Design and Material Selection of High-Speed Rotating Electrical Machines

The increasing emphasis on energy efficiency is starting to yield results in the reduction in greenhouse gas emissions; however, the effort is still far from sufficient. Therefore, new technical solutions that will enhance the efficiency of power generation systems are required to maintain the sustainable growth rate, without spoiling the environment. A reduction in greenhouse gas emissions is only possible with new low-carbon technologies, which enable high efficiencies. The role of the rotating electrical machine development is significant in the reduction of global emissions. A high proportion of the produced and consumed electrical energy is related to electrical machines. One of the technical solutions that enables high system efficiency on both the energy production and consumption sides is high-speed electrical machines. This type of electrical machines has a high system overall efficiency, a small footprint, and a high power density compared with conventional machines. Therefore, high-speed electrical machines are favoured by the manufacturers producing, for example, microturbines, compressors, gas compression applications, and air blowers. High-speed machine technology is challenging from the design point of view, and a lot of research is in progress both in academia and industry regarding the solution development. The solid technical basis is of importance in order to make an impact in the industry considering the climate change. This work describes the multidisciplinary design principles and material development in high-speed electrical machines. First, high-speed permanent magnet synchronous machines with six slots, two poles, and tooth-coil windings are discussed in this doctoral dissertation. These machines have unique features, which help in solving rotordynamic problems and reducing the manufacturing costs. Second, the materials for the high-speed machines are discussed in this work. The materials are among the key limiting factors in electrical machines, and to overcome this limit, an in-depth analysis of the material properties and behavior is required. Moreover, high-speed machines are sometimes operating in a harsh environment because they need to be as close as possible to the rotating tool and fully exploit their advantages. This sets extra requirements for the materials applied.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Theoretical Design and Synthesis of Donor-Acceptor Conjugated Polymers for Photovoltaic and NLO Applications

Polymers with conjugated π-electron backbone display unusual electronic properties such as low energy optical transition, low ionization potentials, and high electron affinities. The properties that make these materials attractive include a wide range of electrical conductivity, mechanical flexibility and thermal stability. Some of the potential applications of these conjugated polymers are in sensors, solar cells, field effect transistors, field emission and electrochromic displays, supercapacitors and energy storage. With recent advances in the stability of conjugated polymer materials, and improved control of properties, a growing number of applications are currently being explored. Some of the important applications of conducting polymers include: they are used in electrostatic materials, conducting adhesives, shielding against electromagnetic interference (EMI), artificial nerves, aircraft structures, diodes, and transistors.

Erneuerbare Energien im Verbund mit Hochleistungs-Bleiakkumulatoren zur Bereitstellung von Spitzenleistung - am Beispiel von Windkraftwerken im 20 kV-Versorgungsnetz der CEGEDEL / Luxemburg -

Die wachsende Weltbevölkerung bedingt einen höheren Energiebedarf, dies jedoch unter der Beachtung der nachhaltigen Entwicklung. Die derzeitige zentrale Versorgung mit elektrischer Energie wird durch wenige Erzeugungsanlagen auf der Basis von fossilen Primärenergieträgern und Kernenergie bestimmt, die die räumlich verteilten Verbraucher zuverlässig und wirtschaftlich über ein strukturiertes Versorgungssystem beliefert. In den Elektrizitätsversorgungsnetzen sind keine nennenswerten Speicherkapazitäten vorhanden, deshalb muss die von den Verbrauchern angeforderte Energie resp. Leistung jederzeit von den Kraftwerken gedeckt werden. Bedingt durch die Liberalisierung der Energiemärkte und die geforderte Verringerung der Energieabhängigkeit Luxemburgs, unterliegt die Versorgung einem Wandel hin zu mehr Energieeffizienz und erhöhter Nutzung der dargebotsabhängigen Energiequellen. Die Speicherung der aus der Windkraft erzeugten elektrischen Energie, wird in den Hochleistungs-Bleiakkumulatoren, errichtet im ländlichen Raum in der Nähe der Windkraftwerke, eingespeichert. Die zeitversetzte Einspeisung dieser gespeicherten elektrischen Energie in Form von veredelter elektrischer Leistung während den Lastspitzen in das 20 kV-Versorgungsnetz der CEGEDEL stellt die Innovation in der luxemburgischen Elektrizitätsversorgung dar. Die Betrachtungen beschränken sich somit auf die regionale, relativ kleinräumige Einbindung der Windkraft in die elektrische Energieversorgung des Großherzogtums Luxemburg. Die Integration der Windkraft im Regionalbereich wird in den Vordergrund der Untersuchung gerückt. Überregionale Ausgleichseffekte durch Hochspannungsleitungen der 230/400 kV-Systeme werden außer Acht gelassen. Durch die verbrauchernahe Bereitstellung von elektrischer Spitzenleistung vermindern sich ebenfalls die Übertragungskosten aus den entfernten Spitzenlastkraftwerken, der Ausbau von Kraftwerkskapazitäten kann in die Zukunft verschoben werden. Die Emission von Treibhausgasen in thermischen Kraftwerken wird zum Teil reduziert. Die Berechnungen der Wirtschaftlichkeit von Hybridanlagen, zusammengesetzt aus den Windkraftwerken und den Hochleistungs-Bleiakkumulatoren bringen weitere Informationen zum Einsatz dieser dezentralen Speichern, als Partner der nachhaltigen Energieversorgung im ländlichen Raum. Die untersuchte Einspeisung von erneuerbarer Spitzenleistung lässt sich auch in die Entwicklungsländer übertragen, welche nicht über zentrale Kraftwerkskapazitäten und Verteilungsnetze verfügen.

