Distributed energy resources like residential electric water heaters and residential battery inverter systems offer a small amount of change to the grid individually. When aggregated however, these assets can cause major effects to the electric grid. Aggregating these resources allows them to take on generator-like functions with the ability to increment power and decrement power. The Western Energy Imbalance Market is an energy market offering 15 minute and 5 minute markets for energy transactions between balancing areas. Generation assets make increment and decrement bids. Traditionally the only entrants to this market have been large scale generators and large scale assets legally designated as generators. Aggregated distributed resources could offer the same increments and decrements from managing residential assets like electric water heaters and batteries. DERAS, a Distributed Energy Resource Aggregation System developed by the Portland State Power Lab group, is an aggregator of residential resources that could offer increment and decrement bids to an energy market, like an Energy Imbalance Market. This research models and simulates aggregations of distributed energy resources. This work analyzes the effects of 10,000 electric water heaters and 10,000 battery inverter systems. A simulation program was built to simulate regular use of these assets, and then add the additional effects of a decrement bid into the Western Energy Imbalance Market. The effects of the bids on energy levels inside the water heaters and batteries are examined. The power imported from the grid is also analyzed as an effect of the aggregator attempting to cover a generation decrement bid.

No description available.

No description available.

Networked systems integrating software with the physical world are known as cyber-physical systems (CPSs). CPSs have been used in diverse sectors, including power generation and distribution, transportation, industrial systems, and building management. The diversity of applications and interdisciplinary nature make CPSs exciting to design and build but challenging to manage once deployed. Deployed CPSs must adapt to changes in the operating environment or the system's architecture, e.g., when outdated or malfunctioning components need to be replaced. Skilled human operators have traditionally performed such adaptations using centralized management protocols. As the CPS grows, management tasks become more complex, tedious, and error-prone. This dissertation studies management challenges in deployed CPSs. It is based on practical research with CPSs of various sizes and diverse application domains, from the large geographically dispersed electrical grid to small-scale consumer Internet of Things (IoT) systems. We study the management challenges unique to each system and propose network services and protocols specifically designed to reduce the amount of management overhead, drawing inspiration from autonomic systems and networking research. We first introduce PhoenixSEN, a self-managing ad hoc network designed to restore connectivity in the electrical grid after a large-scale outage. The electrical grid is a large, heterogeneous, geographically dispersed CPS. We analyze the U.S. electrical grid network subsystem, propose an ad hoc network to temporarily replace the network subsystem during a blackout, and discuss the experimental evaluation of the network on a one-of-a-kind physical electrical grid testbed. The novel aspects of PhoenixSEN lie in a combination of existing and new network technologies and manageability by power distribution industry operators. Motivated by the challenges of running unmodified third-party applications in an ad hoc network like PhoenixSEN, we propose a geographic resource discovery and query processing service for federated CPSs called SenSQL. The service combines a resource discovery protocol inspired by the LoST protocol with a standard SQL-based query interface. SenSQL aims to simplify the development of applications for federated or administratively decoupled autonomous cyber-physical systems without a single administrative or technological point of failure. The SenSQL framework balances control over autonomous cyber-physical devices and their data with service federation, limiting the application's reliance on centralized infrastructures or services. We conclude the first part of the dissertation by presenting the design and implementation of a testbed for usability experiments with mission-critical voice, a vital communication modality in PhoenixSEN, and during emergency scenarios in general. The testbed can be used to conduct human-subject studies under emulated network conditions to assess the influence of various network parameters on the end-user's quality of experience. The second dissertation part focuses on network enrollment of IoT devices, a management process that is often complicated, frustrating, and error-prone, particularly in consumer-oriented systems. We motivate the work by reverse-engineering and analyzing Amazon Echo's network enrollment protocol. The Echo is one of the most widely deployed IoT devices and, thus, an excellent case study. We learn that the process is rather complicated and cumbersome. We then present a systematic study of IoT network enrollment with a focus on consumer IoT devices in advanced deployment scenarios, e.g., third-party installations, shared physical spaces, or evolving IoT systems. We evaluate existing frameworks and their shortcoming and propose WIDE, a network-independent enrollment framework designed to minimize user interactions to enable advanced deployment scenarios. WIDE is designed for large-scale or heterogeneous IoT systems where multiple independent entities cooperate to set the system up. We also discuss the design of a human-subject study to compare and contrast the usability of network enrollment frameworks. A secure network must authenticate a new device before it can be enrolled. The authentication step usually requires physical device access, which may be impossible in many advanced deployment scenarios, e.g., when IoT devices are installed by a specialist in physically unreachable locations. We propose Lighthouse, a visible-light authentication protocol for physically inaccessible IoT devices. We discuss the protocol's design, develop transmitter and receiver prototypes, and evaluate the system. Our measurements with off-the-shelf components over realistic distances indicate authentication times shorter or comparable with existing methods involving gaining physical access to the device. We also illustrate how the visible-light authentication protocol could be used as another authentication method in other network enrollment frameworks.

