Development of an experiment for ultrahigh-precision g-factor

Die vorliegende Arbeit befasst sich mit der Entwicklung und dem Aufbau eines Experiments zur hochpräzisen Bestimmung des g-Faktors gebundener Elektronen in hochgeladenen Ionen. Der g-Faktor eines Teilchens ist eine dimensionslose Konstante, die die Stärke der Wechselwirkung mit einem magnetischen Feld beschreibt. Im Falle eines an ein hochgeladenes Ion gebundenen Elektrons, dient es als einer der genausten Tests der Quantenelektrodynamik gebundener Zustande (BS-QED). Die Messung wird in einem dreifach Penning-Fallen System durchgeführt und basiert auf dem kontinuierlichen Stern-Gerlach-Effekt. Der erste Teil dieser Arbeit gibt den aktuellen Wissensstand über magnetische Momente wieder. Der hier gewählte experimentelle Aufbau wird begründet. Anschließend werden die experimentellen Anforderungen und die verwendeten Messtechniken erläutert. Das Ladungsbrüten der Ionen - einer der wichtigsten Aufgaben dieser Arbeit - ist dargestellt. Seine Realisierung basiert auf einer Feld-Emissions-Spitzen-Anordnung, die die Messung des Wirkungsquerschnitts für Elektronenstoßionisation ermöglicht. Der letzte Teil der Arbeit widmet sich der Entwicklung und dem Aufbau des Penning-Fallen Systems, sowie der Implementierung des Nachweisprozesses. Gegenwärtig ist der Aufbau zur Erzeugung hochgeladener Ionen und der dazugehörigen Messung des g-Faktors abgeschlossen, einschließlich des Steuerprogramms für die erste Datennahme. Die Ionenerzeugung und das Ladungsbrüten werden die nächsten Schritte sein.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Thermal Energy Storage for Solar Power Production

Solar energy is the most abundant persistent energy resource. It is also an intermittent one available for only a fraction of each day while the demand for electric power never ceases. To produce a significant amount of power at the utility scale, electricity generated from solar energy must be dispatchable and able to be supplied in response to variations in demand. This requires energy storage that serves to decouple the intermittent solar resource from the load and enables around-the-clock power production from solar energy. Practically, solar energy storage technologies must be efficient as any energy loss results in an increase in the amount of required collection hardware, the largest cost in a solar electric power system. Storing solar energy as heat has been shown to be an efficient, scalable, and relatively low-cost approach to providing dispatchable solar electricity. Concentrating solar power systems that include thermal energy storage (TES) use mirrors to focus sunlight onto a heat exchanger where it is converted to thermal energy that is carried away by a heat transfer fluid and used to drive a conventional thermal power cycle (e.g., steam power plant), or stored for later use. Several approaches to TES have been developed and can generally be categorized as either thermophysical (wherein energy is stored in a hot fluid or solid medium or by causing a phase change that can later be reversed to release heat) or thermochemical (in which energy is stored in chemical bonds requiring two or more reversible chemical reactions).

Measurement Properties of the Short Multi-Dimensional Observation Scale for Elderly Subjects (MOSES)

This study evaluated the five-factor measurement model of the abbreviated Multidimensional Observation Scale for Elderly Subjects (MOSES), originally proposed by Pruchno, Kleban, and Resch in 1988. Modifications of the five-factor model were examined and evaluated with regard to their practical significance. A confirmatory second-order factor analysis was performed to examine whether the correlations among the first-order factors were adequately accounted for by a global dysfunction factor. Findings indicated that the proposed measurement model was replicated adequately. Although post hoc modifications resulted in significant improvements in overall model fit, the minor parameters had only a trivial influence on the major parameters of the baseline model. Results from the second-order factor analysis showed that a global dysfunc tion factor accounted adequately for the intercorrelations among the first-order factors.

