This thesis is to investigate the power system operation strategy for an electrified mass rapid transit¡]MRT¡^network with the load transfer among main transformers by considering load growth and due to annual ridership increase, the loading factors of main transformers are improved so that the power system loss can be reduced. For the conventional planning of an electrified MRT system to serve the public transportation for the metropolitan area, the transformer capacity is often designed to meet the criterion of not only covering the peak demand but also providing the 100% fully capacity reserve for the system operation of target year. With such a high backup capability, the transformers are very lightly loaded for most of the operation time and significant core loss will be introduced over the lifecycle. In this thesis the train motion equation has been applied to find the mechanical power required, the proper strategy of unit commitment of main transformers and network reconfiguration by switching operation has been considered to enhance the operation efficiency of an MRT power system. To demonstrate the effectiveness of the proposed methodology, the Taipei MRT network is selected for computer simulation. It is found that the loading factors of main transformers can be improved dramatically and the load balance among the transformers can be obtained by the proper switching operation. An efficient strategy for transformer planning by taking into account the growth rate of load so that the overall investment cost of main transformers can be justified. The load characteristics and load growth rate of mass rapid transit¡]MRT¡^are derived by an Energy Management Model (EMM) and the AC load flow analysis is used to solve the transformer copper loss and core loss over the study period. To obtain optimal planning and operation strategy of main transformers for the MRT power system, the transformers initial investment cost and depreciation cost, peak power loss and energy loss, and reliability cost of distribution transformers are combined to form the overall cost function .By performing the dynamic programming (DP) the unit commitment of main transformers by considering the annual peak and off peak power loading of whole MRT system is derived. It is found that more efficient system operation can be obtained by the proposed methodology.

<p>The work presented in this thesis studies the load and loadeffects of traffic loads on railway bridges. The increasedknowledge of the traffic loads, simulated using fieldmeasurements of actual trains, are employed in a reliabilityanalysis in an attempt at upgrading existing railwaybridges.</p><p>The study utilises data from a weigh-in-motion site whichrecords, for each train, the train speed, the loads from eachaxle and the axle spacings. This data of actual trainconfigurations and axle loads are portrayed as moving forcesand then used in computer simulations of trains crossing twodimensional simply supported bridges at constant speed. Onlysingle track short to medium span bridges are considered in thethesis. The studied load effect is the moment at mid-span. Fromthe computer simulations the moment history at mid-span isobtained.</p><p>The load effects are analysed by two methods, the first isthe classical extreme value theory where the load effect ismodelled by the family of distributions called the generalisedextreme value distribution (GEV). The other method adopts thepeaks-over-threshold method (POT) where the limiting family ofdistributions for the heights to peaks-over-threshold is theGeneralised Pareto Distribution (GPD). The two models aregenerally found to be a good representation of the data.</p><p>The load effects modelled by either the GEV or the GPD arethen incorporated into a reliability analysis in order to studythe possibility of raising allowable axle loads on existingSwedish railway bridges. The results of the reliabilityanalysis show that they are sensitive to the estimation of theshape parameter of the GEV or the GPD.</p><p>While the study is limited to the case of the ultimate limitstate where the effects of fatigue are not accounted for, thefindings show that for the studied cases an increase inallowable axle load to 25 tonnes would be acceptable even forbridges built to the standards of 1940 and designed to LoadModel A of that standard. Even an increase to both 27.5 and 30tonnes appears to be possible for certain cases. It is alsoobserved that the short span bridges ofapproximately fourmetres are the most susceptible to a proposed increase inpermissible axle load.</p><p><b>Keywords:</b>bridge, rail, traffic load, load effect,dynamic amplification factor, extreme value theory,peaks-over-threshold, reliability theory, axle loads, fielddata.</p>

