54 resultados para ENERGY SYSTEMS


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One of the targets of the climate and energy package of the European Union is to increase the energy efficiency in order to achieve a 20 percent reduction in primary energy use compared with the projected level by 2020. The energy efficiency can be improved for example by increasing the rotational speed of large electrical drives, because this enables the elimination of gearboxes leading to a compact design with lower losses. The rotational speeds of traditional bearings, such as roller bearings, are limited by mechanical friction. Active magnetic bearings (AMBs), on the other hand, allow very high rotational speeds. Consequently, their use in large medium- and high-speed machines has rapidly increased. An active magnetic bearing rotor system is an inherently unstable, nonlinear multiple-input, multiple-output system. Model-based controller design of AMBs requires an accurate system model. Finite element modeling (FEM) together with the experimental modal analysis provides a very accurate model for the rotor, and a linearized model of the magneticactuators has proven to work well in normal conditions. However, the overall system may suffer from unmodeled dynamics, such as dynamics of foundation or shrink fits. This dynamics can be modeled by system identification. System identification can also be used for on-line diagnostics. In this study, broadband excitation signals are adopted to the identification of an active magnetic bearing rotor system. The broadband excitation enables faster frequency response function measurements when compared with the widely used stepped sine and swept sine excitations. Different broadband excitations are reviewed, and the random phase multisine excitation is chosen for further study. The measurement times using the multisine excitation and the stepped sine excitation are compared. An excitation signal design with an analysis of the harmonics produced by the nonlinear system is presented. The suitability of different frequency response function estimators for an AMB rotor system are also compared. Additionally, analytical modeling of an AMB rotor system, obtaining a parametric model from the nonparametric frequency response functions, and model updating are discussed in brief, as they are key elements in the modeling for a control design. Theoretical methods are tested with a laboratory test rig. The results conclude that an appropriately designed random phase multisine excitation is suitable for the identification of AMB rotor systems.

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Approximately a quarter of electrical power consumption in pulp and paper industry is used in different pumping systems. Therefore, improving pumping system efficiency is a considerable way to reduce energy consumption in different processes. Pumping of wood pulp in different consistencies is common in pulp and paper industry. Earlier, centrifugal pumps were used to pump pulp only at low consistencies, but development of MC technology has made it possible to pump medium consistency pulp. Pulp is a non-Newtonian fluid, which flow characteristics are significantly different than what of water. In this thesis is examined the energy efficiency of pumping medium consistency pulp with centrifugal pump. The factors effecting the pumping of MC pulp are presented and through case study is examined the energy efficiency of pumping in practice. With data obtained from the case study are evaluated the effects of pump rotational speed and pulp consistency on energy efficiency. Additionally, losses caused by control valve and validity of affinity laws in pulp pumping are evaluated. The results of this study can be used for demonstrating the energy consumption of MC pumping processes and finding ways to improve energy efficiency in these processes.

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Cyanobacteria are a diverse group of oxygenic photosynthetic bacteria that inhabit in a wide range of environments. They are versatile and multifaceted organisms with great possibilities for different biotechnological applications. For example, cyanobacteria produce molecular hydrogen (H2), which is one of the most important alternatives for clean and sustainable energy. Apart from being beneficial, cyanobacteria also possess harmful characteristics and may become a source of threat to human health and other living organisms, as they are able to form surface blooms that are producing a variety of toxic or bioactive compounds. The University of Helsinki Culture Collection (UHCC) maintains around 1,000 cyanobacterial strains representing a large number of genera and species isolated from the Baltic Sea and Finnish lakes. The culture collection covers different life forms such as unicellular and filamentous, N2-fixing and non-N2-fixing strains, and planktonic and benthic cyanobacteria. In this thesis, the UHCC has been screened to identify potential strains for sustainable biohydrogen production and also for strains that produce compounds modifying the bioenergetic pathways of other cyanobacteria or terrestrial plants. Among the 400 cyanobacterial strains screened so far, ten were identified as high H2-producing strains. The enzyme systems involved in H2 metabolism of cyanobacteria were analyzed using the Southern hybridization approach. This revealed the presence of the enzyme nitrogenase in all strains tested, while none of them are likely to have contained alternative nitrogenases. All the strains tested, except for two Calothrix strains, XSPORK 36C and XSPORK 11A, were suggested to contain both uptake and bidirectional hydrogenases. Moreover, 55 methanol extracts of various cyanobacterial strains were screened to identify potent bioactive compounds affecting the photosynthetic apparatus of the model cyanobacterium, Synechocystis PCC 6803. The extract from Nostoc XPORK 14A was the only one that modified the photosynthetic machinery and dark respiration. The compound responsible for this effect was identified, purified, and named M22. M22 demonstrated a dual-action mechanism: production of reactive oxygen species (ROS) under illumination and an unknown mechanism that also prevailed in the dark. During summer, the Baltic Sea is occupied by toxic blooms of Nodularia spumigena (hereafter referred to as N. spumigena), which produces a hepatotoxin called nodularin. Long-term exposure of the terrestrial plant spinach to nodularin was studied. Such treatment resulted in inhibition of growth and chlorosis of the leaves. Moreover, the activity and amount of mitochondrial electron transfer complexes increased in the leaves exposed to nodularin-containing extract, indicating upregulation of respiratory reactions, whereas no marked changes were detected in the structure or function of the photosynthetic machinery. Nodularin-exposed plants suffered from oxidative stress, evidenced by oxidative modifications of various proteins. Plants initiated strategies to combat the stress by increasing the levels of alpha-tocopherol, mitochondrial alternative oxidase (AOX), and mitochondrial ascorbate peroxidase (mAPX).

