Im Freistaat Sachsen werden 7.500 Gebäude mit Erdwärme klimatisiert. Genutzt wird die Wärme aus der Tiefe vor allem bei Ein- und Mehrfamilienhäusern zur Heizung und Warmwasserbereitung. Bei Planung und Bau von Erdwärmeanlagen sind Aspekte der Qualitätssicherung und rechtliche Vorgaben zu beachten. Interessierten Bürgern, Planern und Bohrfirmen werden u. a. folgende Fragen beantwortet: - Welche Nutzungsformen der Erdwärme gibt es? - Welche Qualitätsanforderungen, Richtlinien und Gesetze sind einzuhalten? - Wie wird eine Anlage richtig geplant? - Wo und wie werden Bohrungen bei Behörden beantragt? Die Informationsbroschüre erscheint in 3. Auflage und ersetzt den Leitfaden für Erdwärmesonden.

Multi-energy systems offer an opportunity to leverage energy conversion processes and temporary energy storage mechanisms to reduce costs and emissions during operation of campuses, cities, and buildings. With increasing options for flexibility in demand-side resources it is possible to meet demand without sacrificing comfort and convenience of MES occupants. This Thesis develops a multi-period, linear optimization model of an MES with flexible buildings that captures nonlinearities in the efficiency of energy conversion processes. The flexible buildings are parametrized, in part, based on historical data from a college campus in Vermont, USA. The idea of the MES model is to investigate the role that flexibility plays in reducing costs and emissions for a small campus relative to that of a possible carbon tax. The operation of the MES is optimized to reduce costs based on representative seasons. Interestingly, it is found that when utilized optimally, flexible buildings allows for a more cost and energy effective method of not only meeting demand but also reducing carbon emissions in the process.

With the More Electric Aircraft paradigm, commercial commuter aircraft are increasing the size and complexity of electrical power systems by increasing the number of electrical loads. With this increase in complexity comes a need to analyze electrical power systems using new tools. The Hybrid Power System Optimizer (HyPSO) developed by Airbus SAS is a simulator designed to analyze new aircraft power systems. This thesis project will first provide a method to assess the reliability of complex aircraft electrical power systems before and after failure and reconfiguration events. Next, an add-on to HyPSO is developed to integrate the previously developed reliability calculations. Proof-of-concepts including new data visualizations are performed and provided.

This thesis presents the simulation, design, and hardware implementation of a modified multiphase boost converter. Converter design must consider noise imposed on input and output nodes which connect to and influence the operation of other devices. Excessive noise introduces EMI which can damage sensitive circuits or impede their operation. High ripple current degrades battery lifetime and reduces operating efficiency in connected systems such as PV arrays. Converters with high ripple current also experience greater peak conduction loss and require larger components. A two-phase implementation of a modified boost converter demonstrates the input current filtering benefits of the modified topology with increased power capacity. In a 12V to 19V 95W design, the modified multiphase design exhibits a reduced input current ripple of 1.103% compared to the 9.096% of the standard multiphase design while imposing minimal detriment to overall converter efficiency. The modified topology uses two inductors and one feedback capacitance per phase. Larger value inductors generally exhibit lower current ratings as well as larger size. The split inductance of the modified multiphase topology can be designed for occupation of less total volume than the single inductance of the standard multiphase topology.

With the advent of information explosion age, larger capacity disk drives are used to store data and powerful devices are used to process big data. As the scale and complexity of computer systems increase, we expect these systems to provide dependable and energy-efficient services and computation. Although hard drives are reliable in general, they are the most commonly replaced hardware components. Disk failures cause data corruption and even data loss, which can significantly affect system performance and financial losses. In this dissertation research, I analyze different manifestations of disk failures in production data centers and explore data mining techniques combined with statistical analysis methods to discover categories of disk failures and their distinctive properties. I use similarity measures to quantify the degradation process of each failure type and derive the degradation signature. The derived degradation signatures are further leveraged to forecast when future disk failures may happen. Meanwhile, this dissertation also studies energy efficiency of high performance computers. Specifically, I characterize the power and energy consumption of Haswell processors which are used in multiple supercomputers, and analyze the power and energy consumption of Legion, a data-centric programming model and runtime system, and Legion applications. We find that power and energy efficiency can be improved significantly by optimizing the settings and runtime scheduling of processors, and Legion runtime performs well for larger-scale computation in terms of power and energy consumption.

A wind turbine array was constructed in the wind tunnel at Portland State University in a standard Cartesian arrangement. Configurations of the turbine array were tested with rotor blades set to rotate in either a clockwise or counter-clockwise sense. Measurements of velocity were made with stereo particle-image velocimetry. Mean statistics of velocities and Reynolds stresses clearly show the effect of direction of rotation of rotor blades for both entrance and exit row turbines. Rotational sense of the turbine blades is visible in the mean spanwise velocity W and the Reynolds shear stress -[macron over vw]. The normalized anisotropy tensor was decomposed yielding invariants [lowercase eta] and [lowercase xi], which are plotted onto the Lumley triangle. Invariants of the normalized Reynolds stress anisotropy tensor indicate that distinct characters of turbulence exist in regions of the wake following the nacelle and the rotor blade tips. Eigendecomposition of the tensor yields principle components and corresponding coordinate system transformations. Characteristic spheroids are composed with the eigenvalues from the decomposition yielding shapes predicted by the Lumley triangle. Rotation of the coordinate system defined by the eigenvectors demonstrates streamwise trends, especially trailing the top rotor tip and below the hub of the rotors. Direction of rotation of rotor blades is evidenced in the orientation of characteristic spheroids according to principle axes. The characteristic spheroids of the anisotropy tensor and their relate alignments varies between cases clearly seen in the inflows to exit row turbines. There the normalized Reynolds stress anisotropy tensor shows cumulative effects of the rotational sense of upstream turbines. Comparison between the invariants of the Reynolds stress anisotropy tensor and terms from the mean mechanical energy equation indicate a correlation between the degree of anisotropy and the regions of the wind turbine wakes where turbulence kinetic energy is produced. The flux of kinetic energy into the momentum-deficit area of the wake from above the canopy is associated with prolate characteristic spheroids. Flux upward into the wake from below the rotor area is associate with oblate characteristic spheroids. Turbulence in the region of the flow directly following the nacelle of the wind turbines demonstrates more isotropy compared to the regions following the rotor blades. The power and power coefficients for wind turbines indicate that flow structures on the order of magnitude of the spanwise turbine spacing that increase turbine efficiency depending on particular array configuration.

The Markovianity within a wind turbine array boundary layer is explored for data taken in a wind tunnel containing a model wind turbine array. A stochastic analysis of the data is carried out using Markov chain theory. The data were obtained via hot-wire anemometry thus providing point velocity statistics. The theory of Markovian processes is applied to obtain a statistical description of longitudinal velocity increments inside the turbine wake using conditional probability density functions. It is found that two and three point conditional probability density functions are similar for scale differences larger than the Taylor micro-scale. This result is quantified by use of the Wilcoxon rank-sum test which verifies that this relationship holds independent of initial scale selection outside of the near-wake region behind a wind turbine. Furthermore, at the locations which demonstrate Markovian properties there is a well defined inertial sub-range which follows Kolmogorv's -5/3 scaling behavior. Results indicate an existence of Markovian properties at scales on the order of the Taylor micro-scale, λ for most locations in the wake. The exception being directly behind the tips of the rotor and the hub where the complex turbulent interactions characteristic of the near-wake demonstrate influence upon the Markov process. The presence of a Markov process in the remaining locations leads to characterization of the multi-point statistics of the wind turbine wakes using the most recent states of the flow.