Engineers proposed the idea that arching action present may be present in bridge deck cantilever slab overhangs, stiffened along their longitudinal free edge via a traffic barrier, subjected to a wheel load. The experimental research program consisted of the design, construction, and static as well as fatigue destructive testing of a full-scale innovative bridge deck slab complete with two traffic barrier walls. The observed experimental data provided extremely interesting findings that indicated a very strong presence of arching action in edge-stiffened cantilever slab overhangs subjected to static and fatigue wheel loads. Deflection profiles indicated curvatures that contradict classical flexural behavior. Large tensile strain magnitudes on the bottom reinforcing mat in all cantilever test locations as well as cracking patterns dictate behavior typical to arching action. Top transverse strains measured did not agree with flexural theory and patterns confirmed earlier research finding that the quantity of top transverse reinforcement may be reduced. Compressive strains measured on the top surface of the cantilever contradicted flexural theory and confirmed the presence of arching action. Punching shear modes of failure observed in all test locations also strengthened the argument for the presence of arching action. Theoretical and analytical modeling techniques were able to validate and confirm the experimental test results. Based on experimental research findings and analytical modeling researchers were able to confirm a major presence of arching action in edge-stiffened cantilever slab overhangs subjected to static and fatigue wheel loads. Recommendations include a proposed reduction in top transverse reinforcement provided in the adjacent internal panel due to the presence arching action that could contribute to a significant initial capital cost savings. Based on the research findings, the report also suggests potential provisions to design codes that take into account the presence of arching action. Further research and theoretical modeling is still required to better understand the presence of arching action in edge-stiffened cantilever slab overhangs. Additional testing and a demonstration project complete with civionics and structural health monitoring will aid engineers in the implementation of the break-through findings highlighted in this study. / February 2016

A critical requirement of any remote microgrid is its capability to control the balance between electric generation and load within the confines of the microgrid itself. The integration of significant amounts of “as available” renewable generation to any electric grid (macro or micro) makes it more difficult to maintain this balance and can result in large frequency deviations on a microgrid. Ancillary services provide the resources required to maintain the instantaneous and ongoing balance between generation and load. Battery energy storage systems (BESS) can provide regulating reserves, a type of ancillary service, by modulating active power for frequency control, referred to as load frequency control (LFC), to reduce frequency deviations caused by sudden changes in renewable generation. Historically, the most common methodology for reducing frequency disturbances exacerbated by wind plants with BESS systems is ramp rate control and more recently lead compensation. This thesis proposed a modified lead compensator for use in microgrid applications. A PSS®E microgrid model, based upon existing validated models, was developed to test the effectiveness of the LFC controllers used to dispatch the BESS as a regulating resource to allow increased wind energy penetration levels on remote microgrids. A model of the remote microgrid of the island of Maui, Hawaii was chosen as the basis for the designs. Daily wind power data from 2012 was classified and indexed on an hourly basis by severity of variation. The worst hour for power variation from the wind plants was identified from this indexing and used as the basis for simulating the LFC controllers. The results compared the effectiveness of droop, ramp rate, lead compensation, and modified lead compensation controllers in reducing the variability in the grid frequency caused by changes in wind power generation. An RMS of variation with respect to an average over different time windows was used as the comparison metric. The combined modified lead compensator with ramp rate control showed the best performance of the overall system behavior. / text

Server farms are popular architectures for computing infrastructures such as supercomputing centers, data centers and web server farms. As server farms become larger and their workloads more complex, designing efficient policies for managing the resources in server farms via trial-and error becomes intractable. In this thesis, we employ stochastic modeling and analysis techniques to understand the performance of such complex systems and to guide design of policies to optimize the performance. There is a rich literature on applying stochastic modeling to diverse application areas such as telecommunication networks, inventory management, production systems, and call centers, but there are numerous disconnects between the workloads and architectures of these traditional applications of stochastic modeling and how compute server farms operate, necessitating new analytical tools. To cite a few: (i) Unlike call durations, supercomputing jobs and file sizes have high variance in service requirements and this critically affects the optimality and performance of scheduling policies. (ii) Most existing analysis of server farms focuses on the First-Come- First-Served (FCFS) scheduling discipline, while time sharing servers (e.g., web and database servers) are better modeled by the Processor- Sharing (PS) scheduling discipline. (in) Time sharing systems typically exhibit thrashing (resource contention) which limits the achievable concurrency level, but traditional models of time sharing systems ignore this fundamental phenomenon. (iv) Recently, minimizing energy consumption has become an important metric in managing server farms. State-of-the-art servers come with multiple knobs to control energy consumption, but traditional queueing models don’t take the metric of energy consumption into account. In this thesis we attempt to bridge some of these disconnects by bringing the stochastic modeling and analysis literature closer to the realities of today’s compute server farms. We introduce new queueing models for computing server farms, develop new stochastic analysis techniques to evaluate and understand these queueing models, and use the analysis to propose resource management algorithms to optimize their performance.

