Demand Response of HVACs in Large Residential Communities Based on Experimental Developments

Heating, ventilation, and air-conditioning (HVAC) systems contribute the largest electricity usage for a residential community. Modeling of the HVAC systems facilitate the study of demand response (DR) at both the residential and the power system level. In this paper, the equivalent thermal model of a reference house was proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. The aggregated HVAC load was modeled based on the reference house while considering a realistic distribution of HVAC parameters derived from data that was provided by one of the largest smart grid field demonstrators in rural America. A sequential DR as part of a Virtual Power Plant (VPP) control was proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standard

The Effect of High Efficiency Building Technologies and PV Generation on the Energy Profiles for Typical US Residences

The penetrations of high efficiency technologies and photovoltaic (PV) generation are increasing in the residential sector. Technologies such as improved insulation and efficient HVAC systems significantly affect the energy profile of a house. This effect varies due to climate characteristics, i.e. temperature, solar radiation, relative humidity, and wind speeds. The effect of other technologies, such as efficient water heaters, lighting, or kitchen appliances, is mainly governed by human behavior, which may be represented by a schedule. This paper studies the performance of both climate-influenced and scheduled household devices among different levels of efficiency through combined computational and experimental methods. Three houses were constructed by the Tennessee Valley Authority and were outfitted with robots that mimicked the occupation of a family. The houses represented three categories of residences, namely, typical builder, retrofit, and near net-zero-energy. With the energy and weather data collected from 2009 to 2014, a total of four house energy models were developed to account for equipment changes throughout the years. The studies performed using these models considered the behavior of the HVAC systems, PV system, and water heaters as well as climate effects

Virtual Power Plant Control for Large Residential Communities Using HVAC Systems for Energy Storage

Heating, ventilation, and air-conditioning (HVAC) systems use the most electricity of any household appliance in residential communities. HVAC system modeling facilitates the study of demand response (DR) at both the residential and power system levels. In this article, the equivalent thermal model of a reference house is proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. Energy storage capacity of HVAC systems is calculated and an equivalent state-of-charge is defined. The uniformity between HVAC systems and battery energy storage system is demonstrated by DR control. The aggregated HVAC load model is based on the reference house and considers a realistic distribution of HVAC parameters derived from one of the largest smart grid field demonstrators in rural America. A sequential DR scheme as part of a virtual power plant control is proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standards

Roadside Truck Placard Readers for Advanced Notice and Response at Safety-Critical Facilities: Phase 2

The transport of hazardous and dangerous materials (HAZMAT) through safety-critical facilities poses significant risk to overall system reliability should those assets be incapacitated by the occurrence of a related incident. This problem is particularly acute for facilities in remote locations such as Virginia\u2019s mountain tunnels on Interstate 77 (I-77) due to limitations on alternate routes and the availability and proximity of emergency responders and specialized equipment/supplies. Automated placard reader systems (APRSs) are commercially available camera-based computer vision systems that \u201cread\u201d hazardous material placards on passing trucks from roadside installations. This information, along with other pertinent vehicle identification data may then be forwarded to critical facility operators to inform any preparations or responses that may be required. The Virginia Tech Transportation Institute conducted an initial phase of work to assess the readiness of APRSs for their reliable and effective roadside deployment and to determine how the data from such a system could be used by facility operators to improve safety and mitigate disruption during an event involving HAZMAT. The findings of the first phase of work indicated that available APRS technology was sufficiently advanced to warrant a second phase of work that included field testing and further refinement of the preliminary deployment plan. In Phase I, an APRS from Intelligent Imaging Systems (IIS) was identified for further evaluation. In this (second) phase of work, a mobile APRS system provided by IIS was evaluated under experimental and naturalistic scenarios at the Virginia Smart Roads and at several locations on Virginia public roads. A photographic survey of public HAZMAT placard usage conducted previously was used to inform this testing. Additional naturalistic data were acquired from a permanent APRS installation in Delaware when difficulties with the mobile APRS were encountered. The mobile and permanent APRSs were able to classify HAZMAT placard accurately at rates of 96% and 99%, respectively. The mobile and permanent systems were able to read United States Department of Transportation (USDOT) numbers from the sides of tractors correctly at rates of 46% and 67%, respectively, and tractor license plates correctly at rates of 43% and 39%, respectively. Moderate levels of rain and snow, as observed through roadside cameras and reported at nearby weather stations, had minimal impact on reporting accuracy. Performance of the system at night compared favorably with daytime performance. To address potential false negative concerns, a visual survey of 187 commercial vehicles was conducted that revealed that the APRS was 85% successful at locating and identifying the presence of placards on commercial vehicles passing in the near lane. With respect to implementation, the nature of how the subject APRS data is provided to users is not currently conducive to automated integration with existing or future VDOT tunnel or traffic management systems as data must be read from an online interface and no \u201cpush\u201d options are currently available. Also, providing advance warning of the approach of HAZMAT to tunnel operators on I-77 is not feasible given constraints related to the geographic siting of potential APRS installations and respective traffic characteristics. However, facility operator access to APRS data after an incident has occurred may provide benefits of improved responder and traveler safety as well as faster clearance times

The James Webb Space Telescope Mission: Optical Telescope Element Design, Development, and Performance

The James Webb Space Telescope (JWST) is a large, infrared space telescope that has recently started its science program which will enable breakthroughs in astrophysics and planetary science. Notably, JWST will provide the very first observations of the earliest luminous objects in the Universe and start a new era of exoplanet atmospheric characterization. This transformative science is enabled by a 6.6 m telescope that is passively cooled with a 5-layer sunshield. The primary mirror is comprised of 18 controllable, low areal density hexagonal segments, that were aligned and phased relative to each other in orbit using innovative image-based wavefront sensing and control algorithms. This revolutionary telescope took more than two decades to develop with a widely distributed team across engineering disciplines. We present an overview of the telescope requirements, architecture, development, superb on-orbit performance, and lessons learned. JWST successfully demonstrates a segmented aperture space telescope and establishes a path to building even larger space telescopes.Comment: accepted by PASP for JWST Overview Special Issue; 34 pages, 25 figure

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe