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At least 91 records · Page 5

Communication enabled – fast acting imbalance reserve (CE-FAIR)

This letter presents a new frequency control strategy that takes advantage of communications and fast responding resources like PV generation, energy storage, wind generation, and demand response, termed collectively as converter interfaced generators (CIGs). The proposed approach uses an active monitoring of power imbalances to rapidly redispatch CIGs. This approach differs from previously proposed frequency control schemes in that it employs feed-forward control based on a measured power imbalance rather that relying on a frequency measurement. As a result, time-domain simulations of the full Western Electricity Coordinating Council (WECC) system are conducted to demonstrate the effectiveness of the proposed method, showing improved performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cooling assembly for electrical machines and methods of assembling the same

A cryocooler assembly for cooling a field winding of an electrical machine having an axis of rotation is provided. The assembly includes a cryocooler and a reservoir coupled in flow communication to the cryocooler and configured to contain a cooling agent. A flow assembly is coupled in flow communication to the reservoir. The flow assembly includes a first flow loop coupled in flow communication to the reservoir; a second flow loop coupled in flow communication to the reservoir; and a plurality of flow members coupled in flow communication to the first flow loop and the second flow loop and coupled to the field winding. Each flow member is configured to thermosiphon the cooling agent in a first state from the reservoir and in a second state to the reservoir.

42 ENGINEERING↗

Implementing Cybersecurity for Distributed Wind: An Exercise in ICS Security Application

Distributed wind is unique and fast-growing component of the energy production mix, but cybersecurity for distributed wind is not well developed. In this presentation, we will introduce distributed wind as an example of difficult-to-secure critical infrastructure. We will first provide background on distributed wind architectures, applications, and stakeholder roles. We will explain the need and challenges for cybersecurity for distributed wind, pointing to both academic studies and real-world events. The key component of the presentation will discuss recommendations for different aspects of security, such as risk assessments, communications, and access control, that specifically call out considerations that apply uniquely to distributed wind. We will discuss what sets distributed wind apart from other ICS and energy applications, and how to account for these features in a comprehensive security plan. This process is demonstrative of the type of analysis needed to adapt traditional security guidelines and standards to narrow and focused applications.

17 WIND ENERGY↗

Assessment of CReST-VCT Deployment in Real-Time Environments: Communication System Examination

Incorporation of decentralized generation or distributed energy resources (DERs) such as solar and wind, is transforming the electricity grid. These resources have the potential to provide greater overall value when they are grid connected and coordinated between transmission and distribution systems. The Coordinated Real-Time Sub-Transmission Volt-VAr Control Tool (CReST-VCT) has been proposed to provide co-optimization between transmission and distribution systems maximizing DER utilization while maintaining overall grid stability. In this paper, we examine the communication systems that are necessary to support the integration of the CReST-VCT optimization mechanism in a real-time operational environment. The required communication interfaces will be identified based on the operation model of CReST-VCT. The characteristics of the communication systems at these interfaces will be described to establish the context within which CReST-VCT will operate. The related protocols and cybersecurity domain will be reviewed. Potential issues and concerns will then be identified to guide subsequent integration efforts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Resilient Autonomous Wind Farms

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm level, taking into account individual wind turbine information to achieve wind-farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have experienced significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms that can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as from local meteorological stations, nearby radars, sodars, and lidars, and supervisory control and data acquisition (SCADA) data. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and ensuring more efficient overall control of farmwide optimizations through mechanisms such as wake steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach that distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks that seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft-Byzantine-Fault-Tolerant algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will...

fault tolerance↗

Resilient Autonomous Wind Farms: Preprint

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm-level, taking account of individual wind turbine information to achieve wind farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have seen significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms which can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and enabling more efficient overall control of farm-wide optimizations through mechanisms such as wake-steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach which distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks which seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft Byzantine Fault Tolerance algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will be shown to achieve overall consensus, provided the number of faults/malicious nodes is less than 3$n$+1, where $n$ is the number of turbine cluster faults which may occur, and to be robust in the face of multiple arbitrary faults.

autonomous↗

Various Analyses of Structures and Systems Pertaining to Optical Communications

The Optical Communications Group intends to experiment with a 2 by 2 meter Fresnel lens to determine its likelihood as an alternative to focusing mirrors for optical communications. The lens was delivered in four sections. A support structure was required for the lens in order to hold the four sections in a single flat plane with an adjustable degree angle. In order to use the 200-in. Hale telescope for optical communications purposes, an optical filter membrane must used to pass the communications wavelength while blocking sunlight wavelengths. This filter must withstand wind gusts of up to 50 miles per hour. Stress analysis predicts that the membrane will survive with a safety factor greater than two. The methods used were verified by pressure testing the material. Mechanical and thermodynamic analyses were performed on a simple Golay cell in order to optimize its dimensions for best performance. Flexures are examined as an inexpensive alternative to traditional methods for kinematically constraining a 1.5-meter spherical mirror.

