Assessment of Environmental Impacts of Power Generation

Through indisputable evidence of climate change and its link to the greenhouse gas emissions comes the necessity for change in energy production infrastructure during the coming decades. Through political conventions and restrictions energy industry is pushed toward using bigger share of renewable energy sources as energy supply. In addition to climate change, sustainable energy supply is another major issue for future development plans, but neither of these should come with unbearable price. All the power production types have environmental effects as well as strengths and weaknesses. Although each change comes with a price, right track in minimising the environmental impacts and energy supply security can be found by combining all possible low-carbon technologies and by improving energy efficiency in all sectors, for creating a new power production infrastructure of tolerable energy price and of minor environmental effects. GEMIS-Global Emission Model for Integrated Systems is a life-cycle analysis program which was used in this thesis to make indicative energy models for Finland’s future energy supply. Results indicate that the energy supply must comprise both high capacity nuclear power as well as large variation of renewable energy sources for minimization of all environmental effects and keeping energy price reasonable.

Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

Conservation Genetics of Exploited Finnish Salmonid Fishes

Genetic diversity is one of the levels of biodiversity that the World Conservation Union (IUCN) has recognized as being important to preserve. This is because genetic diversity is fundamental to the future evolution and to the adaptive flexibility of a species to respond to the inherently dynamic nature of the natural world. Therefore, the key to maintaining biodiversity and healthy ecosystems is to identify, monitor and maintain locally-adapted populations, along with their unique gene pools, upon which future adaptation depends. Thus, conservation genetics deals with the genetic factors that affect extinction risk and the genetic management regimes required to minimize the risk. The conservation of exploited species, such as salmonid fishes, is particularly challenging due to the conflicts between different interest groups. In this thesis, I conduct a series of conservation genetic studies on primarily Finnish populations of two salmonid fish species (European grayling, Thymallus thymallus, and lake-run brown trout, Salmo trutta) which are popular recreational game fishes in Finland. The general aim of these studies was to apply and develop population genetic approaches to assist conservation and sustainable harvest of these populations. The approaches applied included: i) the characterization of population genetic structure at national and local scales; ii) the identification of management units and the prioritization of populations for conservation based on evolutionary forces shaping indigenous gene pools; iii) the detection of population declines and the testing of the assumptions underlying these tests; and iv) the evaluation of the contribution of natural populations to a mixed stock fishery. Based on microsatellite analyses, clear genetic structuring of exploited Finnish grayling and brown trout populations was detected at both national and local scales. Finnish grayling were clustered into three genetically distinct groups, corresponding to northern, Baltic and south-eastern geographic areas of Finland. The genetic differentiation among and within population groups of grayling ranged from moderate to high levels. Such strong genetic structuring combined with low genetic diversity strongly indicates that genetic drift plays a major role in the evolution of grayling populations. Further analyses of European grayling covering the majority of the species’ distribution range indicated a strong global footprint of population decline. Using a coalescent approach the beginning of population reduction was dated back to 1 000-10 000 years ago (ca. 200-2 000 generations). Forward simulations demonstrated that the bottleneck footprints measured using the M ratio can persist within small populations much longer than previously anticipated in the face of low levels of gene flow. In contrast to the M ratio, two alternative methods for genetic bottleneck detection identified recent bottlenecks in six grayling populations that warrant future monitoring. Consistent with the predominant role of random genetic drift, the effective population size (N_e) estimates of all grayling populations were very low with the majority of N_e estimates below 50. Taken together, highly structured local populations, limited gene flow and the small N_e of grayling populations indicates that grayling populations are vulnerable to overexploitation and, hence, monitoring and careful management using the precautionary principles is required not only in Finland but throughout Europe. Population genetic analyses of lake-run brown trout populations in the Inari basin (northernmost Finland) revealed hierarchical population structure where individual populations were clustered into three population groups largely corresponding to different geographic regions of the basin. Similar to my earlier work with European grayling, the genetic differentiation among and within population groups of lake-run brown trout was relatively high. Such strong differentiation indicated that the power to determine the relative contribution of populations in mixed fisheries should be relatively high. Consistent with these expectations, high accuracy and precision in mixed stock analysis (MSA) simulations were observed. Application of MSA to indigenous fish caught in the Inari basin identified altogether twelve populations that contributed significantly to mixed stock fisheries with the Ivalojoki river system being the major contributor (70%) to the total catch. When the contribution of wild trout populations to the fisheries was evaluated regionally, geographically nearby populations were the main contributors to the local catches. MSA also revealed a clear separation between the lower and upper reaches of Ivalojoki river system – in contrast to lower reaches of the Ivalojoki river that contributed considerably to the catch, populations from the upper reaches of the Ivalojoki river system (>140 km from the river mouth) did not contribute significantly to the fishery. This could be related to the available habitat size but also associated with a resident type life history and increased cost of migration. The studies in my thesis highlight the importance of dense sampling and wide population coverage at the scale being studied and also demonstrate the importance of critical evaluation of the underlying assumptions of the population genetic models and methods used. These results have important implications for conservation and sustainable fisheries management of Finnish populations of European grayling and brown trout in the Inari basin.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

