FABRICATION, CHARACTERIZATION, AND IRRADIATION OF AN AUSTENITIC OXIDE DISPERSION STRENGTHENED STEEL SUITED FOR NEXT GENERATION NUCLEAR APPLICATIONS

As nuclear energy systems become more advanced, the materials encompassing them need to perform at higher temperatures for longer periods of time. In this Master’s thesis we experiment with an oxide dispersion strengthened (ODS) austenitic steel that has been recently developed. ODS materials have a small concentration of nano oxide particles dispersed in their matrix, and typically have higher strength and better extreme temperature creep resistance characteristics than ordinary steels. However, no ODS materials have ever been installed in a commercial power reactor to date. Being a newer research material, there are many unanswered phenomena that need to be addressed regarding the performance under irradiation. Furthermore, due to the ODS material traditionally needing to follow a powder metallurgy fabrication route, there are many processing parameters that need to be optimized before achieving a nuclear grade material specification. In this Master’s thesis we explore the development of a novel ODS processing technology conducted in Beijing, China, to produce solutionized bulk ODS samples with ~97% theoretical density. This is done using relatively low temperatures and ultra high pressure (UHP) equipment, to compact the mechanically alloyed (MA) steel powder into bulk samples without any thermal phase change influence or oxide precipitation. By having solutionized bulk ODS samples, transmission electron microscopy (TEM) observation of nano oxide precipitation within the steel material can be studied by applying post heat treatments. These types of samples will be very useful to the science and engineering community, to answer questions regarding material powder compacting, oxide synthesis, and performance. Subsequent analysis performed at Queen’s University included X-ray diffraction (XRD) and inductively coupled plasma optical emission spectrometry (ICP-OES). Additional TEM in-situ 1MeV Kr2+ irradiation experiments coupled with energy dispersive X-ray (EDX) techniques, were also performed on large (200nm+) non-stoichiometric oxides embedded within the austenite steel grains, in an attempt to quantify the elemental compositional changes during high temperature (520oC) heavy ion irradiation.

Modelling and control of a floating oscillating water column

A novel numerical model of a Bent Backwards Duct Buoy (BBDB) Oscillating Water Column (OWC) Wave Energy Converter was created based on existing isolated numerical models of the different energy conversion systems utilised by an OWC. The novel aspect of this numerical model is that it incorporates the interdependencies of the different power conversion systems rather than modelling each system individually. This was achieved by accounting for the dynamic aerodynamic damping caused by the changing turbine rotational velocity by recalculating the turbine damping for each simulation sample and applying it via a feedback loop. The accuracy of the model was validated using experimental data collected during the Components for Ocean Renewable Energy Systems (CORES) EU FP-7 project that was tested in Galway Bay, Ireland. During the verification process, it was discovered that the model could also be applied as a valuable tool when troubleshooting device performance. A new turbine was developed and added to a full scale model after being investigated using Computational Fluid Dynamics. The energy storage capacity of the impulse turbine was investigated by modelling the turbine with both high and low inertia and applying three turbine control theories to the turbine using the full scale model. A single Maximum Power Point Tracking algorithm was applied to the low-inertia turbine, while both a fixed and dynamic control algorithm was applied to the high-inertia turbine. These results suggest that the highinertia turbine could be used as a flywheel energy storage device that could help minimize output power variation despite the low operating speed of the impulse turbine. This research identified the importance of applying dynamic turbine damping to a BBDB OWC numerical model, revealed additional value of the model as a device troubleshooting tool, and found that an impulse turbine could be applied as an energy storage system.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

Contribution to the diffuse radiation modelling in Évora, Portugal

Solar radiation data is crucial for the design of energy systems based on the solar resource. Since diffuse radiation measurements are not always available in the archive data series, either due to the inexistence of measuring equipment, shading device misplacement or missing data, models to generate these data are needed. In this work, one year of hourly and daily horizontal solar global and diffuse irradiation measurements in Évora are used to establish a new relation between the diffuse radiation and the clearness index. The proposed model includes a fitting parameter, which was adjusted through a simple optimization procedure to minimize the Least Square Error as compared to measurements. A comparison against several other fitting models presented in the literature was also carried out using the Root Mean Square Error as statistical indicator, and it was found that the present model is more accurate than the previous fitting models for the diffuse radiation data in Évora.

