Overlapping and Robust Edge-Colored Clustering in Hypergraphs

A recent trend in data mining has explored (hyper)graph clustering algorithms for data with categorical relationship types. Such algorithms have applications in the analysis of social, co-authorship, and protein interaction networks, to name a few. Many such applications naturally have some overlap between clusters, a nuance which is missing from current combinatorial models. Additionally, existing models lack a mechanism for handling noise in datasets. We address these concerns by generalizing Edge-Colored Clustering, a recent framework for categorical clustering of hypergraphs. Our generalizations allow for a budgeted number of either (a) overlapping cluster assignments or (b) node deletions. For each new model we present a greedy algorithm which approximately minimizes an edge mistake objective, as well as bicriteria approximations where the second approximation factor is on the budget. Additionally, we address the parameterized complexity of each problem, providing FPT algorithms and hardness results

Regional Energy Deployment System (ReEDS)

The Regional Energy Deployment System (ReEDS) is a deterministic optimization model of the deployment of electric power generation technologies and transmission infrastructure throughout the contiguous United States into the future. The model, developed by the National Renewable Energy Laboratory's Strategic Energy Analysis Center, is designed to analyze the critical energy issues in the electric sector, especially with respect to potential energy policies, such as clean energy and renewable energy standards or carbon restrictions. ReEDS provides a detailed treatment of electricity-generating and electrical storage technologies and specifically addresses a variety of issues related to renewable energy technologies, including accessibility and cost of transmission, regional quality of renewable resources, seasonal and diurnal generation profiles, variability of wind and solar power, and the influence of variability on the reliability of the electrical grid. ReEDS addresses these issues through a highly discretized regional structure, explicit statistical treatment of the variability in wind and solar output over time, and consideration of ancillary services' requirements and costs

A Benefit Cost Study of a new Preschool Program Based on Neuroplasticity

38 p. An Honors Paper presented to the Department of Economics in 2006 Adviser: Bill Harbaug

Modeling the impact of state and federal incentives on concentrating solar power market penetration

ABSTRACT This paper presents methodology and results from the Regional Energy Deployment System Model (ReEDS) examining the ability of concentrating solar power (CSP), other renewables, and electricity storage to contribute to the U.S. electric sector. ReEDS is a multiregional, multi-time-period, geographic information system (GIS), and linear programming model, designed to address the principal market issues related to the penetration of renewable energy technologies into the electric sector over the next 50 years. These issues include transmission cost/access and the intermittency of solar and wind power. ReEDS examines these issues using a highly discrete regional structure, renewable resource variability, and consideration of ancillary services requirements and costs. The model was exercised in a business-as-usual scenario that doesn't require any renewable deployment, a second scenario that represents an implementation of current state renewable portfolio standard (RPS) requirements, and a third scenario with a federal renewables requirement. For the years to 2050, the amounts of national generation capacity by technology as well as the emission levels in each scenario are presented. Additionally, the regional deployment of CSP is also examined and presented. Background and Model Overview The Regional Energy Deployment System (ReEDS) 1 is a computer model of expansion of generation and transmission capacity in the U.S. electric sector spanning the next 50 years. It minimizes system-wide costs of meeting loads, reserve requirements, and emission constraints by building and operating new generators and transmission in each of 26 two-year periods from 2000 to 2050. ReEDS is focused on addressing the market issues of greatest significance to renewables. ReEDS attempts to examine these issues primarily by using a much higher level of geographic disaggregation than other models. Most other models -such as the National Energy Modeling System (NEMS) used by the U.S. Energy Information Agency -have only a few regions in the United States (13 in the case of the NEMS electric sector). Because of this, these models cannot adequately represent transmission and renewable energy resource spatial diversity. With a high level of geographic disaggregation, we can model these distance effects directly within the model. ReEDS uses 358 different regions in the entire United States. Much of the data inputs to ReEDS are tied to these regions and derived from a detailed GIS model/database of the renewable resources, transmission grid, and existing plant data. The geographic disaggregation of solar resources allows ReEDS to calculate transmission distances and the benefits of dispersed solar plants supplying power to a demand region. Concentrating solar power troughs (the technology currently included in ReEDS) are most economic in those regions with a high level of direct beam radiation. In the United States, viable resource areas are located primarily within the southwestern part of the United States. Therefore, to minimize model complexity. GIS data requirements

Knowledge is Power: Regaining Control from the Rebel Appliance

Electrical appliances serve important functions in our everyday lives, yet we have very little understanding of how they function. In light of our energy crisis, people are becoming more conscious of buying energy efficient products, but still lack a comprehensive knowledge of how much energy their appliance actually consumes. The purpose of this project is to supply a means by which the average consumer can better quantify the energy use of their household appliances, including the monetary cost associated with them, so as to gain the knowledge they would need to effectively cut back on their energy usage. The project has an added feature that allows it to communicate with your personal computer so that you can monitor energy usage over time. This allows consumers to truly see how much energy is being consumed, even when the appliance is in a low-power state, and track your progress in reducing your energy usage

Knowledge is Power: Regaining Control from the Rebel Appliance

Electrical appliances serve important functions in our everyday lives, yet we have very little understanding of how they function. In light of our energy crisis, people are becoming more conscious of buying energy efficient products, but still lack a comprehensive knowledge of how much energy their appliance actually consumes. The purpose of this project is to supply a means by which the average consumer can better quantify the energy use of their household appliances, including the monetary cost associated with them, so as to gain the knowledge they would need to effectively cut back on their energy usage. The project has an added feature that allows it to communicate with your personal computer so that you can monitor energy usage over time. This allows consumers to truly see how much energy is being consumed, even when the appliance is in a low-power state, and track your progress in reducing your energy usage

Contract No. DE-AC36-08GO28308U.S. Renewable Energy Technical Potentials: A GIS- Based Analysis

Contract No. DE-AC36-08GO28308NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available electronically a

U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis

This document describes the methodology and assumptions for estimating the technical potential of each energy generation potential technology. It then describes the resulting estimates

Regional Energy Deployment System (ReEDS)

The Regional Energy Deployment System (ReEDS) is a deterministic optimization model of the deployment of electric power generation technologies and transmission infrastructure throughout the contiguous United States into the future. The model, developed by the National Renewable Energy Laboratory's Strategic Energy Analysis Center, is designed to analyze the critical energy issues in the electric sector, especially with respect to potential energy policies, such as clean energy and renewable energy standards or carbon restrictions. ReEDS provides a detailed treatment of electricity-generating and electrical storage technologies and specifically addresses a variety of issues related to renewable energy technologies, including accessibility and cost of transmission, regional quality of renewable resources, seasonal and diurnal generation profiles, variability of wind and solar power, and the influence of variability on the reliability of the electrical grid. ReEDS addresses these issues through a highly discretized regional structure, explicit statistical treatment of the variability in wind and solar output over time, and consideration of ancillary services' requirements and costs