A comparison of electricity spot prices simulation using ARMA-GARCH and mean-reverting models

The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

Utilization of a Time Domain Simulator in the Technical and Economic Analysis of a Wind Turbine Electric Drive Train

The amount of installed wind power has been growing exponentially during the past ten years. As wind turbines have become a significant source of electrical energy, the interactions between the turbines and the electric power network need to be studied more thoroughly than before. Especially, the behavior of the turbines in fault situations is of prime importance; simply disconnecting all wind turbines from the network during a voltage drop is no longer acceptable, since this would contribute to a total network collapse. These requirements have been a contributor to the increased role of simulations in the study and design of the electric drive train of a wind turbine. When planning a wind power investment, the selection of the site and the turbine are crucial for the economic feasibility of the installation. Economic feasibility, on the other hand, is the factor that determines whether or not investment in wind power will continue, contributing to green electricity production and reduction of emissions. In the selection of the installation site and the turbine (siting and site matching), the properties of the electric drive train of the planned turbine have so far been generally not been taken into account. Additionally, although the loss minimization of some of the individual components of the drive train has been studied, the drive train as a whole has received less attention. Furthermore, as a wind turbine will typically operate at a power level lower than the nominal most of the time, efficiency analysis in the nominal operating point is not sufficient. This doctoral dissertation attempts to combine the two aforementioned areas of interest by studying the applicability of time domain simulations in the analysis of the economicfeasibility of a wind turbine. The utilization of a general-purpose time domain simulator, otherwise applied to the study of network interactions and control systems, in the economic analysis of the wind energy conversion system is studied. The main benefits of the simulation-based method over traditional methods based on analytic calculation of losses include the ability to reuse and recombine existing models, the ability to analyze interactions between the components and subsystems in the electric drive train (something which is impossible when considering different subsystems as independent blocks, as is commonly done in theanalytical calculation of efficiencies), the ability to analyze in a rather straightforward manner the effect of selections other than physical components, for example control algorithms, and the ability to verify assumptions of the effects of a particular design change on the efficiency of the whole system. Based on the work, it can be concluded that differences between two configurations can be seen in the economic performance with only minor modifications to the simulation models used in the network interaction and control method study. This eliminates the need ofdeveloping analytic expressions for losses and enables the study of the system as a whole instead of modeling it as series connection of independent blocks with no lossinterdependencies. Three example cases (site matching, component selection, control principle selection) are provided to illustrate the usage of the approach and analyze its performance.

Performance of high power fibre laser cutting of thick-section steel and mediumsection aluminium