Can microgrids make a major contribution to UK energy supply?

Almost all the electricity currently produced in the UK is generated as part of a centralised power system designed around large fossil fuel or nuclear power stations. This power system is robust and reliable but the efficiency of power generation is low, resulting in large quantities of waste heat. The principal aim of this paper is to investigate an alternative concept: the energy production by small scale generators in close proximity to the energy users, integrated into microgrids. Microgrids—de-centralised electricity generation combined with on-site production of heat—bear the promise of substantial environmental benefits, brought about by a higher energy efficiency and by facilitating the integration of renewable sources such as photovoltaic arrays or wind turbines. By virtue of good match between generation and load, microgrids have a low impact on the electricity network, despite a potentially significant level of generation by intermittent energy sources. The paper discusses the technical and economic issues associated with this novel concept, giving an overview of the generator technologies, the current regulatory framework in the UK, and the barriers that have to be overcome if microgrids are to make a major contribution to the UK energy supply. The focus of this study is a microgrid of domestic users powered by small Combined Heat and Power generators and photovoltaics. Focusing on the energy balance between the generation and load, it is found that the optimum combination of the generators in the microgrid- consisting of around 1.4 kWp PV array per household and 45% household ownership of micro-CHP generators- will maintain energy balance on a yearly basis if supplemented by energy storage of 2.7 kWh per household. We find that there is no fundamental technological reason why microgrids cannot contribute an appreciable part of the UK energy demand. Indeed, an estimate of cost indicates that the microgrids considered in this study would supply electricity at a cost comparable with the present electricity supply if the current support mechanisms for photovoltaics were maintained. Combining photovoltaics and micro-CHP and a small battery requirement gives a microgrid that is independent of the national electricity network. In the short term, this has particular benefits for remote communities but more wide-ranging possibilities open up in the medium to long term. Microgrids could meet the need to replace current generation nuclear and coal fired power stations, greatly reducing the demand on the transmission and distribution network.

Representing the acquisition and use of energy by individuals in agent-based models of animal populations

Summary 1. Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. 2. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. 3. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. 4. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. 5. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. Keywords: bioenergetics; energy budget; individual-based models; population dynamics.

Do smart grids offer a new incentive for SME carbon reduction?

Collectively small and medium sized enterprises (SMEs) are significant energy users although many are unregulated by existing policies due to their low carbon emissions. Carbon reduction is often not a priority but smart grids may create a new opportunity. A smart grid will give electricity suppliers a picture of real-time energy flows and the opportunity for consumers to receive financial incentives for engaging in demand side management. As well as creating incentives for local carbon reduction, engaging SMEs with smart grids has potential for contributing to wider grid decarbonisation. Modelling of buildings, business activities and technology solutions is needed to identify opportunities for carbon reduction. The diversity of the SME sector complicates strategy development. SMEs are active in almost every business area and occupy the full range of property types. This paper reviews previous modelling work, exposing valuable data on floor space and energy consumption associated with different business activities. Limitations are seen with the age of this data and an inability to distinguish SME energy use. By modelling SME energy use, electrical loads are identified which could be shifted on demand, in a smart network. Initial analysis of consumption, not constrained by existing policies, identifies heating and cooling in retail and commercial offices as having potential for demand response. Hot water in hotel and catering and retail sectors may also be significant because of the energy storage potential. Areas to consider for energy efficiency schemes are also indicated.

