There have been a lot of developments in terms of Plug-in Electric Vehicles (PEVs) regarding many different subjects, and with some variations between authors. On this basis, it is intended to sum up a lot of contents being approached, and help understanding them. Followed by the development and analysis of a model in order to better understand the functionality of these new developments. First a state of the art is presented where the new development are presented, these will include management of the PEV’s, uncontrolled or controlled (i.e. aggregated) and their capability of using V2G and G2V technologies are analyzed. Afterwards, electricity markets are approached where real world applications are shown and different market types are categorized in order to a better understanding of the subject. The interaction of the PEVs with some renewable energy resources (e.g. solar, wind and biomass) is presented. To finalize, models of PEVs are categorized and multiple types of modules, the related variables, applied methods, and the considered parameters are presented. For a case analysis, a model that includes a parking lot of PEVs will be studied, which includes renewable energy resources, wind and solar. The objective is to analyze the impact of these on the market participation of the parking lot and also on the distribution grid. These analyses will be made on size variations, grid placement and also constraint variations of the model.

Os mercados de eletricidade têm vindo a evoluir devido à globalização e ao incremento da competitividade nas últimas décadas, o que levou a sua restruturação. Um exemplo claro é a interligação entre vários países utilizando assim o mesmo operador de mercado, como por exemplo o mercado elétrico Português e o mercado elétrico Espanhol através do “Mercado Ibérico de Eletricidade” (MIBEL). A grande capacidade de energia renovável instalada têm motivado os produtores de energia a melhorar a gestão da sua produção no mercado de eletricidade. Com esse aumento foram também levantadas questões operacionais importantes ao nível do mercado. Um dos desafios dos próximos anos é a contínua integração das renováveis. Um ponto de vista interessante é a combinação entre as energias renováveis com elevado grau de incerteza (eólica e fotovoltaica) e os sistemas de armazenamento de energia. Nesta dissertação, foram desenvolvidos e estudados cinco modelos. Os principais modelos são para cada uma das seguintes tecnologias renováveis, a energia eólica, o sistema de armazenamento genérico e a hídrica reversível. Depois disso o modelo eólico é combinado com o sistema de armazenamento de energia genérico e com a unidade hídrica reversível. Todos os modelos são formulados através de programação linear inteira mista estocástica, com o objetivo otimizar a licitação ao mercado de eletricidade. Para fim, as conclusões mais relevantes são descritas e apresentadas.

Nowadays, the paradigm shift in the electricity sector and the advent of the smart grid, along with the growing impositions of a gradual reduction of greenhouse gas emissions, pose numerous challenges related with the sustainable management of power systems. The insular power systems industry is heavily dependent on imported energy, namely fossil fuels, and also on seasonal tourism behavior, which strongly influences the local economy. In comparison with the mainland power system, the behavior of insular power systems is highly influenced by the stochastic nature of the renewable energy sources available. The insular electricity grid is particularly sensitive to power quality parameters, mainly to frequency and voltage deviations, and a greater integration of endogenous renewables potential in the power system may affect the overall reliability and security of energy supply, so singular care should be placed in all forecasting and system operation procedures. The goals of this thesis are focused on the development of new decision support tools, for the reliable forecasting of market prices and wind power, for the optimal economic dispatch and unit commitment considering renewable generation, and for the smart control of energy storage systems. The new methodologies developed are tested in real case studies, demonstrating their computational proficiency comparatively to the current state-of-the-art.

Os sistemas de distribuição de energia elétrica são geralmente estruturados como sistemas que contêm poucas malhas mas a maioria deles opera com uma topologia radial, principalmente para acomodar a proteção coordenada. Obter a configuração radial ótima sob vários critérios tem sido um tema de investigação ativo nas últimas duas décadas. Motivado pelo elevado esforço computacional requerido e pela não linearidade do problema, a maioria das metodologias propostas, mono-objetivo ou multiobjetivo, usam várias meta-heurísticas. Nesta dissertação, o problema de reconfiguração de sistemas de distribuição é formulado como sendo de programação linear inteira-mista multiobjetivo, respeitando as restrições de radialidade. Implementando uma versão melhorada do método de e-Restrições permite gerar uma representação adequada do conjunto de Pareto, sendo uma nova contribuição relativamente a estudos anteriores. O objetivo consiste em determinar as configurações radiais ótimas durante vários intervalos de tempo, minimizando as perdas de energia ativa e os custos emergentes das operações de switching. A metodologia proposta é inicialmente testada em sistemas de 16 e 69 nós, sendo posteriormente testada num sistema real baseado na Ilha de S. Miguel nos Açores.