Petersen, Collin W.↗

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗

Workshop Report: Wind Innovations for Rural Economic Development (WIRED)

The U.S. Department of Energy's Wind Energy Technologies Office (WETO) hosted the Wind Innovations for Rural Economic Development (WIRED) workshop in October 2018 with support from PNNL and NREL. The goals of the workshop were to develop an understanding of 1) what opportunities and challenges face rural electric utilities, considering distributed wind and other distributed energy resources, 2) what research and development pathways could enable wind technology to be more valuable for rural electric utilities, and 3) how DOE, in partnership with utilities and stakeholders, might ease the deployment of distributed wind systems. The report captures the key challenges, opportunities, and potential federal government R&D solutions as communicated by the stakeholder participants.

17 WIND ENERGY↗

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗

Evolution of the solar wind acceleration region during 1990-1994

The single-station measurements of interplanetary scintillation (IPS) at 2 and 8 GHz have been made at the Kashima Space Research Center of the Communications Research Laboratory in the period from 1990 to 1994. These IPS data are used to study the radial distribution of solar wind velocity and density fluctuations near the sun (i.e. 10-70 Rs), and the long-term variation in these properties. The IPS co-spectrum technique is applied here to estimate the solar wind velocity. Derived velocities show that the solar wind gains a speed significantly in the radial range from 10 to 30 Rs (solar radii). which is much farther than the source surface of the thermally driven solar wind model. From the scintillation index analysis. it is found that the radial fall of density fluctuations is well described by the power-law function. A series of IPS observations reveals that a pronounced change in velocity and turbulence level for this radial range occurs at the polar region of the sun during 1990-1994. That is, the high speed wind and the reduced turbulence region develop there as the solar activity declines. On the other hand, little long-term variation is observed for the solar wind acceleration region at a low latitude. From the comparison with He 1O83 nm observations. it is demonstrated that the change of the solar wind structure is closely linked with the evolution of the coronal hole on the solar surface.

Tokumaru, M.↗

An Investigation of the Large Scale Evolution and Topology of Coronal Mass Ejections in the Solar Wind

This investigation is concerned with the large-scale evolution and topology of coronal mass ejections (CMEs) in the solar wind. During this reporting period we have focused on several aspects of CME properties, their identification and their evolution in the solar wind. The work included both analysis of Ulysses and ACE observations as well as fluid and magnetohydrodynamic simulations. In addition, we analyzed a series of "density holes" observed in the solar wind, that bear many similarities with CMEs. Finally, this work was communicated to the scientific community at three meetings and has led to three scientific papers that are in various stages of review.

Riley, Peter↗

Global Variation of Meteor Trail Plasma Turbulence

We present the first global simulations on the occurrence of meteor trail plasma irregularities. These results seek to answer the following questions: when a meteoroid disintegrates in the atmosphere will the resulting trail become plasma turbulent, what are the factors influencing the development of turbulence, and how do they vary on a global scale. Understanding meteor trail plasma turbulence is important because turbulent meteor trails are visible as non-specular trails to coherent radars, and turbulence influences the evolution of specular radar meteor trails, particularly regarding the inference of mesospheric temperatures from trail diffusion rates, and their usage for meteor burst communication. We provide evidence of the significant effect that neutral atmospheric winds and density, and ionospheric plasma density have on the variability of meteor trail evolution and the observation of nonspecular meteor trails, and demonstrate that trails are far less likely to become and remain turbulent in daylight, explaining several observational trends using non-specular and specular meteor trails.

Dyrud, L. P.↗

Adaptive sensing for a gas leak detection

A method, a system and an apparatus for adaptively sensing a gas leak. The method includes: obtaining wind data from a wind sensor, identifying at least one wireless mote in a plurality of wireless motes that is most likely to detect a gas plume from the wind data, activating the identified at least one wireless mote to trigger measuring gas concentration of the gas plume, and identifying the location of the gas leak if the gas concentration is above a predetermined threshold. Also included is a system for adaptively sensing a gas leak having a wind sensor, a plurality of wireless motes and a server in communication therewith. An apparatus for adaptively sensing a gas leak in an industrial site is also provided.

