Distributed resource integration analysis and network design of electric power distribution systems

The integration of high percentages of distributed energy resources and controllable loads into the distribution system coupled with the strict power quality and service reliability requirements at the power distribution level are necessitating a significant change in the planning, operation and control of the traditional power distribution system. The future power distribution circuits should be able to accommodate the new technologies while simultaneously providing a desired level of power quality and service reliability to the customers. This thesis aims to address the current and future grid requirements of both existing as well as new distribution systems with regard to power quality and service reliability issues. Several methods are proposed to evaluate and mitigate power quality and service reliability concerns due to the integration of smart grid technologies into both existing and new distribution circuits. Notably, for the existing distribution circuits, integration studies are simulated to analyze and mitigate the impacts of electric vehicle loads and photovoltaic generation on the distribution voltages. Furthermore, the problem of siting, sizing and deployment of distributed energy storage systems in meeting distribution planning requirements with regard to integrating distributed generation and providing contingency requirements is also addressed. A new distribution system both grid-connected and operating in islanded mode, however, could be designed to the new requirements. The new distribution circuit could be designed to meet the power quality and service reliability standards directly, thus more efficiently mitigating the concerns. In the thesis, the new distribution circuit design is approached from the perspective of maximizing the service reliability. For the new distribution circuit, approaches to reliability based distribution circuit design are proposed.Electrical and Computer Engineerin

Empiricism and stochastics in cellular automaton modeling of urban land use dynamics

An increasing number of models for predicting land use change in regions of rapidurbanization are being proposed and built using ideas from cellular automata (CA)theory. Calibrating such models to real situations is highly problematic and to date,serious attention has not been focused on the estimation problem. In this paper, wepropose a structure for simulating urban change based on estimating land usetransitions using elementary probabilistic methods which draw their inspiration fromBayes' theory and the related ?weights of evidence? approach. These land use changeprobabilities drive a CA model ? DINAMICA ? conceived at the Center for RemoteSensing of the Federal University of Minas Gerais (CSR-UFMG). This is based on aneight cell Moore neighborhood approach implemented through empirical land useallocation algorithms. The model framework has been applied to a medium-size townin the west of São Paulo State, Bauru. We show how various socio-economic andinfrastructural factors can be combined using the weights of evidence approach whichenables us to predict the probability of changes between land use types in differentcells of the system. Different predictions for the town during the period 1979-1988were generated, and statistical validation was then conducted using a multipleresolution fitting procedure. These modeling experiments support the essential logicof adopting Bayesian empirical methods which synthesize various information aboutspatial infrastructure as the driver of urban land use change. This indicates therelevance of the approach for generating forecasts of growth for Brazilian citiesparticularly and for world-wide cities in general

Demand side control for power system frequency regulation

The increasing penetration of renewable energy resources brings a number of uncertainties to modern power system operation. In particular, the frequent variation of wind or solar power output causes a short-term mismatch between generation and demand and system frequency fluctuation. The traditional approach to dealing with this problem is to increase the amount of system spinning reserve, which increases costs. In recent years, researchers have been actively exploring the utilization of residential and commercial loads in frequency regulation without affecting customers’ comfort level. This is called dynamic demand control (DDC). This dissertation describes an in-depth study of DDC for bulk power system frequency regulation, from both a technical and economic perspective

Reliability of Light Frame Roof Systems Subject to High Winds

Recent hurricane damages have devastated coastal communities and focused national attention on hurricane damage mitigation. Structural damage is one of the most significant impacts of a hurricane. Even small levels of structural damage can result in large economic losses; when gaps open in the roof system, rain water can leak in, ruining the contents of the structure and rendering it uninhabitable although it is still standing. In order to prevent these secondary damages from occurring, a better understanding of the roof system behavior is essential. This research aims to ascertain the behavior of the roof system by determining the influence of variable stiffness in the roof-to-wall connection on system behavior and to develop and propose a method for determining the reliability of a roof system typical to low-rise residential wood construction under wind loads. Monte Carlo simulations were run on a computer model of the roof system using probability density functions for both structural parameters and load variables. The goal of these simulations was to determine the effect of variable connection stiffness and wind zone discretization on the reliability of the roof system. One significant development this study utilized was an analytical connection model for the roof-to-wall connection, capable of shedding load past a randomly generated capacity value, taken from previous research. Sheathing wind loads were modeled as a lognormal variable and generated within the constraints of a correlation matrix. Results were obtained utilizing this Monte Carlo simulation. The system reliability was calculated as approximately 0.95 for a wind speed of 100 mph and 0.62 for a wind speed of 130 mph. The study\u27s results suggested that considering the variability in connection stiffness had little effect on the system reliability. The level of correlation between pressures on the roof, however, was shown to have a significant effect on the system reliability

Seismic vulnerability assessment of Portuguese adobe buildings

Adobe construction represents 5.3% of the total Portuguese building stock according to the latest National Housing Census. The distribution of these adobe buildings is scattered across the country, with higher density in the central region and in Algarve in the south, where the seismic hazard is highest. A large proportion of these buildings are still in use for residential and commercial purposes and are of historical significance, contributing to the cultural heritage of the country. Adobe buildings are known to exhibit low seismic resistance due to their brittle behavior, thus making them vulnerable to ground shaking and more prone to structural damage that can potentially cause human fatalities. Three buildings with one-story, two-stories, and two-stories plus an attic were numerically modeled using solid and contact elements. Calibration and validation of material properties were carried out following experimental results. A set of 30 ground motion records with bi-directional components were selected, and non-linear time-history analyses were performed until complete collapse occurred. Two novel engineering demand parameters (EDPs) were used, and damage thresholds were proposed. Finally, fragility and fatality vulnerability functions were derived. These functions can be used directly in seismic risk assessment studies.This work was funded by the Foundation for Science and Technology (FCT)—Aveiro Research Centre for Risks and Sustainability in Construction (RISCO), Universidade de Aveiro, Portugal in the framework of research project PTDC/ECI-EST/31865/2017 MitRisk—Framework for seismic risk reduction resorting to cost-effective retrofitting solutions