Cutting of thick section stainless steel and mild steel, and medium section aluminium using the high power ytterbium fibre laser has been experimentally investigated in this study. Theoretical models of the laser power requirement for cutting of a metal workpiece and the melt removal rate were also developed. The calculated laser power requirement was correlated to the laser power used for the cutting of 10 mm stainless steel workpiece and 15 mm mild steel workpiece using the ytterbium fibre laser and the CO2 laser. Nitrogen assist gas was used for cutting of stainless steel and oxygen was used for mild steel cutting. It was found that the incident laser power required for cutting at a given cutting speed was lower for fibre laser cutting than for CO2 laser cutting indicating a higher absorptivity of the fibre laser beam by the workpiece and higher melting efficiency for the fibre laser beam than for the CO2 laser beam. The difficulty in achieving an efficient melt removal during high speed cutting of the 15 mmmild steel workpiece with oxygen assist gas using the ytterbium fibre laser can be attributed to the high melting efficiency of the ytterbium fibre laser. The calculated melt flow velocity and melt film thickness correlated well with the location of the boundary layer separation point on the 10 mm stainless steel cut edges. An increase in the melt film thickness caused by deceleration of the melt particles in the boundary layer by the viscous shear forces results in the flow separation. The melt flow velocity increases with an increase in assist gas pressure and cut kerf width resulting in a reduction in the melt film thickness and the boundary layer separation point moves closer to the bottom cut edge. The cut edge quality was examined by visual inspection of the cut samples and measurement of the cut kerf width, boundary layer separation point, cut edge squareness (perpendicularity) deviation, and cut edge surface roughness as output quality factors. Different regions of cut edge quality in 10 mm stainless steel and 4 mm aluminium workpieces were defined for different combinations of cutting speed and laserpower.Optimization of processing parameters for a high cut edge quality in 10 mmstainless steel was demonstrated

Distributed ControlArchitecture of Power Electronics Building-Block-Based Frequency Converters

The increasing power demand and emerging applications drive the design of electrical power converters into modularization. Despite the wide use of modularized power stage structures, the control schemes that are used are often traditional, in other words, centralized. The flexibility and re-usability of these controllers are typically poor. With a dedicated distributed control scheme, the flexibility and re-usability of the system parts, building blocks, can be increased. Only a few distributed control schemes have been introduced for this purpose, but their breakthrough has not yet taken place. A demand for the further development offlexible control schemes for building-block-based applications clearly exists. The control topology, communication, synchronization, and functionality allocationaspects of building-block-based converters are studied in this doctoral thesis. A distributed control scheme that can be easily adapted to building-block-based power converter designs is developed. The example applications are a parallel and series connection of building blocks. The building block that is used in the implementations of both the applications is a commercial off-the-shelf two-level three-phase frequency converter with a custom-designed controller card. The major challenge with the parallel connection of power stages is the synchronization of the building blocks. The effect of synchronization accuracy on the system performance is studied. The functionality allocation and control scheme design are challenging in the seriesconnected multilevel converters, mainly because of the large number of modules. Various multilevel modulation schemes are analyzed with respect to the implementation, and this information is used to develop a flexible control scheme for modular multilevel inverters.

Leptogenesis as the origin of matter-antimatter asymmetry in extra dimensional and supersymmetric models

The Standard Model of particle physics is currently the best description of fundamental particles and their interactions. All particles save the Higgs boson have been observed in particle accelerator experiments over the years. Despite the predictive power the Standard Model there are many phenomena that the scenario does not predict or explain. Among the most prominent dilemmas is matter-antimatter asymmetry, and much effort has been made in formulating scenarios that accurately predict the correct amount of matter-antimatter asymmetry in the universe. One of the most appealing explanations is baryogenesis via leptogenesis which not only serves as a mechanism of producing excess matter over antimatter but can also explain why neutrinos have very small non-zero masses. Interesting leptogenesis scenarios arise when other possible candidates of theories beyond the Standard Model are brought into the picture. In this thesis, we have studied leptogenesis in an extra dimensional framework and in a modified version of supersymmetric Standard Model. The first chapters of this thesis introduce the standard cosmological model, observations made on the photon to baryon ratio and necessary preconditions for successful baryogenesis. Baryogenesis via leptogenesis is then introduced and its connection to neutrino physics is illuminated. The final chapters concentrate on extra dimensional theories and supersymmetric models and their ability to accommodate leptogenesis. There, the results of our research are also presented.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

Modeling and Control of the Power Conversion Unit in a Solid Oxide Fuel Cell Environment

