Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Integrated energy storage tank for large scale power-to-gas applications

The global interest towards renewable energy production such as wind and solar energy is increasing, which in turn calls for new energy storage concepts due to the larger share of intermittent energy production. Power-to-gas solutions can be utilized to convert surplus electricity to chemical energy which can be stored for extended periods of time. The energy storage concept explored in this thesis is an integrated energy storage tank connected to an oxy-fuel combustion plant. Using this approach, flue gases from the plant could be fed directly into the storage tank and later converted into synthetic natural gas by utilizing electrolysis-methanation route. This work utilizes computational fluid dynamics to model the desublimation of carbon dioxide inside a storage tank containing cryogenic liquid, such as liquefied natural gas. Numerical modelling enables the evaluation of the transient flow patterns caused by the desublimation, as well as general fluid behaviour inside the tank. Based on simulations the stability of the cryogenic storage and the magnitude of the key parameters can be evaluated.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Electromagnetic and thermal design of a multilevel converter with high power density and reliability

Electric energy demand has been growing constantly as the global population increases. To avoid electric energy shortage, renewable energy sources and energy conservation are emphasized all over the world. The role of power electronics in energy saving and development of renewable energy systems is significant. Power electronics is applied in wind, solar, fuel cell, and micro turbine energy systems for the energy conversion and control. The use of power electronics introduces an energy saving potential in such applications as motors, lighting, home appliances, and consumer electronics. Despite the advantages of power converters, their penetration into the market requires that they have a set of characteristics such as high reliability and power density, cost effectiveness, and low weight, which are dictated by the emerging applications. In association with the increasing requirements, the design of the power converter is becoming more complicated, and thus, a multidisciplinary approach to the modelling of the converter is required. In this doctoral dissertation, methods and models are developed for the design of a multilevel power converter and the analysis of the related electromagnetic, thermal, and reliability issues. The focus is on the design of the main circuit. The electromagnetic model of the laminated busbar system and the IGBT modules is established with the aim of minimizing the stray inductance of the commutation loops that degrade the converter power capability. The circular busbar system is proposed to achieve equal current sharing among parallel-connected devices and implemented in the non-destructive test set-up. In addition to the electromagnetic model, a thermal model of the laminated busbar system is developed based on a lumped parameter thermal model. The temperature and temperature-dependent power losses of the busbars are estimated by the proposed algorithm. The Joule losses produced by non-sinusoidal currents flowing through the busbars in the converter are estimated taking into account the skin and proximity effects, which have a strong influence on the AC resistance of the busbars. The lifetime estimation algorithm was implemented to investigate the influence of the cooling solution on the reliability of the IGBT modules. As efficient cooling solutions have a low thermal inertia, they cause excessive temperature cycling of the IGBTs. Thus, a reliability analysis is required when selecting the cooling solutions for a particular application. The control of the cooling solution based on the use of a heat flux sensor is proposed to reduce the amplitude of the temperature cycles. The developed methods and models are verified experimentally by a laboratory prototype.

The transforming network of a foreign company operating in Mongolia. Case: A Finnish firm in Mongolia

In the globalising business environment ever fewer market areas remain unknown. Mongolia is yet only considered as an isolated strip between two power states. The purpose of this study is to put Mongolia on the map of academic business research. This is done by describing the transforming network of a foreign company operating in Mongolia. The objective of the study is approached through a case study, which presents the transformation of a Finnish company operating in Mongolia. This study aims at providing understanding on how the foreign case company observes the transformations of its network. The transformation within the case company is reflected to the transformations that occur in the Mongolian business environment. This study was conducted through a qualitative, intrinsic case study approach. The empirical data was gathered by using the method of network pictures. The network pictures were completed with the assistance of themed interviews. In order to be able to analyse the transformation within a network, three different time periods were observed: the past period around 2000, the present around 2014, and the estimated future around 2020. The data was collected from four executives positioned either in Finland, Russia or Mongolia. The respondents have a long experience within the case company, they hold managerial position, and therefore were able to offer valuable data for this study. The analytical framework used to analyse the collected data was built on the industrial network model, the ARA (actors-resources-activities)-model. The study shows that the changing business environment of Mongolia was utilised by the case company. In order to better meet the transforming customer wishes, the case company transformed from being a retailer to being a manufacturer. The case company was able to become a pioneer in the market. Thus, the case company has undergone similar kind of rapid transformation as the economy of Mongolia in entirety. This study shows that the general nature of the ARA-model makes it usable for new research contexts. The initial ARA-model offers a way to identify the dimensions of a network and a mean to understand these dimensions. The ARA-model can be applied to different contexts and to all time dimensions, past, present and future. The managerial recommendations offered in this study are directed towards the managers that plan to start operations in Mongolia. While this study is the first of its kind, it offers a good starting point for the future research on the change of Mongolian business networks. Valuable information could, for example, be obtained from a comparative study between the case company of this study and a multinational mining company operating in Mongolia.