Esta dissertação tem como objetivo principal implementar a técnica de controlo preditivo em algumas cargas residenciais. Pretende-se que a técnica de controlo preditivo seja implementada nas cargas residenciais, para que se possa conseguir um melhor aproveitamento da energia, e uma consequente redução da conta da eletricidade. Uma vez que o sector residencial tem um grande impacto percentual ao nível do consumo energético mundial, e uma redução de energia consumida neste sector é algo necessário, para reduzir os gases com efeitos de estufa que advêm da produção de eletricidade. Para tal efeito, foram então feitas simulações com a duração de 24 horas, em cargas residenciais como o ar condicionado, o termoacumulador e o frigorífico. Cada carga é modelada em tempo discreto, e para tal foram sempre utilizados parâmetros reais, com o objetivo de aproximar os resultados o mais próximo possível da realidade. Assim, foi possível aplicar a técnica de controlo preditivo em algumas cargas como o ar condicionado. Outras cargas como a máquina de lavar roupa, foram simuladas para serem observados os seus efeitos ao nível de consumo e eficiência energética quando juntos com outros equipamentos. Durante a aplicação do controlo preditivo, este foi estudado de tal forma que foi possível aprofundar os conhecimentos sobre ele e assim, explorar funções adicionais que levaram à obtenção de resultados melhorados acima do que era previsto inicialmente. Foi ainda desenvolvido um programa para prever cenários de consumo ótimo, em função das cargas utilizadas nas habitações. Os resultados foram todos obtidos a partir do software Matlab/Simulink onde foi utilizada a toolbox do controlo preditivo (MPC). Todos os resultados obtidos foram bastante satisfatórios, tendo em conta o objetivo inicial de reduzir a energia consumida e consequentemente reduzir o custo da eletricidade.

Electrical energy sector has been changing over the past years due to economic and environmental causes. The climate changes over the last decades have led to the Kyoto Protocol agreement in order to address these environmental concerns. The appointed solution which is proposed as an answer to these concerns is the production of electrical energy through renewable energy sources (RES). RES not only contribute to these environmental goals, but also are an opportunity to reduce the economic challenges that countries face due to fossil fuel dependence. However, it is important to address the challenges that come from adopting RES as a means of energy production. Several RES such as wind and solar production, which are strongly dependent on weather conditions, could have a negative impact on market structures. The production from these types of sources can introduce significant uncertainty to electricity markets, which could further hinder their use. If the investments on RES production units such as wind and solar are to be successful, decision-making models could help the investors to be confident regarding the investment, increasing the promotion of the use of these technologies. In this dissertation, two bidding strategies in the day-ahead market are presented. The proposed strategies maximize the profits from offering the wind and photovoltaic production in the dayahead market, improving the production management.

