Structural and operational optimisation : applications in energy systems

In this work mathematical programming models for structural and operational optimisation of energy systems are developed and applied to a selection of energy technology problems. The studied cases are taken from industrial processes and from large regional energy distribution systems. The models are based on Mixed Integer Linear Programming (MILP), Mixed Integer Non-Linear Programming (MINLP) and on a hybrid approach of a combination of Non-Linear Programming (NLP) and Genetic Algorithms (GA). The optimisation of the structure and operation of energy systems in urban regions is treated in the work. Firstly, distributed energy systems (DES) with different energy conversion units and annual variations of consumer heating and electricity demands are considered. Secondly, district cooling systems (DCS) with cooling demands for a large number of consumers are studied, with respect to a long term planning perspective regarding to given predictions of the consumer cooling demand development in a region. The work comprises also the development of applications for heat recovery systems (HRS), where paper machine dryer section HRS is taken as an illustrative example. The heat sources in these systems are moist air streams. Models are developed for different types of equipment price functions. The approach is based on partitioning of the overall temperature range of the system into a number of temperature intervals in order to take into account the strong nonlinearities due to condensation in the heat recovery exchangers. The influence of parameter variations on the solutions of heat recovery systems is analysed firstly by varying cost factors and secondly by varying process parameters. Point-optimal solutions by a fixed parameter approach are compared to robust solutions with given parameter variation ranges. In the work enhanced utilisation of excess heat in heat recovery systems with impingement drying, electricity generation with low grade excess heat and the use of absorption heat transformers to elevate a stream temperature above the excess heat temperature are also studied.

Strategic Innovation Management Based on Three Dimensions

This thesis examines innovation development needs of firms in a remote rural region. The perspective of the study is in strategic innovation management and three dimensions of innovation development: innovation environment, value delivery and innovation capability. The framework is studied with a theoretical and methodological approach in the context of the development of a regional innovation system and the defining of innovation development needs. The thesis is based on existing innovation management literature, expanding it by examining the features of the three dimensions. The empirical data of the study comprise 50 purposefully selected firms within the region of Pielinen Karelia located in Eastern Finland. Most of the firms (70%) included in the study represent manufacturing firms, and over 90% are small and medium-sized enterprises. The research data consist of two questionnaires and an interview, which were done during 2011 in the connection of a regional development project. The point of view of the research is in regional development and harnessing the innovation capability of the firms within the region. The principal research approach applies soft systems methodology. The study explores the means to foster the innovativeness of firms from the viewpoints of innovation environment, innovation capability and value delivery. In closer detail, the study examines relations between the innovation capability factors, differences in innovation development needs within the value delivery system, between sectors and between firm size categories. The thesis offers three major contributions. First, the study extends earlier research on strategic innovation management by connecting the frameworks of innovation capability, innovation environment and value delivery process to the defining of innovation development needs at the regional level. The results deepen knowledge especially concerning practice-based innovation, peripheral regions and smaller firms. Second, the empirical work, based on a case study, confirms the existence of a structural connection integrating five factors of innovation capability. Statistical evidence is provided especially for the positive impacts of the improvement of absorption capability, marketing capability and networking capability, which are the main weaknesses of firms according to the study. Third, the research provides a methodological contribution by applying the innovation matrix in the defining of the innovation development needs of firms. The study demonstrates how the matrix improves possibility to target policy instruments and innovation services more efficiently through indicating significant differences between the innovation support needs regarding various time horizons and phases of innovation process.

Deregulation’s Impact on the Railway Freight Transport Sector’s Future in the Baltic Sea Region

