Life cycle analysis of biodiesel production

Biodieselhas attracted considerable attention as a renewable, biodegradable, and nontoxic fuel and can contribute to solving the energy problems, significantly reducing the emission of gases which cause global warming. The first stage of this work was to simulate different alternative processes for producing biodiesel. The method used for the production of biodiesel is the transesterification of vegetable oilswith an alcohol in the presence of a catalyst. The raw materials used were palm oils and waste cooking oil. The second stage was a life cycle analysis for all alternatives under study, followed by an economic analysis for the alternatives that present minor impacts and which are more promising from an economic point of view. Finally,we proceeded to compare the different alternatives fromboth the point of view of life cycle and economic analysis. The feasibility of all processes was proven and the biodiesel obtained had good specifications. From the standpoint of life cycle analysis, the best alternative was the process of alkaline catalysiswith acid pretreatment for waste cooking oil. The economic analysis was done to the previous mentioned process and to the process that uses raw virgin oils, methanol, and sodium hydroxide. This process has lower investment costs but the process of alkaline catalysis with acid pre-treatment, whose main raw material is waste oil, is much more profitable and has less environmental impacts.

A comparative analysis of fault injection methods via enhanced on-chip debug infrastructures

On-chip debug (OCD) features are frequently available in modern microprocessors. Their contribution to shorten the time-to-market justifies the industry investment in this area, where a number of competing or complementary proposals are available or under development, e.g. NEXUS, CJTAG, IJTAG. The controllability and observability features provided by OCD infrastructures provide a valuable toolbox that can be used well beyond the debugging arena, improving the return on investment rate by diluting its cost across a wider spectrum of application areas. This paper discusses the use of OCD features for validating fault tolerant architectures, and in particular the efficiency of various fault injection methods provided by enhanced OCD infrastructures. The reference data for our comparative study was captured on a workbench comprising the 32-bit Freescale MPC-565 microprocessor, an iSYSTEM IC3000 debugger (iTracePro version) and the Winidea 2005 debugging package. All enhanced OCD infrastructures were implemented in VHDL and the results were obtained by simulation within the same fault injection environment. The focus of this paper is on the comparative analysis of the experimental results obtained for various OCD configurations and debugging scenarios.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

Aplicação do modelo de Elton-Gruber para a construção de carteira no índice PSI-20

Os mercados financeiros têm um papel fundamental na dinamização das economias modernas. Às empresas cotadas oferece o capital necessário para impulsionar o seu crescimento e aos investidores individuais proporciona a diversificação das suas carteiras, usufruindo desta forma do crescimento e da vitalidade da economia mundial. A gestão de carteiras de ativos financeiros constitui uma área que procura apresentar mecanismos para a obtenção de uma relação ótima entre retorno e risco. Neste sentido, inúmeros estudos têm contribuído de forma significativa para a eficiência e para a prática desta técnica. Esta dissertação pretende analisar a metodologia desenvolvida por Elton-Gruber para a construção de carteiras otimizadas e aplicar as técnicas subjacentes ao mercado acionista português. Para o efeito, serão realizadas pesquisas em fontes bibliográficas da especialidade e serão consultadas bases de dados de cotações históricas das ações e do índice de mercado nacional. A aplicação incidiu sobre ações cotadas no índice PSI-20 durante o período compreendido entre 2010 e 2014. No intuito de melhorar a compreensão das séries de retornos das amostras, o estudo de caráter quantitativo também recorreu à análise estatística. As evidências mostram que a carteira otimizada, no período em análise, contém apenas as ações da empresa Portucel. Este resultado estará condicionado pelos efeitos da crise financeira que iniciou em 2008.