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In this thesis a control system for an intelligent low voltage energy grid is presented, focusing on the control system created by using a multi-agent approach which makes it versatile and easy to expand according to the future needs. The control system is capable of forecasting the future energy consumption and decisions making on its own without human interaction when countering problems. The control system is a part of the St. Petersburg State Polytechnic University’s smart grid project that aims to create a smart grid for the university’s own use. The concept of the smart grid is interesting also for the consumers as it brings new possibilities to control own energy consumption and to save money. Smart grids makes it possible to monitor the energy consumption in real-time and to change own habits to save money. The intelligent grid also brings possibilities to integrate the renewable energy sources to the global or the local energy production much better than the current systems. Consumers can also sell their extra power to the global grid if they want.

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Combating climate change is one of the key tasks of humanity in the 21st century. One of the leading causes is carbon dioxide emissions due to usage of fossil fuels. Renewable energy sources should be used instead of relying on oil, gas, and coal. In Finland a significant amount of energy is produced using wood. The usage of wood chips is expected to increase in the future significantly, over 60 %. The aim of this research is to improve understanding over the costs of wood chip supply chains. This is conducted by utilizing simulation as the main research method. The simulation model utilizes both agent-based modelling and discrete event simulation to imitate the wood chip supply chain. This thesis concentrates on the usage of simulation based decision support systems in strategic decision-making. The simulation model is part of a decision support system, which connects the simulation model to databases but also provides a graphical user interface for the decisionmaker. The main analysis conducted with the decision support system concentrates on comparing a traditional supply chain to a supply chain utilizing specialized containers. According to the analysis, the container supply chain is able to have smaller costs than the traditional supply chain. Also, a container supply chain can be more easily scaled up due to faster emptying operations. Initially the container operations would only supply part of the fuel needs of a power plant and it would complement the current supply chain. The model can be expanded to include intermodal supply chains as due to increased demand in the future there is not enough wood chips located close to current and future power plants.

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Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.

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Energy efficiency is one of the major objectives which should be achieved in order to implement the limited energy resources of the world in a sustainable way. Since radiative heat transfer is the dominant heat transfer mechanism in most of fossil fuel combustion systems, more accurate insight and models may cause improvement in the energy efficiency of the new designed combustion systems. The radiative properties of combustion gases are highly wavelength dependent. Better models for calculating the radiative properties of combustion gases are highly required in the modeling of large scale industrial combustion systems. With detailed knowledge of spectral radiative properties of gases, the modeling of combustion processes in the different applications can be more accurate. In order to propose a new method for effective non gray modeling of radiative heat transfer in combustion systems, different models for the spectral properties of gases including SNBM, EWBM, and WSGGM have been studied in this research. Using this detailed analysis of different approaches, the thesis presents new methods for gray and non gray radiative heat transfer modeling in homogeneous and inhomogeneous H2O–CO2 mixtures at atmospheric pressure. The proposed method is able to support the modeling of a wide range of combustion systems including the oxy-fired combustion scenario. The new methods are based on implementing some pre-obtained correlations for the total emissivity and band absorption coefficient of H2O–CO2 mixtures in different temperatures, gas compositions, and optical path lengths. They can be easily used within any commercial CFD software for radiative heat transfer modeling resulting in more accurate, simple, and fast calculations. The new methods were successfully used in CFD modeling by applying them to industrial scale backpass channel under oxy-fired conditions. The developed approaches are more accurate compared with other methods; moreover, they can provide complete explanation and detailed analysis of the radiation heat transfer in different systems under different combustion conditions. The methods were verified by applying them to some benchmarks, and they showed a good level of accuracy and computational speed compared to other methods. Furthermore, the implementation of the suggested banded approach in CFD software is very easy and straightforward.

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

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In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.