Determination of the thermal parameters of high-power batteries by local heat

A new approach to the determination of the thermal parameters of high-power batteries is introduced here. Application of local heat flux measurement with a gradient heat flux sensor (GHFS) allows determination of the cell thermal parameters in di_erent surface points of the cell. The suggested methodology is not cell destructive as it does not require deep discharge of the cell or application of any charge/discharge cycles during measurements of the thermal parameters of the cell. The complete procedure is demonstrated on a high-power Li-ion pouch cell, and it is verified on a sample with well-known thermal parameters. A comparison of the experimental results with conventional thermal characterization methods shows an acceptably low error. The dependence of the cell thermal parameters on state of charge (SoC) and measurement points on the surface was studied by the proposed measurement approach.

Involving employees in six sigma

Six sigma is a quality improvement philosophy with systematic and formal approach. In order to successfully implement and utilize six sigma the basic disciplines of it should be adopted by the entire organization. Furthermore, employee involvement is crucial in six sigma implementation. This thesis addresses the challenges of long-lasting involvement in the case company. It focuses on gaps of involving six sigma trained employees, Black Belts. Theoretical framework of the thesis illustrates different factors influencing employee involvement. Influencing factors can be divided into ten categories: organizational culture, managerial commitment, leadership style, employee empowerment, employees’ perceptions, communication, training, goals, performance measurement and incentives. Factors and categories overlap and are related to each other. The framework provides holistic view of employee involvement in six sigma context but can be used also with other quality management philosophies. This thesis was conducted as a case study and written on an assignment to a power and automation technology company. Due to the nature of research problem, the data collection was conducted by interviewing case company personnel. In order to study involvement from employees’ point of view interview questions were designed to be open-ended and to allow the interviewees to tell freely about the phenomenon. This thesis provides empirical support on previous studies in organizational support, management commitment and employee empowerment. In addition, it indicates the importance of separate function for Black Belts in the organization. The gaps in Black Belt involvement can be categorized under two categories: Management driven gaps are related to management commitment, organizational structure and culture and information systems. Black Belt driven gaps are related to practice and effort of using six sigma. This thesis finds solutions for bridging these gaps in the case company by applying findings from literature research and suggestions given by the interviewees. For each gap, actions are suggested for bridging the discrepancy between current and desired situations. The thesis states that in order to embed six sigma in the organization the most crucial gaps, lack of management commitment, six sigma vision and possibilities to use six sigma, should be diminished.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.

Involving employees in six sigma

Six sigma is a quality improvement philosophy with systematic and formal approach. In order to successfully implement and utilize six sigma the basic disciplines of it should be adopted by the entire organization. Furthermore, employee involvement is crucial in six sigma implementation. This thesis addresses the challenges of long-lasting involvement in the case company. It focuses on gaps of involving six sigma trained employees, Black Belts. Theoretical framework of the thesis illustrates different factors influencing employee involvement. Influencing factors can be divided into ten categories: organizational culture, managerial commitment, leadership style, employee empowerment, employees’ perceptions, communication, training, goals, performance measurement and incentives. Factors and categories overlap and are related to each other. The framework provides holistic view of employee involvement in six sigma context but can be used also with other quality management philosophies. This thesis was conducted as a case study and written on an assignment to a power and automation technology company. Due to the nature of research problem, the data collection was conducted by interviewing case company personnel. In order to study involvement from employees’ point of view interview questions were designed to be open-ended and to allow the interviewees to tell freely about the phenomenon. This thesis provides empirical support on previous studies in organizational support, management commitment and employee empowerment. In addition, it indicates the importance of separate function for Black Belts in the organization. The gaps in Black Belt involvement can be categorized under two categories: Management driven gaps are related to management commitment, organizational structure and culture and information systems. Black Belt driven gaps are related to practice and effort of using six sigma. This thesis finds solutions for bridging these gaps in the case company by applying findings from literature research and suggestions given by the interviewees. For each gap, actions are suggested for bridging the discrepancy between current and desired situations. The thesis states that in order to embed six sigma in the organization the most crucial gaps, lack of management commitment, six sigma vision and possibilities to use six sigma, should be diminished.