In this doctoral thesis, a power conversion unit for a 10 kWsolid oxide fuel cell is modeled, and a suitable control system is designed. The need for research was identified based on an observation that there was no information available about the characteristics of the solid oxide fuel cell from the perspective of power electronics and the control system, and suitable control methods had not previously been studied in the literature. In addition, because of the digital implementation of the control system, the inherent characteristics of the digital system had to be taken into account in the characteristics of the solid oxide fuel cell (SOFC). The characteristics of the solid oxide fuel cell as well the methods for the modeling and control of the DC/DC converter and the grid converter are studied by a literature survey. Based on the survey, the characteristics of the SOFC as an electrical power source are identified, and a solution to the interfacing of the SOFC in distributed generation is proposed. A mathematical model of the power conversion unit is provided, and the control design for the DC/DC converter and the grid converter is made based on the proposed interfacing solution. The limit cycling phenomenon is identified as a source of low-frequency current ripple, which is found to be insignificant when connected to a grid-tied converter. A method to mitigate a second harmonic originating from the grid interface is proposed, and practical considerations of the operation with the solid oxide fuel cell plant are presented. At the theoretical level, the thesis discusses and summarizes the methods to successfully derive a model for a DC/DC converter, a grid converter, and a power conversion unit. The results of this doctoral thesis can also be used in other applications, and the models and methods can be adopted to similar applications such as photovoltaic systems. When comparing the results with the objectives of the doctoral thesis, we may conclude that the objectives set for the work are met. In this doctoral thesis, theoretical and practical guidelines are presented for the successful control design to connect a SOFC-based distributed generation plant to the utility grid.

Energy Efficiency of a Diesel-Electric MobileWorking Machine

The power demand of many mobile working machines such as mine loaders, straddle carriers and harvesters varies significantly during operation, and typically, the average power demand of a working machine is considerably lower than the demand for maximum power. Consequently, for most of the time, the diesel engine of a working machine operates at a poor efficiency far from its optimum efficiency range. However, the energy efficiency of dieseldriven working machines can be improved by electric hybridization. This way, the diesel engine can be dimensioned to operate within its optimum efficiency range, and the electric drive with its energy storages responds to changes in machine loading. A hybrid working machine can be implemented in many ways either as a parallel hybrid, a series hybrid or a combination of these two. The energy efficiency of hybrid working machines can be further enhanced by energy recovery and reuse. This doctoral thesis introduces the component models required in the simulation model of a working machine. Component efficiency maps are applied to the modelling; the efficiency maps for electrical machines are determined analytically in the whole torque–rotational speed plane based on the electricalmachine parameters. Furthermore, the thesis provides simulation models for parallel, series and parallel-series hybrid working machines. With these simulation models, the energy consumption of the working machine can be analysed. In addition, the hybridization process is introduced and described. The thesis provides a case example of the hybridization and dimensioning process of a working machine, starting from the work cycle of the machine. The selection and dimensioning of the hybrid system have a significant impact on the energy consumption of a hybrid working machine. The thesis compares the energy consumption of a working machine implemented by three different hybrid systems (parallel, series and parallel-series) and with different component dimensions. The payback time of a hybrid working machine and the energy storage lifetime are also estimated in the study.

Power-line-communication-based data transmission concept for an LVDC electricity distribution network – Analysis and implementation

Communications play a key role in modern smart grids. New functionalities that make the grids ‘smart’ require the communication network to function properly. Data transmission between intelligent electric devices (IEDs) in the rectifier and the customer-end inverters (CEIs) used for power conversion is also required in the smart grid concept of the low-voltage direct current (LVDC) distribution network. Smart grid applications, such as smart metering, demand side management (DSM), and grid protection applied with communications are all installed in the LVDC system. Thus, besides remote connection to the databases of the grid operators, a local communication network in the LVDC network is needed. One solution applied to implement the communication medium in power distribution grids is power line communication (PLC). There are power cables in the distribution grids, and hence, they may be applied as a communication channel for the distribution-level data. This doctoral thesis proposes an IP-based high-frequency (HF) band PLC data transmission concept for the LVDC network. A general method to implement the Ethernet-based PLC concept between the public distribution rectifier and the customerend inverters in the LVDC grid is introduced. Low-voltage cables are studied as the communication channel in the frequency band of 100 kHz–30 MHz. The communication channel characteristics and the noise in the channel are described. All individual components in the channel are presented in detail, and a channel model, comprising models for each channel component is developed and verified by measurements. The channel noise is also studied by measurements. Theoretical signalto- noise ratio (SNR) and channel capacity analyses and practical data transmission tests are carried out to evaluate the applicability of the PLC concept against the requirements set by the smart grid applications in the LVDC system. The main results concerning the applicability of the PLC concept and its limitations are presented, and suggestion for future research proposed.