Installation and utilization of residential distribution transformers has not changed substantially over a long period of time. Utilities typically size their transformers based on a formula that takes into account broadly what types and how many dwellings will be connected. Most new residential dwellings feature 200 Amp service per household with an anticipated energy demand of under 20,000 kWh per year. Average electrical energy consumption varies from state to state but averages to 11,280 kWh per year. Energy demand is expected to fall into a typical residential load curve that shows increased demand early in the morning, then decreasing during the day and another peak early to late evening. Distribution transformers are sized at the limit of the combined evening peak with the assumption that the transformer has enough thermal mass to absorb short overloads that may occur when concurrent loading situations among multiple dwellings arise. The assumption that concurrent loading is of short duration and the transformer can cool off during the night time has been validated over the years and has become standard practice. This has worked well when dwelling loads follow an averaging scheme and low level of coincidence. With the arrival of electric vehicles (EV's) this assumption has to be reevaluated. The acquisition of an electric vehicle in a household can drive up energy demand by over 4000 kWh per year. Potentially problematic is the increased capacity of battery packs and the resulting proliferation of Level 2 chargers. The additional load of a single Level 2 charger concurring with the combined evening peak load will push even conservatively sized distribution transformers over their nameplate rating for a substantial amount of time. Additionally, unlike common household appliances of similar power requirements such as ovens or water heaters, a Level 2 battery charger will run at peak power consumption for several hours, and the current drawn by the EVs has very high levels of harmonic distortion. The excessive loading and harmonic profile can potentially result in damaging heat build-up resulting in asset degradation. In this thesis I present a device and method that monitors pole mounted distribution transformers for overheating, collect and wirelessly upload data and initiate commands to chargers to change output levels from Level 2 to Level 1 or shut down EV charging altogether until the transformer returns into safe operational range.

Over the last the last three decades, there has been a significant and documented decrease of power engineering curriculum within U.S. electrical engineering programs. Development of lifelong learners capable of critical and independent thinking is required to replace the large number of upcoming retirees from the industry and to prepare for the engineering challenges new technologies, laws and regulations are bringing to the electrical power system. In response to these challenges, Portland State University redesigned its BSEE and MSECE power engineering programs in order to create a launching pad for successful power engineering careers. A course series on power system protection is part of the requisite curriculum for both programs. Due to the complex and applied nature of this subject, the course features a laboratory component. This thesis addresses the pedagogical and engineering problems associated with developing power systems protection laboratory curriculum. Laboratory equipment and curriculum design were guided by outcomes defined by ABET EC2000 and specific outcomes defined for the laboratory that we adopted from research commissioned by ABET. Hands-on experience with industry equipment and software enhances classroom-based course curriculum, expanding student understanding of the complexities of the subject of power system protection. Intergroup and intragroup communication is required in the laboratory, as are weekly written reports synthesizing subject material and experimental results. The outcomes of the laboratory are evaluated through a combination of grading rubrics and student participation in individual laboratory assignment surveys. The laboratory is comprised of three stations consisting of electromechanical (EM) relays and digital relay equipment. The practical experience with industry standard relays types happens in concert with a software-based simulation program. There are three phases of development; Phase I includes the design of the physical laboratory and the procural, or design and fabrication, of necessary equipment. Phase II involves the teaching term of the laboratory and the active assessment. Phase III involves the design and specification of a model-scale laboratory, to be built in future terms, which will provide students with the ability to test power system protection equipment in a physically simulated environment. This model-scale system will also provide a platform for future expansions of the power system protection laboratory in terms of distance protection, generation control, phasor measurement units, and system control schemes.

Vortex identification techniques are used to analyze the flow structure in a 4 x 3 array of scale model wind turbines. Q-criterion, Δ-criterion, and λ2-criterion are applied to Particle Image Velocimetry data gathered fore and aft of the last row centerline turbine. Q-criterion and λ2-criterion provide a clear indication of regions where vortical activity exists while the Δ-criterion does not. Galilean decomposition, Reynolds decomposition, vorticity, and swirling strength are used to further understand the location and behavior of the vortices. The techniques identify and display the high magnitude vortices in high shear zones resulting from the blade tips. Using Galilean and Reynolds decomposition, swirling motions are shown enveloping vortex regions in agreement with the identification criteria. The Galilean decompositions are 20% and 50% of a convective velocity of 7 m/s. As the vortices convect downstream, these vortices weaken in magnitude to approximately 25% of those present in the near wake. A high level of vortex activity is visualized as a result of the top tip of the wind turbine blade; the location where the highest vertical entrainment commences.