It is widely recognized that renewable energy sources are likely to represent a significant portion of the production mix in many power systems around the world, a trend expected to be increasingly followed in the coming years due to environmental and economic reasons. Among the different endogenous renewable sources that may be used in order to achieve reductions in the carbon footprint related to the electricity sector and increase the economic efficiency of the generation mix, wind power generation has been one of the most popular options. However, despite the potential benefits that arise from the integration of these resources in the power system, their large-scale integration leads to additional problems due to the fact that their production is highly volatile. As a result, apart from the typical sources of uncertainty that the System Operators have to face, such as system contingencies and intra-hour load deviations, through the deployment of sufficient levels of reserve generation, additional reserves must be kept in order to maintain the balance between the generation and the consumption. Furthermore, a series of other problems arise, such as efficiency loss because of ramping of conventional units, environmental costs because of increased emissions due to suboptimal unit commitment and dispatch and more costly system operation and maintenance. Recently, it has been recognized that apart from the generation side, several types of loads may be deployed in order to provide system services and especially, different types of reserves, through demand response. The contribution of demand side reserves to accommodate higher levels of wind power generation penetration is likely to be of substantial importance in the future and therefore, the integration of these resources in the system operations needs to be thoroughly studied. This thesis deals with the aspects of demand response as regards the integration of wind power generation in the power system. First, a mapping of the current status of demand response internationally is attempted, followed also by a discussion concerning the opportunities, the benefits and the barriers to the widespread adoption of demand side resources. Then, several joint energy and reserve market structures are developed which explicitly incorporate demand side resources that may contribute to energy and reserve services. Two-stage stochastic programming is employed in order to capture the uncertainty of wind power generation. Moreover, several aspects of demand response are considered such as the capability of providing contingency and load following reserves, the appropriate modeling of industrial consumer processes load and the load recovery effect. Finally, this thesis investigates the effect of demand side resources on the risk that is associated with the decisions of the System Operator through appropriate risk management techniques, proposing also a novel methodology of handling risk as an alternative to the commonly used technique.

Floating-point computing with more than one TFLOP of peak performance is already a reality in recent Field-Programmable Gate Arrays (FPGA). General-Purpose Graphics Processing Units (GPGPU) and recent many-core CPUs have also taken advantage of the recent technological innovations in integrated circuit (IC) design and had also dramatically improved their peak performances. In this paper, we compare the trends of these computing architectures for high-performance computing and survey these platforms in the execution of algorithms belonging to different scientific application domains. Trends in peak performance, power consumption and sustained performances, for particular applications, show that FPGAs are increasing the gap to GPUs and many-core CPUs moving them away from high-performance computing with intensive floating-point calculations. FPGAs become competitive for custom floating-point or fixed-point representations, for smaller input sizes of certain algorithms, for combinational logic problems and parallel map-reduce problems. © 2014 Technical University of Munich (TUM).

A unified architecture for fast and efficient computation of the set of two-dimensional (2-D) transforms adopted by the most recent state-of-the-art digital video standards is presented in this paper. Contrasting to other designs with similar functionality, the presented architecture is supported on a scalable, modular and completely configurable processing structure. This flexible structure not only allows to easily reconfigure the architecture to support different transform kernels, but it also permits its resizing to efficiently support transforms of different orders (e. g. order-4, order-8, order-16 and order-32). Consequently, not only is it highly suitable to realize high-performance multi-standard transform cores, but it also offers highly efficient implementations of specialized processing structures addressing only a reduced subset of transforms that are used by a specific video standard. The experimental results that were obtained by prototyping several configurations of this processing structure in a Xilinx Virtex-7 FPGA show the superior performance and hardware efficiency levels provided by the proposed unified architecture for the implementation of transform cores for the Advanced Video Coding (AVC), Audio Video coding Standard (AVS), VC-1 and High Efficiency Video Coding (HEVC) standards. In addition, such results also demonstrate the ability of this processing structure to realize multi-standard transform cores supporting all the standards mentioned above and that are capable of processing the 8k Ultra High Definition Television (UHDTV) video format (7,680 x 4,320 at 30 fps) in real time.

In this paper, a novel ROM-less RNS-to-binary converter is proposed, using a new balanced moduli set {22n-1, 22n + 1, 2n-3, 2n + 3} for n even. The proposed converter is implemented with a two stage ROM-less approach, which computes the value of X based only in arithmetic operations, without using lookup tables. Experimental results for 24 to 120 bits of Dynamic Range, show that the proposed converter structure allows a balanced system with 20% faster arithmetic channels regarding the related state of the art, while requiring similar area resources. This improvement in the channel's performance is enough to offset the higher conversion costs of the proposed converter. Furthermore, up to 20% better Power-Delay-Product efficiency metric can be achieved for the full RNS architecture using the proposed moduli set. © 2014 IEEE.