Vaasan kaukolämmön kehittämissuunnitelma

Tämän työn tarkoituksena on tarkastella tulevaisuuden kehitysnäkymien vaikutusta Vaasan kaukolämpötoimintaan. Komartekin Flowra 32 verkostolaskentaohjelman avulla tutkitaan kaukolämpöverkon siirtokykyä nykyisissä ja tulevaisuuden kuormitustilanteissa. Työn yhteydessä laaditaan kaukolämmityksen kasvuennuste seuraavalle kymmenelle vuodelle ja selvitetään mitoituslämpötilaa -29°C vastaava teho tilastollisen analyysin avulla. Lisäksi tutkitaan mahdollisia ratkaisuja huippu- ja varatehon tuottamiseksi. Tarkastelun kohteena on myös lämmön lyhytaikaisvarastoinnin kannattavuus energianhankintajärjestelmässä. Kaukolämpöverkon siirtokyky on tarkastelun perusteella kohtalaisen hyvä, mutta liittymistehojen kasvaessa paine-erot verkon häntäpäässä jäävät liian alhaisiksi. Paras ratkaisu paine-ero ongelmaan on rakentaa välipumppaamo Hovioikeudenpuistoon. Tarkastelun perusteella kaukolämmön varatehon lisätarve on kymmenen vuoden kuluttua noin 40 MW ja varatehoksi on kannattavinta rakentaa raskasta polttoöljyä käyttävä lämpökeskus. Lämmön lyhytaikaisvarastointi on nykyisillä energianhinnoilla kohtalaisen kannattavaa varsinkin, jos Kauppa- ja teollisuusministeriö myöntää hankkeelle täyden 30%:n investointiavustuksen.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Assessment of meshing techniques for fatigue analysis of load carrying welded joints using the effective notch approach

The effective notch stress approach for the fatigue strength assessment of welded structures as included in the Fatigue Design Recommendation of the IIW requires the numerical analysis of the elastic notch stress in the weld toe and weld root which is fictitiously rounded with a radius of 1mm. The goal of this thesis work was to consider alternate meshing strategies when using the effective notch stress approach to assess the fatigue strength of load carrying partial penetration fillet-welded cruciform joints. In order to establish guidelines for modeling the joint and evaluating the results, various two-dimensional (2D) finite element analyses were carried out by systematically varying the thickness of the plates, the weld throat thickness, the degree of bending, and the shape and location of the modeled effective notch. To extend the scope of this work, studies were also carried out on the influence of

Quantitative market and sales forecast accuracy analysis

The main objective of this master’s thesis was to quantitatively study the reliability of market and sales forecasts of a certain company by measuring bias, precision and accuracy of these forecasts by comparing forecasts against actual values. Secondly, the differences of bias, precision and accuracy between markets were explained by various macroeconomic variables and market characteristics. Accuracy and precision of the forecasts seems to vary significantly depending on the market that is being forecasted, the variable that is being forecasted, the estimation period, the length of the estimated period, the forecast horizon and the granularity of the data. High inflation, low income level and high year-on-year market volatility seems to be related with higher annual market forecast uncertainty and high year-on-year sales volatility with higher sales forecast uncertainty. When quarterly market size is forecasted, correlation between macroeconomic variables and forecast errors reduces. Uncertainty of the sales forecasts cannot be explained with macroeconomic variables. Longer forecasts are more uncertain, shorter estimated period leads to higher uncertainty, and usually more recent market forecasts are less uncertain. Sales forecasts seem to be more uncertain than market forecasts, because they incorporate both market size and market share risks. When lead time is more than one year, forecast risk seems to grow as a function of root forecast horizon. When lead time is less than year, sequential error terms are typically correlated, and therefore forecast errors are trending or mean-reverting. The bias of forecasts seems to change in cycles, and therefore the future forecasts cannot be systematically adjusted with it. The MASE cannot be used to measure whether the forecast can anticipate year-on-year volatility. Instead, we constructed a new relative accuracy measure to cope with this particular situation.

Calculation of the critical crack size for cold form rectangular hollow section tube (CRHS) under bending load at -40º C temperature

To predict the capacity of the structure or the point which is followed by instability, calculation of the critical crack size is important. Structures usually contain several cracks but not necessarily all of these cracks lead to failure or reach the critical size. So, defining the harmful cracks or the crack size which is the most leading one to failure provides criteria for structure’s capacity at elevated temperature. The scope of this thesis was to calculate fracture parameters like stress intensity factor, the J integral and plastic and ultimate capacity of the structure to estimate critical crack size for this specific structure. Several three dimensional (3D) simulations using finite element method by Ansys program and boundary element method by Frank 3D program were carried out to calculate fracture parameters and results with the aid of laboratory tests (loaddisplacement curve, the J resistance curve and yield or ultimate stress) leaded to extract critical size of the crack. Two types of the fracture which is usually affected by temperature, Elastic and Elasti-Plastic fractures were simulated by performing several linear elastic and nonlinear elastic analyses. Geometry details of the weldment; flank angle and toe radius were also studied independently to estimate the location of crack initiation and simulate stress field in early stages of crack extension in structure. In this work also overview of the structure’s capacity in room temperature (20 ºC) was studied. Comparison of the results in different temperature (20 ºC and -40 ºC) provides a threshold of the structure’s behavior within the defined range.

