As power electronic based controllers and loads become more prevalent in power systems, there is a growing concern about how the harmonics generated by these controllers and loads affect the power quality of the system. One widely used power electronic based load is the Variable Frequency Drive (VFDs) used to vary the speed of an induction motor; whereas a common example of a power electronic based controller used in power systems is the Static VAR Compensator (SVC) for improving a system’s power factor. In this thesis, the harmonic content and overall performance of a system including both a VFD and a SVC will be studied and analyzed. Specifically, the cases of no compensation, static capacitor compensation, and power electronic based static VAR compensation are examined. A small-scale model of a system for study was constructed in lab. Several cases were then performed and tested to simulate a system which contained both fixed and power electronic based harmonic generating loads. The performance of each case was determined by total harmonic current and voltage distortions, true power factor, and RMS current levels at different points in the system.

This thesis investigates a relatively new method for harvesting wind energy by using flexible piezoelectric polymers with additional sails to increase their ability to harvest wind energy. This paper also introduces a new topology deemed the “stacked buck” that allows for multiple inputs to a system with a single output. Derivations and analysis detail the workings of the “stacked buck” with a laboratory test to show a working model. This paper also reports another experiment done in a wind tunnel to analyze the capability of the piezoelectric polymers as sources to the “stacked buck” topology with measurements of the power output. The results of this thesis demonstrate that because the design is very modular, it is possible to scale the proposed wind energy harvesting system for small power applications.

A load flow and contingency analysis program for secure design, planning and operation of power systems. Depending on the application either Newton-Raphson or Fast- Decoupled method is employed to solve the load flow. Fault analysis is done by Z bus method. Contingency analysis may be done following the load flow solution by Fast-Decoupled method. The program is also interfaced with a graphic system which displays a single line diagram of the system on the graphic screen along with relevant data and informs the operator of any change by flashing the faulted bus or the line outage.

Energy efficiency stands out with its potential to address a number of challenges that today's electric utilities face, including increasing and changing electricity demand, shrinking operating capacity, and decreasing system reliability and flexibility. Being the least cost and least risky alternative, the share of energy efficiency programs in utilities' energy portfolios has been on the rise since the 1980s, and their increasing importance is expected to continue in the future. Despite holding great promise, the ability to determine and invest in only the most promising program alternatives plays a key role in the successful use of energy efficiency as a utility-wide resource. This issue becomes even more significant considering the availability of a vast number of potential energy efficiency programs, the rapidly changing business environment, and the existence of multiple stakeholders. This dissertation introduces hierarchical decision modeling as the framework for energy efficiency program planning in electric utilities. The model focuses on the assessment of emerging energy efficiency programs and proposes to bridge the gap between technology screening and cost/benefit evaluation practices. This approach is expected to identify emerging technology alternatives which have the highest potential to pass cost/benefit ratio testing procedures and contribute to the effectiveness of decision practices in energy efficiency program planning. The model also incorporates rank order analysis and sensitivity analysis for testing the robustness of results from different stakeholder perspectives and future uncertainties in an attempt to enable more informed decision-making practices. The model was applied to the case of 13 high priority emerging energy efficiency program alternatives identified in the Pacific Northwest, U.S.A. The results of this study reveal that energy savings potential is the most important program management consideration in selecting emerging energy efficiency programs. Market dissemination potential and program development and implementation potential are the second and third most important, whereas ancillary benefits potential is the least important program management consideration. The results imply that program value considerations, comprised of energy savings potential and ancillary benefits potential; and program feasibility considerations, comprised of program development and implementation potential and market dissemination potential, have almost equal impacts on assessment of emerging energy efficiency programs. Considering the overwhelming number of value-focused studies and the few feasibility-focused studies in the literature, this finding clearly shows that feasibility-focused studies are greatly understudied. The hierarchical decision model developed in this dissertation is generalizable. Thus, other utilities or power systems can adopt the research steps employed in this study as guidelines and conduct similar assessment studies on emerging energy efficiency programs of their interest.