Armazenamento sazonal de energia solar térmica de baixa temperatura para climatização de edifícios

Face aos padrões atuais de vida, em que despendemos a maior parte do nosso tempo no interior de edifícios, com um nível de conforto que ninguém quer abdicar, urge o desenvolvimento de tecnologias de climatização sustentáveis. Devido a uma combinação única de fatores, casas de baixo consumo de energia (e também casas passivas) em Portugal, são particularmente adequadas de explorar as vantagens da energia solar térmica, especialmente quando combinado com armazenamento sazonal de energia. No entanto nenhum exemplo documentado existe de como esta sinergia pode ser explorada com sucesso em Portugal, ilustrando assim o modo em que a necessidade de aquecimento pode ser colmatada de uma forma sustentável sem o uso de combustíveis fósseis. A energia solar é uma excelente alternativa de fonte de energia para aquecimento de edifícios. Um principal fator que limita a sua aplicação é que é uma fonte de energia com uma disponibilidade média de variação cíclica. O uso de armazenamento sazonal de energia pode reduzir substancialmente o custo do sistema solar que é capaz de fornecer até 100% das necessidades energéticas dos edifícios. Estes sistemas são projetados para armazenar a energia solar durante o verão e reter o calor armazenado para posterior utilização durante o inverno; Abstract: SEASONAL SOLAR THERMAL ENERGY STORAGE FOR LOW TEMPERATURE HEATING BUILDINGS. Given the current standards of living, where we spent most of our time inside buildings, with a level of Comfort that no one wants to give up, urges the development of sustainable climate control technologies. Due to a unique combination of factors, low energy (and also passive) houses in Portugal are particularly well suited to exploiting the advantages of solar thermal energy especially when combined with seasonal energy storage. However no documented example there of how this synergy can be exploited successfully in Portugal, illustrating the way in which the need for heating can be addressed in a sustainable manner without the use of fossil fuels. Solar energy is an important alternative energy source for heating applications. One main factor that limits its application is that it is an energy source with an average availability of cyclical variation. The use of seasonal thermal energy storage can substantially reduce the cost of solar energy systems that can supply up to 100% of buildings energy needs. Such systems are designed to collect solar energy during the summer and retain the stored heat for use during the winter.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

Sintesi e caratterizzazione di materiali polimerici water-soluble per applicazioni nel campo del fotovoltaico organico

The need to use renewable energy sources, due to the massive production of pollution for the energy production, has led to the development of new technologies for the use of solar energy. The purpose of this thesis project is to synthesize and characterize new thiophene-based polymeric materials processable in water, a green solvent, for the construction of organic solar cells, promising and versatile devices used for the production of electric energy. For this, a highly regioregular polymer was synthesized through GRIM polymerization (Grignard Metathesis Polymerization) on which a study was performed to identify the optimal reaction time.

Energy Storage Systems for Electric Vehicles: Performance Comparison based on a Simple Equivalent Circuit and Experimental Tests

The decision to select the most suitable type of energy storage system for an electric vehicle is always difficult, since many conditionings must be taken into account. Sometimes, this study can be made by means of complex mathematical models which represent the behavior of a battery, ultracapacitor or some other devices. However, these models are usually too dependent on parameters that are not easily available, which usually results in nonrealistic results. Besides, the more accurate the model, the more specific it needs to be, which becomes an issue when comparing systems of different nature. This paper proposes a practical methodology to compare different energy storage technologies. This is done by means of a linear approach of an equivalent circuit based on laboratory tests. Via these tests, the internal resistance and the self-discharge rate are evaluated, making it possible to compare different energy storage systems regardless their technology. Rather simple testing equipment is sufficient to give a comparative idea of the differences between each system, concerning issues such as efficiency, heating and self-discharge, when operating under a certain scenario. The proposed methodology is applied to four energy storage systems of different nature for the sake of illustration.

Assessment of energy efficiency in electric storage water heaters

Nowadays there are several ways of supplying hot water for showers in residential buildings. One of them is the use of electric storage water heaters (boilers). This equipment raises the water temperature in a reservoir (tank) using the heat generated by an electric resistance. The behavior of this equipment in Brazil is still a research object and there is not a standard in the country to regulate its efficiency. In this context, an experimental program was conducted aiming to collect power consumption data to evaluate its performance. The boilers underwent an operation cycle to simulate a usage condition aiming to collect parameters for calculating the efficiency. This 1-day cycle was composed of the following phases: hot water withdrawal, reheating and standby heat loss. The methods allowed the identification of different parameters concerning the boilers work, such as: standby heat loss in 24 h, hot water withdrawal rate, reheating time and energy efficiency. The average energy efficiency obtained was of 75%. The lowest efficiency was of 62% for boiler 2 and the highest was of 85% for boiler 9. (C) 2008 Elsevier B.V. All rights reserved.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Energy Resource Management under the Influence of the Weekend Transition Considering an Intensive use of Electric Vehicles

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Active Damping and Energy Recovery in a Hydraulic Boom Controlled by an Electric Drive

The aim of the study is to obtain a mathematical description for an alternative variant of controlling a hydraulic circuit with an electrical drive. The electrical and hydraulic systems are described by basic mathematical equations. The flexibilities of the load and boom is modeled with assumed mode method. The model is achieved and proven with simulations. The controller is constructed and proven to decrease oscillations and improve the dynamic response of the system.

Energy Efficiency of a Diesel-Electric MobileWorking Machine

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.