The European transport market has confronted several changes during the last decade. Due to European Union legislative mandates, the railway freight market was deregulated in 2007. The market followed the trend started by other transport modes as well as other previously regulated industries such as banking, telecommunications and energy. Globally, the first country to deregulate the railway freight market was the United States, with the introduction of the Staggers Rail Act in 1980. Some European countries decided to follow suit already before regulation was mandated; among the forerunners were the United Kingdom, Sweden and Germany. The previous research has concentrated only on these countries, which has provided an interesting research gap for this thesis. The Baltic Sea Region consists of countries with different kinds of liberalization paths, including Sweden and Germany, which have been on the frontline, whereas Lithuania and Finland have only one active railway undertaking, the incumbent. The transport market of the European Union is facing further challenges in the near future, due to the Sulphur Directive, oil dependency and the changing structure of European rail networks. In order to improve the accessibility of this peripheral area, further action is required. This research focuses on topics such as the progression of deregulation, barriers to entry, country-specific features, cooperation and internationalization. Based on the research results, it can be stated that the Baltic Sea Region’s railway freight market is expected to change in the future. Further private railway undertakings are anticipated, and these would change the market structure. The realization of European Union’s plans to increase the improved rail network to cover the Baltic States is strongly hoped for, and railway freight market counterparts inside and among countries are starting to enhance their level of cooperation. The Baltic Sea Region countries have several special national characteristics which influence the market and should be taken into account when companies evaluate possible market entry actions. According to thesis interviews, the Swedish market has a strong level of cooperation in the form of an old-boy network, and is supported by a positive attitude of the incumbent towards the private railway undertakings. This has facilitated the entry process of newcomers, and currently the market has numerous operating railway undertakings. A contrary example was found from Poland, where the incumbent sent old rolling stock to the scrap yard rather than sell it to private railway undertakings. The importance of personal relations is highlighted in Russia, followed by the railway market’s strong political bond with politics. Nonetheless, some barriers to entry are shared by the Baltic Sea Region, the main ones being acquisition of rolling stock, bureaucracy and needed investments. The railway freight market is internationalizing, which is perceived via several alliances as well as the increased number of mergers and acquisitions. After deregulation, markets seem to increase the number of railway undertakings at a rather fast pace, but with the passage of time, the larger operators tend to acquire smaller ones. Therefore, it is expected that in a decade’s time, the number of railway undertakings will start to decrease in the deregulation pioneer countries, while the ones coming from behind might still experience an increase. The Russian market is expected to be totally liberalized, and further alliances between the Russian Railways and European railway undertakings are expected to occur. The Baltic Sea Region’s railway freight market is anticipated to improve, and, based on the interviewees’ comments, attract more cargoes from road to rail.

Fluorescence-based imaging of cellular defect in lysinuric protein intolerance (LPI)

Fluoresenssiperusteiset kuvantamismenetelmät lysinurisen proteiini-intoleranssin (LPI) soluhäiriön tutkimuksessa Lysinurinen proteiini-intoleranssi on suomalaiseen tautiperintöön kuuluva autosomaalisesti peit¬tyvästi periytyvä sairaus, jonka aiheuttaa kationisten aminohappojen kuljetushäiriö munuaisten ja ohutsuolen epiteelisolujen basolateraalikalvolla. Aminohappojen kuljetushäiriö johtaa moniin oirei¬siin, kuten kasvuhäiriöön, osteoporoosiin, immuunijärjestelmän häiriöihin, oksenteluun ja runsaspro¬teiinisen ravinnon nauttimisen jälkeiseen hyperammonemiaan. LPI-geeni SLC7A7 (solute carrier family 7 member 7) koodaa y+LAT1 proteiinia, joka on basolateraali¬nen kationisten ja neutraalien aminohappojen kuljettimen kevyt ketju, joka muodostaa heterodimee¬rin raskaan alayksikön 4F2hc:n kanssa. Tällä hetkellä SLC7A7-geenistä tunnetaan yli 50 LPI:n aiheut¬tavaa mutaatiota. Tässä tutkimuksessa erityyppisiä y+LAT1:n LPI-mutaatiota sekä yhdeksän C-terminaalista polypep¬tidiä lyhentävää deleetiota kuvannettiin nisäkässoluissa y+LAT1:n GFP (green fluorescent protein) -fuusioproteiineina. Tulokset vahvistivat muissa soluissa tehdyt havainnot siitä, että 4F2hc on edel¬lytyksenä y+LAT1:n solukalvokuljetukselle, G54V-pistemutantti sijaitsee solukalvolla samoin kuin vil¬lityyppinen proteiini, mutta lukukehystä muuttavia ja proteiinia lyhentäviä mutantteja ei kuljeteta solukalvoon. Lisäksi havaittiin, että poikkeuksena tästä säännöstä ovat y+LAT1-deleetioproteiinit, joista puuttui korkeintaan 50 C-terminaalista aminohappoa. Nämä lyhentyneet kuljettimet sijaitsevat solukalvolla kuten villityyppiset ja LPI-pistemutanttiproteiinit. Dimerisaation osuutta kuljetushäiriön synnyssä tutkittiin käyttämällä fluorescence resonance energy transfer (FRET) menetelmää. Heterodimeerin alayksiköistä kloonattiin ECFP (cyan) ja EYFP (yellow) fuusioproteiinit, joita ilmennettiin nisäkässoluissa, ja FRET mitattiin virtaussytometri-FRET -menetel¬mällä (FACS-FRET). Tutkimuksissa kaikkien mutanttien havaittiin dimerisoituvan yhtä tehokkaasti. Kul¬jetushäiriön syynä ei siten ole alayksiköiden dimerisaation estyminen mutaation seurauksena. Tutkimuksessa havaittiin, että kaikki mutantti-y+LAT1-transfektiot tuottavat vähemmän transfektoi¬tuneita soluja kuin villityyppisen y+LAT1:n transfektiot. Solupopulaatioissa, joihin oli tranfektoitu lu¬kukehystä muuttava tai stop-kodonin tuottava mutaatio havaittiin suurempi kuolleisuus kuin saman näytteen transfektoitumattomissa soluissa, kun taas villityyppistä tai G54V-pistemutanttia tuottavas¬sa solupopulaatiossa oli pienempi kuolleisuus kuin saman näytteen fuusioproteiinia ilmentämättö¬missä soluissa. Tulos osoittaa mutanttiproteiinien erilaiset vaikutukset niitä ilmentäviin soluihin, joko suoraan y+LAT1:n tai 4F2hc:n kautta aiheutuneina. LPIFin SLC7A7 lähetti-RNA:n määrä ei merkittävästi poikennut villityyppisen määrästä fibroblasteissa ja lymfoblasteissa. SLC7A7:n promoottorianalyysissä oli osoitettavissa säätelyalueita geenin 5’ ei-koo¬daavalla alueella sekä ensimmäisten kahden intronin alueella. LPI-taudin tautimekanismin kannalta keskeisin tekijä on kuitenkin aminohappokuljetuksen häiriö, jonka vaikutuksesta näistä aminohapoista riippuvaiset prosessit elimistössä eivät toimi normaalisti. Havaittu virheellinen y+LAT1/4F2hc kuljetuskompleksin sijainti edellyttää lisätutkimuksia sen mahdol¬lisen kliinisen merkityksen selvittämiseksi.