The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Simulation of Photovoltaic Panel Production as Complement to Ground Source Heat Pump System

This master thesis presents a new technological combination of two environmentally friendly sources of energy in order to provide DHW, and space heating. Solar energy is used for space heating, and DHW production using PV modules which supply direct current directly to electrical heating elements inside a water storage tank. On the other hand a GSHP system as another source of renewable energy provides heat in the water storage tank of the system in order to provide DHW and space heating. These two sources of renewable energy have been combined in this case-study in order to obtain a more efficient system, which will reduce the amount of electricity consumed by the GSHP system.The key aim of this study is to make simulations, and calculations of the amount ofelectrical energy that can be expected to be produced by a certain amount of PV modules that are already assembled on a house in Vantaa, southern Finland. This energy is then intended to be used as a complement to produce hot water in the heating system of the house beside the original GSHP system. Thus the amount of electrical energy purchased from the grid should be reduced and the compressor in the GSHP would need fewer starts which would reduce the heating cost of the GSHP system for space heating and providing hot water.The produced energy by the PV arrays in three different circuits will be charged directly to three electrical heating elements in the water storage tank of the existing system to satisfy the demand of the heating elements. The excess energy can be used to heat the water in the water storage tank to some extent which leads to a reduction of electricity consumption by the different components of the GSHP system.To increase the efficiency of the existing hybrid system, optimization of different PV configurations have been accomplished, and the results are compared. Optimization of the arrays in southern and western walls shows a DC power increase of 298 kWh/year compared with the existing PV configurations. Comparing the results from the optimization of the arrays on the western roof if the intention is to feed AC power to the components of the GSHP system shows a yearly AC power production of 1,646 kWh.This is with the consideration of no overproduction by the PV modules during the summer months. This means the optimized PV systems will be able to cover a larger part of summer demand compared with the existing system.

Evaluation of a high temperature solar thermal seasonal borehole storage

A solar thermal system with seasonal borehole storage for heating of a residential area in Anneberg, Sweden, approximately 10 km north of Stockholm, has been in operation since late 2002. Originally, the project was part of the EU THERMIE project “Large-scale Solar Heating Systems for Housing Developments” (REB/0061/97) and was the first solar heating plant in Europe with borehole storage in rock not utilizing a heat pump. Earlier evaluations of the system show lower performance than the preliminary simulation study, with residents complaining of a high use of electricity for domestic hot water (DHW) preparation and auxiliary heating. One explanation mentioned in the earlier evaluations is that the borehole storage had not yet reached “steady state” temperatures at the time of evaluation. Many years have passed since then and this paper presents results from a new evaluation. The main aim of this work is to evaluate the current performance of the system based on several key figures, as well as on system function based on available measurement data. The analysis show that though the borehole storage now has reached a quasi-steady state and operates as intended, the auxiliary electricity consumption is much higher than the original design values largely due to high losses in the distribution network, higher heat loads as well as lower solar gains.

Background thermal depolarization of electrons in storage rings

We discuss the influence of the background thermal bath on the depolarization of electrons in high-energy storage rings, and on the photon emission associated with the spin flip. We focus, in particular, on electrons at CERN LEP. We show that in a certain interval of solid angles the photon emission is enhanced several orders of magnitude because of the presence of the thermal bath. Notwithstanding, the overall depolarization induced by the background thermal bath at LEP conditions is much smaller than the one induced by plain acceleration at zero temperature and can be neglected in practical situations. Eventually we discuss under what conditions the background thermal bath can enhance the overall depolarization by several orders of magnitude.

Orientation, building height and sky view factor as energy efficiency design parameters

The energy efficiency of buildings should be a goal at the pre-design phase, though the importance of the design variables is often neglected even during the design process. Highlighting the relevance of these design variables, this research studies the relationships of building location variables with the electrical energy consumption of residential units. The following building design parameters are considered: orientation, story height and sky view factor (SVF). The consideration of the SVF as a location variable contributes to the originality of this research. Data of electrical energy consumption and users' profiles were collected and several variables were considered for the development of an Artificial Neural Network model. This model allows the determination of the relative importance of each variable. The results show that the apartments' orientation is the most important design variable for the energy consumption, although the story height and the sky view factor play a fundamental role in that consumption too. We pointed out that building heights above twenty-four meters do not optimize the energy efficiency of the apartments and also that an increasing SVF can influence the energy consumption of an apartment according to their orientation.