Greenhouse gas emissions from peat and biomass-derived fuels, electricity and heat — Estimation of various production chains by using LCA methodology

More discussion is required on how and which types of biomass should be used to achieve a significant reduction in the carbon load released into the atmosphere in the short term. The energy sector is one of the largest greenhouse gas (GHG) emitters and thus its role in climate change mitigation is important. Replacing fossil fuels with biomass has been a simple way to reduce carbon emissions because the carbon bonded to biomass is considered as carbon neutral. With this in mind, this thesis has the following objectives: (1) to study the significance of the different GHG emission sources related to energy production from peat and biomass, (2) to explore opportunities to develop more climate friendly biomass energy options and (3) to discuss the importance of biogenic emissions of biomass systems. The discussion on biogenic carbon and other GHG emissions comprises four case studies of which two consider peat utilization, one forest biomass and one cultivated biomasses. Various different biomass types (peat, pine logs and forest residues, palm oil, rapeseed oil and jatropha oil) are used as examples to demonstrate the importance of biogenic carbon to life cycle GHG emissions. The biogenic carbon emissions of biomass are defined as the difference in the carbon stock between the utilization and the non-utilization scenarios of biomass. Forestry-drained peatlands were studied by using the high emission values of the peatland types in question to discuss the emission reduction potential of the peatlands. The results are presented in terms of global warming potential (GWP) values. Based on the results, the climate impact of the peat production can be reduced by selecting high-emission-level peatlands for peat production. The comparison of the two different types of forest biomass in integrated ethanol production in pulp mill shows that the type of forest biomass impacts the biogenic carbon emissions of biofuel production. The assessment of cultivated biomasses demonstrates that several selections made in the production chain significantly affect the GHG emissions of biofuels. The emissions caused by biofuel can exceed the emissions from fossil-based fuels in the short term if biomass is in part consumed in the process itself and does not end up in the final product. Including biogenic carbon and other land use carbon emissions into the carbon footprint calculations of biofuel reveals the importance of the time frame and of the efficiency of biomass carbon content utilization. As regards the climate impact of biomass energy use, the net impact on carbon stocks (in organic matter of soils and biomass), compared to the impact of the replaced energy source, is the key issue. Promoting renewable biomass regardless of biogenic GHG emissions can increase GHG emissions in the short term and also possibly in the long term.

Modeling and Parameter Estimation of Double-Star Permanent Magnet Synchronous Machines

The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

Factors Affecting Customer Profitability: a Bibliometric Study

The first objective of the thesis is to find out which factors impact on customer profitability has been studied in scientific articles. The second objective is to find out the main authors and publishers from the subject area. Expectations were to find factors from marketing and management accounting literature, but this study did not succeed to gather management accounting perspective on the subject area. This study used bibliometric methods. The data for this study was collected manually from Scopus and Web of Science databases. Search words resulted 770 articles and from those 82 were included to further analyze. Descriptive analysis, citation analysis and content analysis were made. Bibexcel and Pajek software were used in this study. Publication activity was concentrated on years 2004-2013. The most productive author around the subject area is Kumar Vipin from Georgia State University (USA). A multiple customer profitability factors were identified. A lot of research was made for example about satisfaction, relationship duration, loyalty, marketing actions and customer equity drivers. The research is concentrated on service sector. The results are suggesting that there are research gaps in business-to-business and manufacturing sector.

The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

Sähkönsiirtoprojektien kustannuslaskennan kehittäminen

Tämän tutkimuksen tarkoituksena oli lisätä tietoa asiakasyrityksen voimajohto- ja sähköasemaliiketoimintayksiköiden tarjouslaskennan nykytilasta, etsiä ongelmakohtia ja kehittää ratkaisuja ongelmiin. Työn tuloksena saatu tieto on kyseisille liiketoimintayksiköille tärkeää tulevaisuuden kannattavuuden ja jatkuvuuden kannalta. Työn alun teoriaosuudessa esitellään Suomen sähkönsiirtojärjestelmä, käydään läpi voimajohto- ja sähköasemarakentamisen perusteet sekä esitellään kirjallisuuskatsaus projektiliiketoiminnasta. Teoriaosuutta hyödynnetään myöhemmissä tarkasteluissa joissa pyrittiin löytämään kustannuslaskennan ongelmia. Tutkimuksen tärkein tavoite oli löytää tämän hetkisen kustannuslaskennan ongelmakohdat. Tutkimukseen sisältyy tarjouslaskentaohjelmiston koekäyttö sekä sen analysointi. Työn lopputuloksena todetaan, ettei tarkasteltu ohjelma ole sopiva voimajohto- tai sähköasematarjouslaskennan toteutukseen. Ohjelma on laskentatarkkuudeltaan hyvä, mutta ohjelman käyttö hidastaa ja vaikeuttaa sekä laskennan että projektin talouden seurannan suorittamista. Lopputuloksissa todetaan myös erinäisiä pienempiä kehityskohteita tarjouslaskennan sujuvoittamiseksi ja sen tarkkuuden parantamiseksi. 