Grid-scale integration of renewable energy sources and smart grid devices has created new demands in flexible power conversion. State-of-the-art semiconductor power switches present limitations in power handling capability, as well as forward and reverse breakdown voltages. Superconducting materials are a viable alternative due to their robustness against high ampacities, large electric fields and abrupt changes in power flow. This work pays focus to material testing and apparatus design for an antenna-coupled cryotron (ACC), which is a superconducting power switch.Design, fabrication and testing are examined for a longitudinal resonant cavity, paired with monopole transmit and modified slot receive antennae. These couple radio frequency (RF) energy into superconducting thin film niobium (Nb) carrying high current densities (∼105A/cm2), thereby creating an antenna-coupled cryotron.Induced electromagnetic field effects at the receive antenna alter superconductive fluid dynamics. The theorized quality in manipulating this mechanism is a rapid normal-conductivity transition (µs), which affects a switch "off" state. Functional evaluation of the device as a waveguide revealed evanescent mode resonance at frequencies below the waveguide cut-off of ∼18GHz. The thin film Nb was deposited on a quartz dielectric, which penetrated the waveguide and supported evanescent resonances within the structure.Altered resistivity and critical transition-point properties emerged from device testing at applied RF. When the Nb film temperature-dependent coherence length was comparable to its thickness, perpendicular magnetic field application generated an Abrikosov vortex state, energetically favoring a mixed domain condensate. Interaction of the magnetically-induced flux vortex lattice with Lorentz current forces gave rise to resistive changes within the metal. Three resistive transition mechanisms developed: a latch to normal state resistance, attributed to cooper-pair destruction avalanche induced near critical transition points; a small reversible increase in resistance (∼mV), arising from flux-flow within an intermediate state at peak resonance; as well as temporal alterations in superfluid dynamics from disequilibrium in the quasi-particle population. The RF induced superfluid effects were observable in separate terms of electric and thermodynamic fluctuations.Motivation for this work is the eventual design of a high voltage, high current and low cost power switch, able to function where existing semiconductor technology fails. Concentration is paid to the fundamental theory, physics and methodology in conceptual testing and design of prototype ACCs. Assessment focuses on preliminary findings and concludes with next stage design requirements.

The exponential nature of Moore's law has inadvertently created huge data storage complexes that are scattered around the world. Data elements are continuously being searched, processed, erased, combined and transferred to other storage units without much regard to power consumption. The need for faster searches and power efficient data processing is becoming a fundamental requirement. Quantum computing may offer an elegant solution to speed and power through the utilization of the natural laws of quantum mechanics. Therefore, minimal cost quantum circuit implementation methodologies are greatly desired. This thesis explores the decomposition of group functions and the Walsh spectrum for implementing quantum canonical cascades with minimal cost. Three different methodologies, using group decomposition, are presented and generalized to take advantage of different quantum computing hardware, such as ion traps and quantum dots. Quantum square root of swap gates and fixed angle rotation gates comprise the first two methodologies. The third and final methodology provides further quantum cost reduction by more efficiently utilizing Hilbert spaces through variable angle rotation gates. The thesis then extends the methodology to realize a robust quantum circuit synthesis tool for single and multi-output quantum logic functions.

Present-day datacenter networks (DCNs) are designed to achieve full bisection bandwidth in order to provide high network throughput and server agility. However, the average utilization of typical DCN infrastructure is below 10% for significant time intervals. As a result, energy is wasted during these periods. In this thesis we analyze traffic behavior of datacenter networks using traces as well as simulated models. Based on the insight developed, we present techniques to reduce energy waste by making energy use scale linearly with load. The solutions developed are analyzed via simulations, formal analysis, and prototyping. The impact of our work is significant because the energy savings we obtain for networking infrastructure of DCNs are near optimal. A key finding of our traffic analysis is that network switch ports within the DCN are grossly under-utilized. Therefore, the first solution we study is to modify the routing within the network to force most traffic to the smallest of switches. This increases the hop count for the traffic but enables the powering off of many switch ports. The exact extent of energy savings is derived and validated using simulations. An alternative strategy we explore in this context is to replace about half the switches with fewer switches that have higher port density. This has the effect of enabling even greater traffic consolidation, thus enabling even more ports to sleep. Finally, we explore a third approach in which we begin with end-to-end traffic models and incrementally build a DCN topology that is optimized for that model. In other words, the network topology is optimized for the potential use of the datacenter. This approach makes sense because, as other researchers have observed, the traffic in a datacenter is heavily dependent on the primary use of the datacenter. A second line of research we undertake is to merge traffic in the analog domain prior to feeding it to switches. This is accomplished by use of a passive device we call a merge network. Using a merge network enables us to attain linear scaling of energy use with load regardless of datacenter traffic models. The challenge in using such a device is that layer 2 and layer 3 protocols require a one-to-one mapping of hardware addresses to IP (Internet Protocol) addresses. We overcome this problem by building a software shim layer that hides the fact that traffic is being merged. In order to validate the idea of a merge network, we build a simple mere network for gigabit optical interfaces and demonstrate correct operation at line speeds of layer 2 and layer 3 protocols. We also conducted measurements to study how traffic gets mixed in the merge network prior to being fed to the switch. We also show that the merge network uses only a fraction of a watt of power, which makes this a very attractive solution for energy efficiency. In this research we have developed solutions that enable linear scaling of energy with load in datacenter networks. The different techniques developed have been analyzed via modeling and simulations as well as prototyping. We believe that these solutions can be easily incorporated into future DCNs with little effort.

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations research, including non-convex problems. Finally, an optimization framework is applied to solve a problem in electric power systems involving a smart solar inverter and battery storage system providing energy and ancillary services to the grid.