Russia, China, India Foresight for Small and Medium size Enterprises in Uusimaa : Changes forecast in the Russian, Chinese and Indian operating environments from the viewpoint of small and middle-sized enterprises in Uusimaa

The report describes those factors of the future that are related to the growth and needs of Russia, China, and India and that may provide significant internationalisation potential for Uusimaa companies. The report examines the emerging trends and market-entry challenges for each country separately. Additionally, it evaluates the training needs of Uusimaa companies in terms of the current offerings available for education on topics related to Russia, China, and India. The report was created via the Delphi method: experts were interviewed, and both Trendwiki material and the latest literature were used to create a summary of experts’ views, statements, and reasons behind recent developments. This summary of views was sent back to the experts with the objective of reaching consensus synthesising the differing views or, at least, of providing argumentation for the various alternative lines of development. In addition to a number of outside experts and business leaders, all heads of Finpro’s Finland Trade Centers participated in the initial interviews. The summary was commented upon by all Finpro consultants and analysts for Russia, China, and India, with each focusing on his or her own area of expertise. The literature used consisted of reports, listed for each country, and an extensive selection of the most recent newspaper articles. The report was created in January-April 2010. On 22 April 2010 its results were reviewed at the final report presentation in cooperation with the Uusimaa ELY Centre.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

Characteristic Approach to Predicting Analysts’ Forecast Errors in the Finnish Market

Extensive literature shows that analysts’ forecasts and recommendations are often biased. Thus, it is important for the financial market to be able to recognize this bias to be able to correctly valuate public companies. This thesis uses characteristic approach, which was introduced by So (2013, pp. 615-640), to forecast analysts’ forecast errors and tests if predictable forecast error is fully incorporated into share prices. Data is collected of listed Finnish companies. Thesis’ timeframe spans over ten years from 2004 to 2013 consisting of 788 firm-years. Although there is earlier evidence that the characteristic approach is able to predict analysts’ forecast errors, no support for this is found in the Finnish market. This thesis contributes to the current knowledge by showing that the characteristic approach does not work universally as such but requires development to work especially in the smaller markets.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Load balancing in P2P smartphone based distributed IoT systems

With the new age of Internet of Things (IoT), object of everyday such as mobile smart devices start to be equipped with cheap sensors and low energy wireless communication capability. Nowadays mobile smart devices (phones, tablets) have become an ubiquitous device with everyone having access to at least one device. There is an opportunity to build innovative applications and services by exploiting these devices’ untapped rechargeable energy, sensing and processing capabilities. In this thesis, we propose, develop, implement and evaluate LoadIoT a peer-to-peer load balancing scheme that can distribute tasks among plethora of mobile smart devices in the IoT world. We develop and demonstrate an android-based proof of concept load-balancing application. We also present a model of the system which is used to validate the efficiency of the load balancing approach under varying application scenarios. Load balancing concepts can be apply to IoT scenario linked to smart devices. It is able to reduce the traffic send to the Cloud and the energy consumption of the devices. The data acquired from the experimental outcomes enable us to determine the feasibility and cost-effectiveness of a load balanced P2P smart phone-based applications.

The Forecast Performance of Model-Free Implied Volatility: Evidence from DAX Index Options

Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.

Hävittäjäohjaajan kognitiivisen kuormituksen tason mittaaminen NASA-Task Load Index ja Modified Cooper-Harper -mittareilla F/A-18 virtuaalisimulaattorissa

F/A-18-monitoimihävittäjän ohjaajan tehtävän kognitiiviset vaatimukset ovat korkeat. Kognitiivisen kuormituksen taso vaikuttaa hävittäjäohjaajan suoritustasoon ja subjektiivisiin tun-temuksiin. Yerkesin ja Dodsonin periaatteen mukaisesti erittäin matala tai erittäin korkea kuormituksen taso laskee suoritustasoa. Optimaalinen kuormituksen taso ja suoritustaso saa-vutetaan jossain ääripäiden välillä. Hävittäjäohjaajan kognitiivisen kuormituksen tasoon vaikuttaa lentotehtävän suorittamiseen vaadittava henkinen ponnistelu. Vaadittavan ponnistelun taso riippuu tehtävien vaatimustasosta ja määrästä, tehtäviin käytettävissä olevasta ajasta sekä yksilöllisistä ominaisuuksista. Tutkimuksessa mitattiin kognitiivisen kuormituksen tasoa subjektiivisen arvioinnin menetelmällä NASA-TLX (National Aeronautics and Space Administration - Task Load Index) ja MCH (Modified Cooper-Harper) -mittareilla. Tutkimuksessa selvitettiin mittareiden havaintoarvojen muutosta, sensitiivisyyttä ja yhdenmukaisuutta kognitiivisen kuormituksen tason muuttuessa. Tutkimuksen mittauksiin osallistui 35 Suomen ilmavoimien aktiivisessa palveluksessa olevaa F/A-18-monitoimihävittäjäohjaajaa. Koehenkilöiden lentotuntien keskiarvo F/A-18-monitoimihävittäjällä oli 598 tuntia ja keskihajonta 445 tuntia. Koehenkilöiden tehtävänä oli lentää F/A-18-virtuaalisimulaattorilla 11 ILS (Instrument Landing System) -mittarilähestymistä eri aloitusetäisyyksiltä kiitotien kynnyksestä. Kognitiivisesti kuormitta-van mittarilähestymistehtävän aikana kuormituksen tasoa nostettiin lisätehtävillä ja vähentä-mällä tehtäviin käytettävissä olevaa aikaa. Koehenkilöitä pyydettiin ponnistelemaan mahdollisimman paljon tehtävien suorittamisen aikana hyvän suoritustason ylläpitämiseksi. Tulosten perusteella mittareiden havaintoarvot muuttuivat kognitiivisen kuormituksen tason muuttuessa. Käytettävissä olevan ajan vaikutus kognitiivisen kuormituksen tasoon oli tilastollisesti erittäin merkitsevä. Mittarit olivat sensitiivisiä kognitiivisen kuormituksen tason muutokselle ja antoivat yhdenmukaisia havaintoarvoja.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.