Effect of Material Recycling on the Feasibility of Solid Recovered Fuel Fired Power Plant

This master’s thesis examines the effects of increased material recycling on different waste-to-energy concepts. With background study and a developed techno-economic computational method the feasibility of chosen scenarios with different combinations of mechanical treatment and waste firing technologies can be evaluated. The background study covers the waste scene of Finland, and potential market areas Poland and France. Calculated cases concentrate on municipal solid waste treatment in the Finnish operational environment. The chosen methodology to approach the objectives is techno-economic feasibility assessment. It combines calculation methods of literature and practical engineering to define the material and energy balances in chosen scenarios. The calculation results together with other operational and financial data can be concluded to net present values compared between the scenarios. For the comparison, four scenarios, most vital and alternative between each other, are established. The baseline scenario is grate firing of source separated mixed municipal solid waste. Second scenario is fluidized bed combustion of solid recovered fuel produced in mechanical treatment process with metal separation. Third scenario combines a biomaterial separation process to the solid recovered fuels preparation and in the last scenario plastics are separated in addition to the previous operations. The results indicated that the mechanical treatment scenarios still need to overcome some problems to become feasible. Problems are related to profitability, residue disposal and technical reliability. Many uncertainties are also related to the data gathered over waste characteristics, technical performance and markets. With legislative support and development of further processing technologies and markets of the recycled materials the scenarios with biomaterial and plastic separation may operate feasibly in the future.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

A Reading of the conception of man in Hans Jonas’ works: Between Nature and Responsibility. An Environmental Ethics Approach

Hans Jonas is considered one of the principal leaders of the ecological doctrine that fights against the hegemony of technical power upon society. We will study the conception of man in Jonas’ ideology through the lens of nature and of responsibility. He brandishes the specter of disaster (“heuristics of fear”) as a guard against technological excesses. He appeals to a prospective, universal and categorical responsibility to protect nature and to save future generations. Jonas considers responsibility as a method of anticipating the threat to that which is vulnerable, ephemeral, and perishable. Thus, the responsibility that Jonas decrees implies an ethics of conservation. Jonas’ writings aim to procure a new dimension of acting, which necessitates an ethics of foresight and responsibility.

Alternatives de partenariats pour la gestion de l’eau potable dans les quartiers pauvres des zones urbaines : cas de Kinshasa

Face à l’incapacité de l’État à offrir des services de base aux ménages pauvres des zones urbaines périphériques et marginales, ce sont les opérateurs informels (individuels et collectifs) qui s’activent à répondre aujourd’hui aux besoins croissants des ménages. Mais leurs actions sont ponctuelles, éparpillées sur le territoire, non intégrées dans un plan de développement local, et beaucoup de ménages n’ont toujours pas accès à l’eau potable. Cette recherche, de type exploratoire, porte donc sur l’examen d’un type de partenariat entre les acteurs publics et les opérateurs informels collectifs, susceptible de créer la synergie entre les partenaires locaux et de pérenniser la fourniture de l’eau potable. Elle vise à analyser et à comprendre les mécanismes de collaboration entre l’État et les opérateurs informels collectifs en vue d’améliorer la qualité de la vie dans les quartiers urbains pauvres grâce à la résolution des problèmes d’accès à l’eau potable. À partir de l’étude de cas d’une zone pauvre de la ville de Kinshasa (République Démocratique du Congo), nous avons donc cherché à dégager ce qui peut éclairer le fonctionnement du partenariat État-opérateurs informels collectifs. Comme cadre d’analyse, nous avons recouru à l’analyse stratégique et, pour l’examen des expériences de partenariat, nous avons utilisé le modèle de Coston (1998) et recouru aux approches de régulation État-tiers secteur (approche socio-étatique et approche socio-communautaire). La méthode qualitative a été privilégiée. Les données analysées proviennent d’entrevues semi-dirigées, de la recherche documentaire et de l’observation. À partir du modèle de Coston (1998), les résultats obtenus montrent que les relations qui correspondent le mieux au partenariat entre les acteurs publics et les opérateurs informels collectifs sont de type « contractuel » et correspondent à l’orientation socio-étatique. Mais le système formel actuel de gestion de l’eau potable et les relations de pouvoir sont plus proches du type « rivalité ». Notre étude montre également que les partenariats, entre les acteurs publics et les opérateurs informels collectifs, sont très difficiles à instituer, car il n’existe pas encore d’environnement socio-politique solidaire. Le contexte institutionnel n’est pas propice à l’émergence d’un partenariat dynamique. Les déficiences structurelles, humaines et institutionnelles constatées sont la résultante directe de la pauvreté dont sont victimes les individus et les institutions. Les réseaux sociaux (à base de parenté, ethnique ou religieux) affectent les relations entre les individus, membres d’une association locale et les représentants des institutions locales ou nationales. Une complémentarité, négociée entre l’État et les opérateurs informels collectifs, ne pourra se réaliser que par la mise en place de nouvelles politiques favorisant la démocratie, la décentralisation et la promotion du mouvement associatif avec une société civile forte, dynamique, soucieuse du bien commun, privilégiant les qualités managériales plutôt que l’assistance perpétuelle.