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

Profitability differences between online and offline retailers -An empirical study on European SMEs

Tämän pro gradu tutkielman tarkoituksena oli selvittää jos ja miten kannattavuus eroaa verkko- ja kivijalkakauppojen välillä. Lisäksi pyrittiin selvittämään onko näiden erojen syitä mahdollista selvittää yritysten taloudellisten tunnuslukujen avulla. Tutkielma koostuu kirjallisuuskatsauksesta ja kvantitatiivisesta tutkimuksesta. Kirjallisuuskatsaus antaa yleiskuvan siitä miten verkkokaupan toiminta eroaa kivijalkaliikkeen toiminnasta ja mitkä ovat näistä eroista koituvat hyödyt ja yleisimmät sudenkuopat. Kvantitatiivisessa tutkimuksessa käytetään Amadeus tietokannasta kerättyjä taloudellisia tietoja Eurooppalaisista verkko- ja kivijalkakaupoista. Tutkimuksessa löydettiin tilastollisesti merkitseviä eroja verkko- ja kivijalkakauppojen kannattavuudessa. Verkkokauppojen todettiin olevan kivijalkakauppoja kannattavampia, mutta taloudellisten tunnuslukujen tilastollisella analysoinnilla ei kyetty löytämään yksittäisiä selittäviä tekijöitä näille eroille.

Net working capital estimation model in project business

The objective of this Master’s thesis is to develop a model which estimates net working capital (NWC) monthly in a year period. The study is conducted by a constructive research which uses a case study. The estimation model is designed in the need of one case company which operates in project business. Net working capital components should be linked together by an automatic model and estimated individually, including advanced components of NWC for example POC receivables. Net working capital estimation model of this study contains three parts: output template, input template and calculation model. The output template gets estimate values automatically from the input template and the calculation model. Into the input template estimate values of more stable NWC components are inputted manually. The calculate model gets estimate values for major affecting components automatically from the systems of a company by using a historical data and made plans. As a precondition for the functionality of the estimation calculation is that sales are estimated in one year period because the sales are linked to all NWC components.

Power efficiency estimation and simulation of different control methods for the rotary screw compressor

Nowadays the energy efficiency has become one of the most concerned topics. Compressors are the equipment, which is very common in industry. Moreover, they tend to operate during long cycles and therefore even small decrease in power consumption can significantly reduce electricity costs during the year. And therefore it is important to investigate ways of increasing the energy efficiency of the compressors. In the thesis rotary screw compressor alongside with different control approaches is described. Simulation models for various control types of rotary screw compressor are developed. Analysis of laboratory equipment is conducted and results are compared with simulation. Suggestions of the real laboratory equipment improvement are given.

Effects of life cycle profits on the profitability of industrial heavy duty cranes

The goal of the thesis was to investigate how much after-sales profits a crane sale generates over the life cycle of the crane and the effects of these after-sales profits on the overall profitability of the crane. The thesis utilizes theories about life cycle costing from an equipment and service supplier’s point of view. However, instead of costs, the thesis is focused on the life cycle after-sales profits from maintenance services and spare parts provided for the sold crane. The case study approach was chosen and a total of five cranes from three different segments were investigated. An eight-step life cycle profit calculation model was developed in order to analyze the chosen cases’ life cycle profits systematically. The results of the investigation suggest that the life cycle after-sales profits are significant in value. In the case analyses they accounted for between 20% and 44% of the overall life cycle profits of the case cranes. The after-sales profits should be taken into account already in the pricing when offering a crane to a customer.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.