield” CPG development) compared to if only existing CO 2 sequestration injection wells are used (i.e., “brownfield” CPG development). This is because comparatively few wells are needed for sequestration-only, and the increased power capacity from having more CPG wells outweighs the increased costs from more drilling. We also find that sequestered CO 2 could be used to approximately triple the United States geothermal electricity power capacity via a single CPG “sweet spot” in South Dakota, but that breakeven electricity price for this development is on the order of $200/MW e h.

15 GEOTHERMAL ENERGY↗

A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources

Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). Here, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the introduced strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Big Data Analysis of Massive PMU Datasets: A Data Platform Perspective

The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.

Kumar, Vijay S.↗

Aero-MINE (Motionless INtegrated Energy) for Distributed Scalable Wind Power.

The proposed Aero-MINE technology will extract energy from wind without any exterior moving parts. Aero-MINEs can be integrated into buildings or function stand-alone, and are scalable. This gives them advantages similar to solar panels, but with the added benefit of operation in cloudy or dark conditions. Furthermore, compared to solar panels, Aero-MINEs can be manufactured at lower cost and with less environmental impact. Power generation is isolated internally by the pneumatic transmission of air and the outlet air-jet nozzles amplify the effectiveness. Multiple units can be connected to one centrally located electric generator. Aero-MINEs are ideal for the built-environment, with numerous possible configurations ranging from architectural integration to modular bolt-on products. Traditional wind turbines suffer from many fundamental challenges. The fast-moving blades produce significant aero-acoustic noise, visual disturbances, light-induced flickering and impose wildlife mortality risks. The conversion of massive mechanical torque to electricity is a challenge for gears, generators and power conversion electronics. In addition, the installation, operation and maintenance of wind turbines is required at significant height. Furthermore, wind farms are often in remote locations far from dense regions of electricity customers. These technical and logistical challenges add significantly to the cost of the electricity produced by utility-scale wind farms. In contrast, distributed wind energy eliminates many of the logistical challenges. However, solutions such as micro-turbines produce relatively small amounts of energy due to the reduction in swept area and still suffer from the motion-related disadvantages of utility-scale turbines. Aero-MINEs combine the best features of distributed generation, while eliminating the disadvantages.

17 WIND ENERGY↗

Integrated Transmission and Distribution Systems Restoration with Distributed Generation Scheduling

The self-healing smart grids enable system operators to quickly and efficiently recover transmission and distribution systems from outages and blackouts. The current restoration procedure solves the transmission and distribution system restoration problems separately without considering their impacts on each other, which may prolong the restoration process. However, with the emerging active distribution networks, distributed generators can contribute into the bottom-up restoration strategy. The interaction between the restoration of two interconnected systems should be taken into account. In this paper, a hybrid model of transmission and distribution systems restoration (HTDSR) is proposed by exchanging data of power and voltage between two separate optimization problems. The effectiveness of the HTDSR algorithm is demonstrated through case studies of the integrated IEEE 13-bus distribution network and IEEE 39-bus transmission grid. Simulation results demonstrate that the integrated restoration strategy with optimal scheduling of distributed generation sources can expedite the restoration process.

Distributed generation↗

Western Wind and Solar Integration Study Phase 3A: Low Levels of Synchronous Generation

The stability of the North American electric power grids under conditions of high penetrations of wind and solar is a significant concern and possible impediment to reaching renewable energy goals. The 33% wind and solar annual energy penetration considered in this study results in substantial changes to the characteristics of the bulk power system. This includes different power flow patterns, different commitment and dispatch of existing synchronous generation, and different dynamic behavior from wind and solar generation. The Western Wind and Solar Integration Study (WWSIS), sponsored by the U.S. Department of Energy, is one of the largest regional solar and wind integration studies to date. In multiple phases, it has explored different aspects of the question: Can we integrate large amounts of wind and solar energy into the electric power system of the West? The work reported here focused on the impact of low levels of synchronous generation on the transient stability performance in one part of the region in which wind generation has displaced synchronous thermal generation under highly stressed, weak system conditions. It is essentially an extension of WWSIS-3. Transient stability, the ability of the power system to maintain synchronism among all elements following disturbances, is a major constraint on operations in many grids, including the western U.S. and Texas systems. These constraints primarily concern the performance of the large-scale bulk power system. But grid-wide stability concerns with high penetrations of wind and solar are still not thoroughly understood. This work focuses on 'traditional' fundamental frequency stability issues, such as maintaining synchronism, frequency, and voltage. The objectives of this study are to better understand the implications of low levels of synchronous generation and a weak grid on overall system performance by: 1) Investigating the Western Interconnection under conditions of both high renewable generation (e.g., wind and solar) and low synchronous generation (e.g., significant coal power plant decommitment or retirement); and 2) Analyzing both the large-scale stability of the Western Interconnection and regional stability issues driven by more geographically dispersed renewable generation interacting with a transmission grid that evolved with large, central station plants at key nodes. As noted above, the work reported here is an extension of the research performed in WWSIS-3.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Harmonic Modeling, Data Generation and Analysis of Power Electronics-Interfaced Residential Loads

The share of electronics-based residential load is expected to rise as devices such as variable frequency drives (VFDs), electric vehicle chargers, and inverter-based distributed energy resources (DERs), e.g., photovoltaic (PV) systems become more common. These loads may introduce significant harmonics into power networks that need to be closely studied in order to perform accurate load modeling and forecasting. However, it can be difficult to obtain harmonic-rich voltage and current data - necessary for identifying accurate load models - for residential electrical loads. Recognizing this need, we identify and model a set of electronics-based end-use loads and DERs in an electromagnetic transients program (EMTP) tool for a residence with a single- phase split-phase supply. Further, a procedure is developed to model harmonic interactions between end-use loads connected to the same non-ideal supply voltage in a residential setting. Finally, a harmonic-rich dataset produced via the proposed procedure is utilized to identify frequency coupling matrix (FCM) based load model. Numerical results demonstrate the accuracy of the model, and explore model identifiability with limited data points.

harmonics, power quality, load modeling↗

Scoping Study for Direct Power Extraction (DPE) Systems (Final Report)

NETL led a detailed scoping study of various direct power extraction systems and concepts for utility power generation. The study consisted of qualitative analysis along with quantitative techno-economic analysis of selected systems which use magnetohydrodynamic (MHD) power generators.

24 POWER TRANSMISSION AND DISTRIBUTION↗

GLASS: General Line Ampacity State Solver

The U.S. installed more than 8,000 megawatts of wind generation in 2016. Wind energy is now powering more than 20 million homes. Idaho National Laboratory technology uses real time weather information and computer models to help utilities integrate more wind energy, relieving transmission line congestion, and extending the life time of existing grid infrastructure.

17 WIND ENERGY↗