Scenario-based traffic forecasts for the routes between the PENTA ports in 2020

Maritime transport is the foundation for trade in the Baltic Sea area. It represents over 15% of the world’s cargo traffic and it is predicted to increase by over 100% in the future. There are currently over 2,000 ships sailing on the Baltic Sea and both the number and the size of ships have been growing in recent years. Due to the importance of maritime traffic in the Baltic Sea Region, ports have to be ready to face future challenges and adapt to the changing operational environment. The companies within the transportation industry – in this context ports, shipowners and logistics companies – compete continuously and although the number of companies in the business is not particularly substantial because the products offered are very similar, other motives for managing the supply chain arise. The factors creating competitive advantage are often financial and related to cost efficiency, but geographical location, road infrastructure in the hinterland and vessel connections are among the most important factors. The PENTA project focuses on adding openness, transparency and sharing knowledge and information, so that the challenges of the future can be better addressed with regard to cooperation. This report presents three scenario-based traffic forecasts for routes between the PENTA ports in 2020. The chosen methodology is PESTE, in which the focus in on economic factors affecting future traffic flows. The report further analyses the findings and results of the first PENTA WP2 report “Drivers of demand in cargo and passenger traffic between PENTA ports” and utilises the same material, which was obtained through interviews and mail surveys.

Comparison between dSPACE and NI systems based on real-time intelligent control of a teleoperated hydraulic servo system

The Laboratory of Intelligent Machine researches and develops energy-efficient power transmissions and automation for mobile construction machines and industrial processes. The laboratory's particular areas of expertise include mechatronic machine design using virtual technologies and simulators and demanding industrial robotics. The laboratory has collaborated extensively with industrial actors and it has participated in significant international research projects, particularly in the field of robotics. For years, dSPACE tools were the lonely hardware which was used in the lab to develop different control algorithms in real-time. dSPACE's hardware systems are in widespread use in the automotive industry and are also employed in drives, aerospace, and industrial automation. But new competitors are developing new sophisticated systems and their features convinced the laboratory to test new products. One of these competitors is National Instrument (NI). In order to get to know the specifications and capabilities of NI tools, an agreement was made to test a NI evolutionary system. This system is used to control a 1-D hydraulic slider. The objective of this research project is to develop a control scheme for the teleoperation of a hydraulically driven manipulator, and to implement a control algorithm between human and machine interaction, and machine and task environment interaction both on NI and dSPACE systems simultaneously and to compare the results.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.

Improving Cost-Efficiency and Reducing Environmental Impacts of Intermodal Transportation with Dry Port Concept – Major Rail Transport Corridor in Baltic Sea Region