Hypothesis. Heterochronicity of body functions reveals itself during the performing different movement tasks, in particular at onset of the exercise or in changing the parameters of the load as well as during the recovering period. We think that estimations of body functional state of the sportsmen can better reflect manifestations of complexity of body functioning during the physical loads tries join different movement tasks: a dosed aerobic load and a maximum effort anaerobic load try. In order to verify this hypothesis it is purposeful to estimate peculiarities of functional state change and long-term adaptation effects due to concentrated physical loads of different direction. The aim of the research: to define how the functional state of subjects adapted to speed-power physical loads is affected by concentrated aerobic and anaerobic type loads by using various assessments of sportsmen functional state. CONCLUSIONS 1. Subjects adapted to speed-power physical loads distinguish themselves by the higher indices of muscles working-capacity by performing maximum short-term effort requiring tasks than non-athletes or the subjects adapted to endurance physical loads. From the standpoint of central nervous system functional state indices they distinguish themselves by greater central nervous system mobility and smallest central nervous system functional stability values. Speed-power representatives distinguish themselves by lower cardiovascular system indices related to... [to full text]

A single-chip, hybrid, heterogeneous, and dynamic shared memory multiprocessor architecture is being developed which may be used for real-time and non-real-time applications. This architecture can execute any application described by a dataflow (process flow) graph of any topology; it can also dynamically reconfigure its structure at the node and processor architecture levels and reallocate its resources to maximize performance and to increase reliability and fault tolerance. Dynamic change in the architecture is triggered by changes in parameters such as application input data rates, process execution times, and process request rates. The architecture is a Hybrid Data/Command Driven Architecture (HDCA). It operates as a dataflow architecture, but at the process level rather than the instruction level. This thesis focuses on the development, testing and evaluation of a new graphic software (hdca) developed to first do a static resource allocation for the architecture to meet timing requirements of an application and then hdca simulates the architecture executing the application using statically assigned resources and parameters. While simulating the architecture executing an application, the software graphically and dynamically displays parameters and mechanisms important to the architectures operation and performance. The new graphical software is able to show system and node level dynamic capability of the HDCA. The newly developed software can model a fixed or varying input data rate. The model also allows fault tolerance analysis of the architecture.

Despite the extensive deployment of smart-meters (SMs) at the low-voltage (LV) level, which are either fully operational or will be in the near future, distribution network operators (DNOs) are still relying on a limited number of permanently installed monitoring devices at primary and secondary medium-voltage (MV) substations, for purposes of network operation and control, as well as to inform and facilitate trading interactions between generators, distributors and suppliers. Accordingly, improved and sufficiently developed models for the analysis of aggregate demands at the MV-level are required for the correct assessment of load variability, composition and time-dependent evolution, necessary for: addressing issues of robustness, security and reliability; accomplishing higher penetration levels from renewable/distributed generation; implementing demand-side-management (DSM) schemes and incorporating new technologies; decreasing environmental and economic costs and aiding towards the realisation of automated and proactive ''smart-grid'' networks. The analysis of MV-demand measurements provides an independent source of information that can capture network characteristics that do not manifest in the data collected at the LV-level, or when such data is restricted or altogether unavailable. This information describes the supply/demand interactions at the mid-level between high-voltage (HV) transmission and LV end-user consumption and opens possibilities for validation of existing bottom-up aggregation approaches, while addressing issues of reliance on survey-based data for technical and economic power system studies. This thesis presents improved and novel methodologies for the analysis of aggregate demands, measured at MV-substations, aimed at more accurate and detailed load profiling, temporal decomposition and identification of the drivers of demand variability, classification of grid-supply- points (GSPs) according to consumption patterns, disaggregation with respect to customer-classes and load-types and load forecasting. The developed models are based on a number of traditional and modern analytical and statistical techniques, including: data mining, correlational and regression analysis, Fourier analysis, clustering and pattern recognition, etc. The approaches are demonstrated on demand datasets from UK and European based DNOs, thus providing specific information for the demand characteristics, the dependencies to external parameters and to socio-behavioural factors and the most likely load composition at the corresponding geographical locations, while the approaches are also intendent to be easily adaptable for studies at equivalent voltage and demand aggregation levels.

