This thesis is composed of two parts, that relate to both parallel and heterogeneous processing. The first describes DistCL, a distributed OpenCL framework that allows a cluster of GPUs to be programmed like a single device. It uses programmer-supplied meta-functions that associate work-items to memory. DistCL achieves speedups of up to 29x using 32 peers. By comparing DistCL to SnuCL, we determine that the compute-to-transfer ratio of a benchmark is the best predictor of its performance scaling when distributed. The second is a statistical power model for the AMD Fusion heterogeneous processor. We present a systematic methodology to create a representative set of compute micro-benchmarks using data collected from real hardware. The power model is created with data from both micro-benchmarks and application benchmarks. The model showed an average predictive error of 6.9% on heterogeneous workloads. The Multi2Sim heterogeneous simulator was modified to support configurable power modelling.

This thesis is composed of two parts, that relate to both parallel and heterogeneous processing. The first describes DistCL, a distributed OpenCL framework that allows a cluster of GPUs to be programmed like a single device. It uses programmer-supplied meta-functions that associate work-items to memory. DistCL achieves speedups of up to 29x using 32 peers. By comparing DistCL to SnuCL, we determine that the compute-to-transfer ratio of a benchmark is the best predictor of its performance scaling when distributed. The second is a statistical power model for the AMD Fusion heterogeneous processor. We present a systematic methodology to create a representative set of compute micro-benchmarks using data collected from real hardware. The power model is created with data from both micro-benchmarks and application benchmarks. The model showed an average predictive error of 6.9% on heterogeneous workloads. The Multi2Sim heterogeneous simulator was modified to support configurable power modelling.

When wind power and other intermittent renewable energy (IRE) sources begin to supply a significant part of the load, concerns are often raised about the inherent intermittency and unpredictability of these sources. In order to study the impact from higher IRE penetration levels on the power system, integration studies are regularly performed. The model package presented and evaluated in Papers I–IV provides a comprehensive methodology for simulating realistic time series of wind generation and forecasts for such studies. The most important conclusion from these papers is that models based on coarse meteorological datasets give very accurate results, especially in combination with statistical post-processing. Advantages with our approach include a physical coupling to the weather and wind farm characteristics, over 30 year long, 5-minute resolution time series, freely and globally available input data and computational times in the order of minutes. In this thesis, I make the argument that our approach is generally preferable to using purely statistical models or linear scaling of historical measurements. In the variability studies in Papers V–VII, several IRE sources were considered. An important conclusion is that these sources and the load have very different variability characteristics in different frequency bands. Depending on the magnitudes and correlations of these fluctuation, different time scales will become more or less challenging to balance. With a suitable mix of renewables, there will be little or no increase in the needs for balancing on the seasonal and diurnal timescales, even for a fully renewable Nordic power system. Fluctuations with periods between a few days and a few months are dominant for wind power and net load fluctuations of this type will increase strongly for high penetrations of IRE, no matter how the sources are combined. According to our studies, higher capacity factors, more offshore wind power and overproduction/curtailment would be beneficial for the power system.

This Thesis addressed the challenge of ensuring balanced currents in the phases of a multi-kW, interleaved dc-dc converter by means of closed-loop digital control. The Thesis examines uniformly-sampled, valley-current, peak-current and average-current control for a dual interleaved boost converter with inter-phase transformer which might form part of the power train of an electric vehicle. Also, an enhancement of the average-current control is investigated in which the transistor duty-ratio is updated more rapidly, which allows an improvement of approximately ten times in the response speed of the system. Based on the theoretical analysis, the average-current control methodology was determined to be the most suitable technique for this type of converter as it ensures well-balanced phase currents over a wide range. To provide a basis for control system analysis and design for interleaved converters, a modelling methodology is developed based on a combination of multi-rate data-sampled theory and a small-signal averaged converter model. The model is shown to represent accurately the interaction between the interleaved phases, revealing a reduced stability range compared with a non-interleaved converter. The modelling and control methods are validated using switched and average value simulations obtained with the SABER software and by experimental results from a 25 kW, 30 kHz converter prototype. The control techniques were implemented on a Texas Instruments TMS320F28335 digital signal controller.

Electrical energy is one of the most common forms of energy these days. Consequently, electric power system is an indispensable part of any society. However, due to the deregulation of electricity markets and the growth in the share of power generation by uncontrollable renewable energies such as wind and solar, power system simulations are more challenging than earlier. Thus, new techniques for simplifying these simulations are needed. One important example of such simplification techniques is the power system reduction. Power system reduction can be used at least for four different purposes: a) Simplifying the power system simulations, b) Reducing the computational complexity, c) Compensating the data unavailability, and d) Reducing the existing uncertainty. Due to such reasons, power system reduction is an important and necessary subject, but a challenging task to do. Power system reduction is even more essential when system operators are facing very large-scale power systems and when the renewable energy resources like hydro, wind, and solar have a high share in power generation. This thesis focuses on the topic of large-scale power system reduction with high penetration of renewable energy resources and tries to pursue the following goals: • The thesis first reviews the different methods which can be used for simplifying the power system studies, including the power system reduction. A comparison among three important simplification techniques is also performed to reveal which simplification results in less error and more simulation time decrement. • Secondly, different steps and methods for power system reduction, including network aggregation and generation aggregation, are introduced, described and discussed. • Some improvements regarding the subject of power system reduction, i.e. on both network aggregation and generation aggregation, are developed. • Finally, power system reduction is applied to some power system problems and the results of these applications are evaluated. A general conclusion is that using power system simplification techniques and specially the system reduction can provides many important advantages in studying large-scale power systems with high share of renewable energy generations. In most of applications, not only the power system reduction highly reduces the complexity of the power system study under consideration, but it also results in small errors. Therefore, it can be used as an efficient method for dealing with current bulk power systems with huge amounts of renewable and distributed generations. / <p>The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively. QC 20150116</p>