Charge induced enhancement of adsorption for hydrogen storage materials

The rising concerns about environmental pollution and global warming have facilitated research interest in hydrogen energy as an alternative energy source. To apply hydrogen for transportations, several issues have to be solved, within which hydrogen storage is the most critical problem. Lots of materials and devices have been developed; however, none is able to meet the DOE storage target. The primary issue for hydrogen physisorption is a weak interaction between hydrogen and the surface of solid materials, resulting negligible adsorption at room temperature. To solve this issue, there is a need to increase the interaction between the hydrogen molecules and adsorbent surface. In this study, intrinsic electric dipole is investigated to enhance the adsorption energy. The results from the computer simulation of single ionic compounds with hydrogen molecules to form hydrogen clusters showed that electrical charge of substances plays an important role in generation of attractive interaction with hydrogen molecules. In order to further examine the effects of static interaction on hydrogen adsorption, activated carbon with a large surface area was impregnated with various ionic salts including LiCl, NaCl, KCl, KBr, and NiCl and their performance for hydrogen storage was evaluated by using a volumetric method. Corresponding computer simulations have been carried out by using DFT (Density Functional Theory) method combined with point charge arrays. Both experimental and computational results prove that the adsorption capacity of hydrogen and its interaction with the solid materials increased with electrical dipole moment. Besides the intrinsic dipole, an externally applied electric field could be another means to enhance hydrogen adsorption. Hydrogen adsorption under an applied electric field was examined by using porous nickel foil as electrodes. Electrical signals showed that adsorption capacity increased with the increasing of gas pressure and external electric voltage. Direct measurement of the amount of hydrogen adsorption was also carried out with porous nickel oxides and magnesium oxides using the piezoelectric material PMN-PT as the charge supplier due to the pressure. The adsorption enhancement from the PMN-PT generated charges is obvious at hydrogen pressure between 0 and 60 bars, where the hydrogen uptake is increased at about 35% for nickel oxide and 25% for magnesium oxide. Computer simulation reveals that under the external electric field, the electron cloud of hydrogen molecules is pulled over to the adsorbent site and can overlap with the adsorbent electrons, which in turn enhances the adsorption energy Experiments were also carried out to examine the effects of hydrogen spillover with charge induced enhancement. The results show that the overall storage capacity in nickel oxide increased remarkably by a factor of 4.

Orbits design for Leo space based solar power satellite system

Space Based Solar Power satellites use solar arrays to generate clean, green, and renewable electricity in space and transmit it to earth via microwave, radiowave or laser beams to corresponding receivers (ground stations). These traditionally are large structures orbiting around earth at the geo-synchronous altitude. This thesis introduces a new architecture for a Space Based Solar Power satellite constellation. The proposed concept reduces the high cost involved in the construction of the space satellite and in the multiple launches to the geo-synchronous altitude. The proposed concept is a constellation of Low Earth Orbit satellites that are smaller in size than the conventional system. For this application a Repeated Sun-Synchronous Track Circular Orbit is considered (RSSTO). In these orbits, the spacecraft re-visits the same locations on earth periodically every given desired number of days with the line of nodes of the spacecraft’s orbit fixed relative to the Sun. A wide range of solutions are studied, and, in this thesis, a two-orbit constellation design is chosen and simulated. The number of satellites is chosen based on the electric power demands in a given set of global cities. The orbits of the satellites are designed such that their ground tracks visit a maximum number of ground stations during the revisit period. In the simulation, the locations of the ground stations are chosen close to big cities, in USA and worldwide, so that the space power constellation beams down power directly to locations of high electric power demands. The j2 perturbations are included in the mathematical model used in orbit design. The Coverage time of each spacecraft over a ground site and the gap time between two consecutive spacecrafts visiting a ground site are simulated in order to evaluate the coverage continuity of the proposed solar power constellation. It has been observed from simulations that there always periods in which s spacecraft does not communicate with any ground station. For this reason, it is suggested that each satellite in the constellation be equipped with power storage components so that it can store power for later transmission. This thesis presents a method for designing the solar power constellation orbits such that the number of ground stations visited during the given revisit period is maximized. This leads to maximizing the power transmission to ground stations.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

HOUSEHOLD SOLAR POWER SYSTEM

Photovoltaic power has become one of the most popular research area in new energy field. In this report, the case of household solar power system is presented. Based on the Matlab environment, the simulation is built by using Simulink and SimPowerSystem. There are four parts in a household solar system, solar cell, MPPT system, battery and power consumer. Solar cell and MPPT system are been studied and analyzed individually. The system with MPPT generates 30% more energy than the system without MPPT. After simulating the household system, it is can be seen that the power which generated by the system is 40.392 kWh per sunny day. By combining the power generated by the system and the price of the electric power, 8.42 years are need for the system to achieve a balance of income and expenditure when weather condition is considered.