The growing uptake of wind and photovoltaic technologies requires further sources of system-level flexibility to avoid or defer significant investments. The ability to control, to some extent, customer demand (load management, LM) is one of these sources of flexibility. However, the direct involvement of a large number of customers makes the scalability of such approach a major challenge. A mostly unexplored solution to overcome the challenges of managing thousands or millions of customers is to leverage the positive correlation between voltage and demand. More precisely, Distribution Network Operators (DNOs) can control existing regulation devices to reduce customer voltages and so triggering a reduction in demand. This scheme, hereafter called voltage-led LM, avoids the direct involvement of customers overcoming one of the major barriers of traditional LM solutions. To understand whether this approach can be of any significance, a methodology able to quantify such reduction in demand need to be developed. However, the few methodologies available in the literature neglect the interactions across voltage levels and their influence on the benefits of the scheme. Moreover, time-varying demand profiles and load models are not always considered. Finally, the impact that the widespread adoption of distributed energy resources might have, is also neglected. This thesis addressed these gaps by developing a four-stage approach in which the time-varying volume of demand reduction that the scheme can unlock is quantified considering for the first time the influences among all voltage levels in distribution network. To reduce the complexity each voltage level is analysed separately whilst maintaining the corresponding dependencies. The methodology, also able to extrapolate the results at national scale, can quantify the impact that the uptake of residential scale PV units might have on the scheme. The methodology is demonstrated with a real UK case study where 10-min resolution time-series daily and seasonal analysis are performed. For the first time real network models across the whole distribution network, from 132 kV to 400 V, have been adopted. The interactions across voltage levels, the adoption of realistic load models, the variety of network models and the use of a time-varying approach, all aspects simultaneously considered for the first time in a case study, have shown to play a key role in the quantification. In Great Britain the scheme is expected to provide a significant volume of flexibility of around 1.8GW (60 GW of peak demand). The presence of PV, at least in the short term, has shown to have only a marginally effect on the benefits unlocked by the voltage-led LM scheme, making such scheme promising even in a low carbon future.

abstract: Voltage stability is always a major concern in power system operation. Recently Fault Induced Delayed Voltage Recovery (FIDVR) has gained increased attention. It is widely believed that the motor-driven loads of high efficiency, low inertia air conditioners are one of the main causes of FIDVR events. Simulation tools that assist power system operation and planning have been found insufficient to reproduce FIDVR events. This is because of their inaccurate load modeling of single-phase motor loads. Conventionally three-phase motor models have been used to represent the aggregation effect of single-phase motor load. However researchers have found that this modeling method is far from an accurate representation of single-phase induction motors. In this work a simulation method is proposed to study the precise influence of single-phase motor load in context of FIDVR. The load, as seen the transmission bus, is replaced with a detailed distribution system. Each single-phase motor in the distribution system is represented by an equipment-level model for best accuracy. This is to enable the simulation to capture stalling effects of air conditioner compressor motors as they are related to FIDVR events. The single phase motor models are compared against the traditional three phase aggregate approximation. Also different percentages of single-phase motor load are compared and analyzed. Simulation result shows that proposed method is able to reproduce FIDVR events. This method also provides a reasonable estimation of the power system voltage stability under the contingencies. / Dissertation/Thesis / M.S. Electrical Engineering 2012