Geographic Information System (GIS) is a technology that can help collect, edit, store, manage, transform, analyze and represent data. This research aimed to show how mobile GIS application can  be designed, developed and applied to electric field work. An Android mobile application, which had been integrated with GIS was developed in Java. The prototype was tested and evaluated by employees of China Southern Power Grid (CSG). The resulting mobile application had three important features and functionalities: map view, location and electrical object querying, and attribute viewing and editing. According to the results of the user testing, the advantages of the application were its improved performance as brought about by the different scales used in the maps, its clear layout, and the speed of completing the query tasks. The disadvantages, on the other hand, were restrictions in the data types used and the query window. The study showed that with wireless communication, GPS and Location-based (LBS) supplements, electric utilities can benefit from this mobile GIS application in the following aspects: 1) eliminate the obstacles of going out in the field; 2) increase the flexibility of field work by faster access to data; 3) increase the accuracy and efficiency of field workers by dealing with the querying and editing task, and field mapping on a portable devices in real time. According to these aspects, electric field work can easily be enhanced by saving time, resources, and costs.

This study presents a multi-attribute decision making (MADM) framework in support of strategic resource planning of electric utilities. Study efforts have focused on four technical issues identified to be essentially important to the process of strategic resource development, i.e., decision data expansion, MADM analysis with imprecise information, MADM analysis under uncertainty and screening applications. Main contributions from this study are summarized as follows. First, an automatic learning method is introduced for decision data expansion aiming at reducing the amount of computations involved in the creation of decision database. Test results have shown that the proposed method is feasible, easy to implement, and more accurate than the techniques available in the existing literature. Second, an interval-based MADM methodology is developed, which extends the traditional utility function model with the measure of composite utility variance, accounting for individual errors from inaccurate attribute measurements and inconsistent priority judgments. This enhanced decision approach would help the decision-maker (DM) gain insight into how the imprecise data may affect the choice toward the best solution and how a range of acceptable alternatives may be identified with certain confidence. Third, an integrated MADM framework is developed for multi-attribute planning under uncertainty which combines attractive features of utility function, tradeoff/risk analysis and analytical hierarchy process and thus provides a structured decision analysis platform accommodating both probabilistic evaluation approach and risk evaluation approach. Fourth, the application of screening models is investigated in the context of integrated resource planning of electric utilities as to identify cost effective demand-side options and robust generation expansion planning schemes. / Ph. D.

Analyses and designs of a peak-power tracking system using microprocessor control are performed. Large-signal stability of the system for various modes of operation is analyzed to predict system dynamics. The stability analysis is supported mainly by qualitative graphical representations of different component blocks of the system. Small-signal stability analysis around the equilibrium points is done to assure proper performance and operation of this particular peak-power tracking system. Specific design details and procedures are discussed, and predictions from the analyses are verified through hardware. / Master of Science

Title IV of the 1990 Clean Air Act Amendments established a market-based incentive approach to pollution control through the use of tradable allowances for sulfur dioxide (SO₂) emissions by electric utilities. Many researchers have theorized that this approach will be compromised by state regulatory policies that create incentives for utilities to invest in costly pollution control equipment, inhibiting the formation of a free and competitive allowance market. The pUrpose of this research is to investigate the impact of state regulatory policies on the development of the SO₂ allowance market. More specifically, this research examines whether the geographic distribution of traded SO₂ allowances (as determined by an analysis of EPA Allowance Tracking System data) has been affected by the actions of state regulators. The research also investigates the effect of Title IV on the Virginia coal industry. Several trends in the allowance market are identified in this study, including the declining price of allowances, over compliance at Phase I units, and the geographic patterns of trading. This research only partially supports earlier predictions that states with regulatory policies biased towards costly capital investments in flue gas desulfurization (scrubber) retrofits would become net allowance sellers in the national market. However, the research finds that these state policies, along with several other factors (including the Phase I Extension program, the tax treatment of allowances, and the risk-averse nature of utilities) have contributed to the slow growth in the allowance market. The research also concludes that Virginia low-sulfur coal producers are not benefiting from Title IV implementation. / Master of Urban and Regional Planning

Previous research has shown that the asset pricing model of Sharpe, Litner and Black fails to capture the relationship between market β and average return. This previous work showed that the relationship between β and average return was flat. Subsequently it was shown that a strong relationship between book-to-market equity and stock price returns existed. It has also been shown that book to market equity has strong roots in economic fundamentals. Utilities have historically used betas to justify rate increases I developing rate structures that meet the rate of return demands for investors given the risk profiles that the company betas suggest. Realizing that low betas argue against large rate increases l utilities have turned to other avenues to justify higher returns. The suggested relationship of book-to-market equity and average stock returns would provide utilities with a new argument. This thesis will show that the search for a risk proxy in the rate of return relationship for the electric utility is not resolved. The relationship reported between book-to-market equity and stock price returns does not appear to be statistically significant in the electric utility sector and extreme caution is advised in using this empirical model to predict or explain stock price returns. / Master of Arts

Project Completion Report, OWRT Project No. A-043-ARIZ / Agreement No. 14-31-0001-4003 / Project Dates: July 1973 - June 1974 / Acknowledgment: The work upon which this report is based was supported in large part by funds provided by the United States Department of the Interior, Office of Water Research and Technology, as authorized under the Water Resources Research Act of 1964. / A growing demand for energy production in Arizona has increased the need for assembling and analyzing water resource information relative to energy production, especially electrical power generation. Unit water requirements for cooling of electrical plants, combined with projections of future electrical power demands in Arizona, provide a perspective on future quantities of water needed for cooling. Probabilistic estimates of storage reserves in Arizona groundwater basins indicate that some prospective plant sites can be supplied from groundwater for the 30 -year life of the plant, while others cannot. An estimate of comparative cost for supplying groundwater versus municipal wastewater for cooling electrical plants at selected sites in Arizona showed that use of wastewater would result in considerable savings over use of groundwater, at all sites considered.