Impact of New Madrid Seismic Zone Earthquakes on the Central USA, Vol. 1 and 2

The information presented in this report has been developed to support the Catastrophic Earthquake Planning Scenario workshops held by the Federal Emergency Management Agency. Four FEMA Regions (Regions IV, V, VI and VII) were involved in the New Madrid Seismic Zone (NMSZ) scenario workshops. The four FEMA Regions include eight states, namely Illinois, Indiana, Kentucky, Tennessee, Alabama, Mississippi, Arkansas and Missouri. The earthquake impact assessment presented hereafter employs an analysis methodology comprising three major components: hazard, inventory and fragility (or vulnerability). The hazard characterizes not only the shaking of the ground but also the consequential transient and permanent deformation of the ground due to strong ground shaking as well as fire and flooding. The inventory comprises all assets in a specific region, including the built environment and population data. Fragility or vulnerability functions relate the severity of shaking to the likelihood of reaching or exceeding damage states (light, moderate, extensive and near-collapse, for example). Social impact models are also included and employ physical infrastructure damage results to estimate the effects on exposed communities. Whereas the modeling software packages used (HAZUS MR3; FEMA, 2008; and MAEviz, Mid-America Earthquake Center, 2008) provide default values for all of the above, most of these default values were replaced by components of traceable provenance and higher reliability than the default data, as described below. The hazard employed in this investigation includes ground shaking for a single scenario event representing the rupture of all three New Madrid fault segments. The NMSZ consists of three fault segments: the northeast segment, the reelfoot thrust or central segment, and the southwest segment. Each segment is assumed to generate a deterministic magnitude 7.7 (Mw7.7) earthquake caused by a rupture over the entire length of the segment. US Geological Survey (USGS) approved the employed magnitude and hazard approach. The combined rupture of all three segments simultaneously is designed to approximate the sequential rupture of all three segments over time. The magnitude of Mw7.7 is retained for the combined rupture. Full liquefaction susceptibility maps for the entire region have been developed and are used in this study. Inventory is enhanced through the use of the Homeland Security Infrastructure Program (HSIP) 2007 and 2008 Gold Datasets (NGA Office of America, 2007). These datasets contain various types of critical infrastructure that are key inventory components for earthquake impact assessment. Transportation and utility facility inventories are improved while regional natural gas and oil pipelines are added to the inventory, alongside high potential loss facility inventories. The National Bridge Inventory (NBI, 2008) and other state and independent data sources are utilized to improve the inventory. New fragility functions derived by the MAE Center are employed in this study for both buildings and bridges providing more regionally-applicable estimations of damage for these infrastructure components. Default fragility values are used to determine damage likelihoods for all other infrastructure components. The study reports new analysis using MAE Center-developed transportation network flow models that estimate changes in traffic flow and travel time due to earthquake damage. Utility network modeling was also undertaken to provide damage estimates for facilities and pipelines. An approximate flood risk model was assembled to identify areas that are likely to be flooded as a result of dam or levee failure. Social vulnerability identifies portions of the eight-state study region that are especially vulnerable due to various factors such as age, income, disability, and language proficiency. Social impact models include estimates of displaced and shelter-seeking populations as well as commodities and medical requirements. Lastly, search and rescue requirements quantify the number of teams and personnel required to clear debris and search for trapped victims. The results indicate that Tennessee, Arkansas, and Missouri are most severely impacted. Illinois and Kentucky are also impacted, though not as severely as the previous three states. Nearly 715,000 buildings are damaged in the eight-state study region. About 42,000 search and rescue personnel working in 1,500 teams are required to respond to the earthquakes. Damage to critical infrastructure (essential facilities, transportation and utility lifelines) is substantial in the 140 impacted counties near the rupture zone, including 3,500 damaged bridges and nearly 425,000 breaks and leaks to both local and interstate pipelines. Approximately 2.6 million households are without power after the earthquake. Nearly 86,000 injuries and fatalities result from damage to infrastructure. Nearly 130 hospitals are damaged and most are located in the impacted counties near the rupture zone. There is extensive damage and substantial travel delays in both Memphis, Tennessee, and St. Louis, Missouri, thus hampering search and rescue as well as evacuation. Moreover roughly 15 major bridges are unusable. Three days after the earthquake, 7.2 million people are still displaced and 2 million people seek temporary shelter. Direct economic losses for the eight states total nearly $300 billion, while indirect losses may be at least twice this amount. The contents of this report provide the various assumptions used to arrive at the impact estimates, detailed background on the above quantitative consequences, and a breakdown of the figures per sector at the FEMA region and state levels. The information is presented in a manner suitable for personnel and agencies responsible for establishing response plans based on likely impacts of plausible earthquakes in the central USA.Armu W0132T-06-02unpublishednot peer reviewe