Transportation plays a major role in the gross domestic product of various nations. There are, however, many obstacles hindering the transportation sector. Cost-efficiency along with proper delivery times, high frequency and reliability are not a straightforward task. Furthermore, environmental friendliness has increased the importance of the whole transportation sector. This development will change roles inside the transportation sector. Even now, but especially in the future, decisions regarding the transportation sector will be partly based on emission levels and other externalities originating from transportation in addition to pure transportation costs. There are different factors, which could have an impact on the transportation sector. IMO’s sulphur regulation is estimated to increase the costs of short sea shipping in the Baltic Sea. Price development of energy could change the roles of different transport modes. Higher awareness of the environmental impacts originating from transportation could also have an impact on the price level of more polluting transport modes. According to earlier research, increased inland transportation, modal shift and slowsteaming can be possible results of these changes in the transportation sector. Possible changes in the transportation sector and ways to settle potential obstacles are studied in this dissertation. Furthermore, means to improve cost-efficiency and to decrease environmental impacts originating from transportation are researched. Hypothetical Finnish dry port network and Rail Baltica transport corridor are studied in this dissertation. Benefits and disadvantages are studied with different methodologies. These include gravitational models, which were optimized with linear integer programming, discrete-event and system dynamics simulation, an interview study and a case study. Geographical focus is on the Baltic Sea Region, but the results can be adapted to other geographical locations with discretion. Results indicate that the dry port concept has benefits, but optimization regarding the location and the amount of dry ports plays an important role. In addition, the utilization of dry ports for freight transportation should be carefully operated, since only a certain amount of total freight volume can be cost-efficiently transported through dry ports. If dry ports are created and located without proper planning, they could actually increase transportation costs and delivery times of the whole transportation system. With an optimized dry port network, transportation costs can be lowered in Finland with three to five dry ports. Environmental impacts can be lowered with up to nine dry ports. If more dry ports are added to the system, the benefits become very minor, i.e. payback time of investments becomes extremely long. Furthermore, dry port network could support major transport corridors such as Rail Baltica. Based on an analysis of statistics and interview study, there could be enough freight volume available for Rail Baltica, especially, if North-West Russia is part of the Northern end of the corridor. Transit traffic to and from Russia (especially through the Baltic States) plays a large role. It could be possible to increase transit traffic through Finland by connecting the potential Finnish dry port network and the studied transport corridor. Additionally, sulphur emission regulation is assumed to increase the attractiveness of Rail Baltica in the year 2015. Part of the transit traffic could be rerouted along Rail Baltica instead of the Baltic Sea, since the price level of sea transport could increase due to the sulphur regulation. Both, the hypothetical Finnish dry port network and Rail Baltica transport corridor could benefit each other. The dry port network could gain more market share from Russia, but also from Central Europe, which is the other end of Rail Baltica. In addition, further Eastern countries could also be connected to achieve higher potential freight volume by rail.

Efficient Algorithms for Coastal Geographic Problems

The increasing performance of computers has made it possible to solve algorithmically problems for which manual and possibly inaccurate methods have been previously used. Nevertheless, one must still pay attention to the performance of an algorithm if huge datasets are used or if the problem iscomputationally difficult. Two geographic problems are studied in the articles included in this thesis. In the first problem the goal is to determine distances from points, called study points, to shorelines in predefined directions. Together with other in-formation, mainly related to wind, these distances can be used to estimate wave exposure at different areas. In the second problem the input consists of a set of sites where water quality observations have been made and of the results of the measurements at the different sites. The goal is to select a subset of the observational sites in such a manner that water quality is still measured in a sufficient accuracy when monitoring at the other sites is stopped to reduce economic cost. Most of the thesis concentrates on the first problem, known as the fetch length problem. The main challenge is that the two-dimensional map is represented as a set of polygons with millions of vertices in total and the distances may also be computed for millions of study points in several directions. Efficient algorithms are developed for the problem, one of them approximate and the others exact except for rounding errors. The solutions also differ in that three of them are targeted for serial operation or for a small number of CPU cores whereas one, together with its further developments, is suitable also for parallel machines such as GPUs.

Opportunity meets uncertainty. Towards sustainable business in the Arctic region

The Arctic region is experiencing a significant change in terms of climate change and a growing economic interest towards its natural resources and emerging business opportunities. The purpose of this study is to explore how can Finnish companies create sustainable business in the Arctic. This is done by examining the arctic business environment, identifying sectors with growth potential, addressing challenges related to operating in the Arctic and suggesting how to ensure sustainability and succeed in the globally competed arctic market. The theoretical framework is based on theories of sustainable development, corporate social responsibility and the role of strategy in creating sustainable business. Empirical data was collected by using qualitative research methods: first, background knowledge was formed based on written documents and, secondly, six expert interviews were conducted in early 2014. The interviewees represented the viewpoints of companies, political decision makers and NGO’s. The analysis of the data was conducted using thematic categorization. The empirical findings of the study suggest that in order to create sustainable business in the Arctic companies should adopt a long-term perspective, embrace a holistic approach to sustainability, understand interdependencies between the dimensions of sustainability and aim at high-level engagement in responsible behavior. To succeed in the arctic market core competencies, customer needs, multivendor cooperation and long-term presence need to be invested in on a company level. In addition, to promote and advance arctic development on a national level support is needed in terms of investments in infrastructure, funding research and design, creating a regulative framework and removing barriers of trade.