DIMENSION REDUCTION FOR POWER SYSTEM MODELING USING PCA METHODS CONSIDERING INCOMPLETE DATA READINGS

Principal Component Analysis (PCA) is a popular method for dimension reduction that can be used in many fields including data compression, image processing, exploratory data analysis, etc. However, traditional PCA method has several drawbacks, since the traditional PCA method is not efficient for dealing with high dimensional data and cannot be effectively applied to compute accurate enough principal components when handling relatively large portion of missing data. In this report, we propose to use EM-PCA method for dimension reduction of power system measurement with missing data, and provide a comparative study of traditional PCA and EM-PCA methods. Our extensive experimental results show that EM-PCA method is more effective and more accurate for dimension reduction of power system measurement data than traditional PCA method when dealing with large portion of missing data set.

Political economy of low sulfurization and air pollution control policy in Japan : SOx emission reduction by fuel conversion

In the early stages of the development of Japan’s environmental policy, sulfur oxide (SOx) emissions, which seriously damage health, was the most important air pollution problem. In the second half of the 1960s and the first half of the 1970s, the measures against SOx emissions progressed quickly, and these emissions were reduced drastically. The most important factor of the reduction was the conversion to a low-sulfur fuel for large-scale fuel users, such as the electric power industry. However, industries started conversion to low-sulfur fuel not due to environmental concerns, but simply to reduce costs. Furthermore, the interaction among the various interests of the electric power industry, oil refineries, the central government, local governments, and citizens over the energy and environmental policies led to the measures against SOx emissions by fuel conversion.

Do electricity supply constraints matter for comparative advantage? : a neoclassical approach

This paper examines the extent to which electricity supply constraints could affect sectoral specialization. For this purpose, an empirical trade model is estimated from 1990-2008 panel data on 15 OECD countries and 12 manufacturing sectors. We find that along with Ricardian technological differences and Heckscher-Ohlin factor-endowment differences, productivity-adjusted electricity capacity drives sectoral specialization in several sectors. Among them, electrical equipment, transport equipment, machinery, chemicals, and paper products will see lower output shares as a result of decreases in productivity-adjusted electricity capacity. Furthermore, our dynamic panel estimation reveals that the effects of Ricardian technological differences dominate in the short-run, and factor endowment differences and productivity-adjusted electricity capacity tend to have a significant effect in only the long-run.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Change-Impact driven Agile Architecting.

Software architecture is a key factor to scale up Agile Software Development ASD in large softwareintensive systems. Currently, software architectures are more often approached through mechanisms that enable to incrementally design and evolve software architectures aka. agile architecting. Agile architecting should be a light-weight decision-making process, which could be achieved by providing knowledge to assist agile architects in reasoning about changes. This paper presents the novel solution of using change-impact knowledge as the main driver for agile architecting. The solution consists of a Change Impact Analysis technique and a set of models to assist agile architects in the change -decision-making- process by retrieving the change-impact architectural knowledge resulting from adding or changing features iteration after iteration. To validate our approach, we have put our solution into practice by running a project of a metering management system in electric power networks in an i-smart software factory.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Power Converter Topologies for a High Performance Transformer Rectifier Unit in Aircraft Applications

This paper presents some power converter architectures and circuit topologies, which can be used to achieve the requirements of the high performance transformer rectifier unit in aircraft applications, mainly as: high power factor with low THD, high efficiency and high power density. The voltage and the power levels demanded for this application are: three-phase line-to-neutral input voltage of 115 or 230V AC rms (360 – 800Hz), output voltage of 28V DC or 270V DC(new grid value) and the output power up to tens of kilowatts.