03 NATURAL GAS↗

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, thereby communicating to consumers the costs of supplying electricity throughout the day. This study evaluates the impact of Decision D.15.07-001, which mandates a transition to default TOU rates in California, on the economic viability of behind-the-meter distributed wind and solar systems. We assess viability through 'economic potential,' a metric we define as the amount of generation capacity that exceeds a specified rate of return (5.4%) and therefore would be economic to construct; we do not attempt to project deployment or adoption. In addition, we identify cost improvements needed for a robust distributed wind market and the specific counties and sectors with substantial economic potential. Over the scenarios considered, model results indicate realistic pathways to reaching a robust, 1-GW distributed wind market in California though solar economic potential was found to be substantially larger than that of wind. Distributed wind's capacity factor does not appear to be strongly correlated to the periods of peak electricity prices as set by utility's TOU periods. Because of this disassociation and nuances in the billing of tiered electricity, the transition to TOU is projected to moderately decrease distributed wind economic potential and increase that of distributed solar. However, a limitation of this analysis is that it does not factor in the change in rate values as California works toward its goal of 100% renewables. As variable renewable energy penetration increases to meet this goal, our results suggest that wind generation will become increasingly correlated to periods of peak electricity prices. Increased variable renewable penetration, especially of solar, is likely to shift periods of higher electricity demand to later in the evening, and any periodic adjustments in TOU periods to reflect these new periods of demand will positively affect the value of wind generation more than the value of solar generation. High distributed wind capital costs are a significant barrier to large scale adoption; we explore the sensitivity of capital cost reductions on distributed wind economic potential. We find that distributed wind economic potential increases substantially in 2020 for capital costs below 3 dollars/W - particularly for residential- and commercial-scale turbines; capital costs must fall below 2 dollars/W in 2030 to support a significant increase in economic potential, in large part due to the expected continued cost reductions in solar. We identified an upper limit to the state's behind-the-meter distributed wind economic potential at approximately 5 GW. Overall, California exhibits over 1 GW of economic potential for distributed wind by 2030, even with the moderate decrease in potential under TOU. This potential is represented mostly by Southern California, which sees the most notable increase in economic viability as capital expenditure prices decline.

17 WIND ENERGY↗

Exploration of Solar Wind Acceleration Region Using Interplanetary Scintillation of Water Vapor Maser Source and Quasars

Single-station observations of interplanetary scintillation UPS) at three microwave frequencies 2, 8, and 22GHz, were carried out between 1989 and 1998 using a large (34-micro farad) radio telescope at the Kashima Space Research Center of the Communications Research Laboratory. The aim of these observations was to explore the near-sun solar wind, which is the key region for the study of the solar wind acceleration mechanism. Strong quasars, 3C279 and 3C273B, were used for the Kashima IPS observations at 2 and 8GHz, and a water-vapor maser source, IRC20431, was used for the IPS observations at 22GHz. Solar wind speeds derived from Kashima IPS data suggest that the solar wind acceleration takes place at radial distances between 10 and 30 solar radii (Rs) from the sun. The properties of the turbulence spectrum (e.g. anisotropy, spectral index, inner scale) inferred from the Kashima data were found to change systematically in the solar wind acceleration region. While the solar wind in the maximum phase appears to be dominated by the slow wind, fast and rarefied winds associated with the coronal holes were found to develop significantly at high latitudes as the solar activity declined. Nevertheless, the Kashima data suggests that the location of the acceleration region is stable throughout the solar cycle.

Tokumaru, Munetoshi↗

The Development of a Finite Volume Method for Modeling Sound in Coastal Ocean Environment

: As the rapid growth of marine renewable energy and off-shore wind energy, there have been concerns that the noises generated from construction and operation of the devices may interfere marine animals’ communication. In this research, a underwater sound model is developed to simulate sound prorogation generated by marine-hydrokinetic energy (MHK) devices or offshore wind (OSW) energy platforms. Finite volume and finite difference methods are developed to solve the 3D Helmholtz equation of sound propagation in the coastal environment. For finite volume method, the grid system consists of triangular grids in horizontal plane and sigma-layers in vertical dimension. A 3D sparse matrix solver with complex coefficients is formed for solving the resulting acoustic pressure field. The Complex Shifted Laplacian Preconditioner (CSLP) method is applied to efficiently solve the matrix system iteratively with MPI parallelization using a high performance cluster. The sound model is then coupled with the Finite Volume Community Ocean Model (FVCOM) for simulating sound propagation generated by human activities in a range-dependent setting, such as offshore wind energy platform constructions and tidal stream turbines. As a proof of concept, initial validation of the finite difference solver is presented for two coastal wedge problems. Validation of finite volume method will be reported separately.

Coastal↗