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Forest biomass represents a geographically distributed feedstock, and geographical location affects the greenhouse gas (GHG) performance of a given forest-bioenergy system in several ways. For example, biomass availability, forest operations, transportation possibilities and the distances involved, biomass end-use possibilities, fossil reference systems, and forest carbon balances all depend to some extent on location. The overall objective of this thesis was to assess the GHG emissions derived from supply and energy-utilization chains of forest biomass in Finland, with a specific focus on the effect of location in relation to forest biomass’s availability and the transportation possibilities. Biomass availability and transportation-network assessments were conducted through utilization of geographical information system methods, and the GHG emissions were assessed by means of lifecycle assessment. The thesis is based on four papers in which forest biomass supply on industrial scale was assessed. The feedstocks assessed in this thesis include harvesting residues, smalldiameter energy wood and stumps. The principal implication of the findings in this thesis is that in Finland, the location and availability of biomass in the proximity of a given energyutilization or energy-conversion plant is not a decisive factor in supply-chain GHG emissions or the possible GHG savings to be achieved with forest-biomass energy use. Therefore, for the greatest GHG reductions with limited forest-biomass resources, energy utilization of forest biomass in Finland should be directed to the locations where most GHG savings are achieved through replacement of fossil fuels. Furthermore, one should prioritize the types of forest biomass with the lowest direct supply-chain GHG emissions (e.g., from transport and comminution) and the lowest indirect ones (in particular, soil carbon-stock losses), regardless of location. In this respect, the best combination is to use harvesting residues in combined heat and power production, replacing peat or coal.

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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.

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The main objective of the present study was to design an agricultural robot, which work is based on the generation of the electricity by the solar panel. To achieve the proper operation of the robot according to the assumed working cycle the detailed design of the main equipment was made. By analysing the possible areas of implementation together with developments, the economic forecast was held. As a result a decision about possibility of such device working in agricultural sector was made and the probable topics of the further study were found out.

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Pumping systems account for up to 22 % of the energy consumed by electrical motors in European industry. Many studies have shown that there is also a lot of potential for energy savings in these systems with the improvement of devices, flow control or surrounding sys-tem. The best method for more energy efficient pumping has to be found for each system separately. This thesis studies how energy saving potential in reservoir pumping system is affected by surrounding variables, such as the static head variation and friction factor. The objective is to create generally applicable graphs to quickly compare methods for reducing pumping system’s energy costs. The gained results are several graphs showcasing how the chosen variables affect energy saving potential of the pumping system in one specific case. To judge if these graphs are generally applicable, more testing with different pumps and environments are required.

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The greatest threat that the biodegradable waste causes on the environment is the methane produced in landfills by the decomposition of this waste. The Landfill Directive (1999/31/EC) aims to reduce the landfilling of biodegradable waste. In Finland, 31% of biodegradable municipal waste ended up into landfills in 2012. The pressure of reducing disposing into landfills is greatly increased by the forthcoming landfill ban on biodegradable waste in Finland. There is a need to discuss the need for increasing the utilization of biodegradable waste in regional renewable energy production to utilize the waste in a way that allows the best possibilities to reduce GHG emissions. The objectives of the thesis are: (1) to find important factors affecting renewable energy recovery possibilities from biodegradable waste, (2) to determine the main factors affecting the GHG balance of biogas production system and how to improve it and (3) to find ways to define energy performance of biogas production systems and what affects it. According to the thesis, the most important factors affecting the regional renewable energy possibilities from biodegradable waste are: the amount of available feedstock, properties of feedstock, selected utilization technologies, demand of energy and material products and the economic situation of utilizing the feedstocks. The biogas production by anaerobic digestion was seen as the main technology for utilizing biodegradable waste in agriculturally dense areas. The main reason for this is that manure was seen as the main feedstock, and it can be best utilized with anaerobic digestion, which can produce renewable energy while maintaining the spreading of nutrients on arable land. Biogas plants should be located close to the heat demand that would be enough to receive the produced heat also in the summer months and located close to the agricultural area where the digestate could be utilized. Another option for biogas use is to upgrade it to biomethane, which would require a location close to the natural gas grid. The most attractive masses for biogas production are municipal and industrial biodegradable waste because of gate fees the plant receives from them can provide over 80% of the income. On the other hand, directing gate fee masses for small-scale biogas plants could make dispersed biogas production more economical. In addition, the combustion of dry agricultural waste such as straw would provide a greater energy amount than utilizing them by anaerobic digestion. The complete energy performance assessment of biogas production system requires the use of more than one system boundary. These can then be used in calculating output–input ratios of biogas production, biogas plant, biogas utilization and biogas production system, which can be used to analyze different parts of the biogas production chain. At the moment, it is difficult to compare different biogas plants since there is a wide variation of definitions for energy performance of biogas production. A more consistent way of analyzing energy performance would allow comparing biogas plants with each other and other recovery systems and finding possible locations for further improvement. Both from the GHG emission balance and energy performance point of view, the energy consumption at the biogas plant was the most significant factor. Renewable energy use to fulfil the parasitic energy demand at the plant would be the most efficient way to reduce the GHG emissions at the plant. The GHG emission reductions could be increased by upgrading biogas to biomethane and displacing natural gas or petrol use in cars when compared to biogas CHP production. The emission reductions from displacing mineral fertilizers with digestate were seen less significant, and the greater N2O emissions from spreading digestate might surpass the emission reductions from displacing mineral fertilizers.