Community solar is a renewable energy practice that's been adopted by multiple U.S. states and is being considered by many more, including the state of Oregon. A recent senate bill in Oregon, called the "Clean Electricity and Coal Transition Plan", includes a provision that directs the Oregon Public Utility Commission to establish a community solar program for investor-owned utilities by late 2017. Thus, energy consumers in Portland will be offered participation in community solar projects in the near future. Community solar is a mechanism that allows ratepayers to experience both the costs and benefits of solar energy while also helping to offset the proportion of fossil-fuel generated electricity in utility grids, thus aiding climate change mitigation. For community solar to achieve market success in the residential sector of Portland, ratepayers of investor-owned utilities must socially accept this energy practice. The aim of this study was to forecast the potential social acceptance of community solar among Portland residents by measuring willingness to participate in these projects. Additionally, consumer characteristics, attitudes, awareness, and knowledge were captured to assess the influence of these factors on intent to enroll in community solar. The theory of planned behavior, as well as the social acceptance, diffusion of innovation, and dual-interest theories were frameworks used to inform the analysis of community solar adoption. These research objectives were addressed through a mixed-mode survey of Portland residents, using a stratified random sample of Portland neighborhoods to acquire a gradient of demographics. 330 questionnaires were completed, yielding a 34.2% response rate. Descriptive statistics, binomial logistic regression models, and mean willingness to pay were the analyses conducted to measure the influence of project factors and demographic characteristics on likelihood of community solar participation. Roughly 60% of respondents exhibited interest in community solar enrollment. The logistic regression model revealed the percent change in utility bill (essentially the rate of return on the community solar investment) as a dramatically influential variable predicting willingness to participate. Community solar project scenarios also had a strong influence on willingness to participate: larger, cheaper, and distant projects were preferred over small and expensive local projects. Results indicate that community solar project features that accentuate affordability are most important to energy consumers. Additionally, demographic characteristics that were strongly correlated with willingness to enroll were politically liberal ideologies, higher incomes, current enrollment in green utility programs, and membership in an environmental organization. Thus, the market acceptance of community solar in Portland will potentially be broadened by emphasizing affordability over other features, such as community and locality. Additionally, I explored attitudinal influences on interest in community solar by conducting exploratory factor analysis on attitudes towards energy, climate change, and solar barriers and subsequently conducting binomial logistic regression models. Results found that perceiving renewable energy as environmentally beneficial was positively correlated with intent to enroll in community solar, which supported the notion that environmental attitudes will lead to environmental behaviors. The logistic regression model also revealed a negative correlation between community solar interest and negative attitudes towards renewable energy. Perceptions of solar barriers were mild, indicating that lack of an enabling mechanism may be the reason solar continues to be underutilized in this region.

Oregon utilities are replacing their portfolios of traditional fossil fuel generation with renewable generating sources. Stepping away from carbon-producing energy will leave a deficit of on-demand power, resulting in decreased reliability. To overcome these technical challenges, utilities must maximize the use of their present dispatchable resources. One such resource is the Portland General Electric (PGE) Dispatchable Standby Generation Program (DSG), which is an aggregated 105 MWs of distributed generation (DG). These resources are brought on-line when there is a critical need for power. Resources are added to the program if a transfer trip scheme is in place or a modeling study reveals that the feeder load is at least three times the generator capacity. If the load-to-capacity ratio were lower, more assets could be added to the DSG program. To investigate the impacts of lowering the DG load-to-capacity ratio on existing distribution feeders, we use Open-Source Distribution System Simulator (OpenDSS). We modeled the Oxford Rural feeder by converting a utility CYME database to instantiation files using several MATLAB programs. A MATLAB control program varies the load-to-capacity ratio of the OpenDSS feeder model and monitors the generator behavior immediately following a fault. We analyzed the results to determine the ideal load-to-capacity ratio that prevents unintentional islanding. The results show that the instantaneous (50) relay element settings dictate both the minimum load-to-capacity ratio and the maximum DG capacity. The present three-to-one ratio is very conservative and can be reduced. Additional dispatchable resources include a five MW battery-inverter system currently used as grid-back up. The battery is grid-tied to a 12.4 kV feeder making it an ideal candidate for conservation voltage reduction (CVR). Using the same feeder model, we investigated the effects of lowering the system voltage to the allowable minimum using injections of reactive power. A lower system voltage reduces the load at peak times. Conversely, increasing the voltage prevents generation conflicts. To determine the benefit of CVR by VAr-injection on the Oxford Rural feeder, we created a MATLAB optimization program to output the optimal feeder voltage for reduced system power. We use a Simulink feedback model to determine the appropriate reactive power needed to achieve the voltage change. We analyze the system model to reveal that the feeder is ideal for CVR but the system capacity must be increased to achieve the maximum power reduction.