Eficiência de antioxidantes na estabilização do Biodiesel

O Biodiesel é uma fonte de energia renovável que actualmente se encontra em expansão. O Biodiesel é constituído por uma mistura de ésteres alquílicos de ácidos gordos. A existência de ácidos gordos insaturados torna o Biodiesel quimicamente menos estável, podendo ocorrer oxidação, degradação e polimerização do combustível, se este for inadequadamente armazenado ou transportado. O objectivo deste trabalho consistiu em avaliar a eficiência da utilização de antioxidantes fenólicos (ácido protocatecuico, ácido gálico, ácido 3,4 di-hidroxifenilacético, ácido cafeico, ácido hidrocafeico, ácido 3,4,5-tri-hidroxicinâmico, ácido m-coumárico e ácido p-coumárico), na estabilização do Biodiesel. O estudo envolveu a análise da influência do uso de cada um dos antioxidantes na inibição da peroxidação lipídica do ácido linoleico um dos principais ácidos gordos insaturados presentes na matéria-prima utilizada na produção de Biodiesel. A avaliação do efeito de inibição dos antioxidantes na peroxidação do ácido linoleico foi efetuada usando o método do tiocianato de ferro (III). Os resultados obtidos demonstraram, que todos os ácidos fenólicos estudados, apresentam uma elevada capacidade para inibir a peroxidação lipídica do ácido linoleico. As percentagens de inibição da peroxidação do ácido linoleico variaram entre os 72%, observada para o ácido p-coumárico, e os 82 %, verificada para o ácido protocatecuico. A eficiência de inibição da peroxidação por parte dos antioxidantes fenólicos em estudo foi comparada com a obtida utilizando um antioxidante de referência, o trolox. A eficiência de inibição obtida para todos os antioxidantes fenólicos estudados foi muito superior à observada para o trolox. Os resultados obtidos nesta dissertação permitem concluir que a utilização de ácidos fenólicos constitui uma boa alternativa para a estabilização de matrizes lipídicas, particularmente em combustíveis como o Biodiesel.

Electricity markets modeling considering complex contracts and aggregators

All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.

Utilização da Nanotecnologia para o desenvolvimento sustentável na indústria agro-alimentar

O crescimento populacional esperado para os próximos anos conduzirá à necessidade de aumentar a produção agrícola de modo a satisfazer o aumento da procura. Nos últimos anos tem-se assistido a uma evolução tecnológica nos sistemas de produção que tem permitido aumentar a produtividade agrícola, por vezes à custa de elevados consumos de energia e com práticas nem sempre ambientalmente corretas. Os desafios que se colocam atualmente são no sentido de melhorar a conservação de recursos escassos, como o solo e a água, de aumentar a eficiência de uso de fatores de produção, de encontrar novas culturas, do desenvolvimento da biotecnologia, da diminuição dos consumos energéticos e de melhorar ainda mais as tecnologias associadas à produção. De maneira a responder aos desafios emergentes da procura por alimentos, da escassez de terrenos agrícolas aráveis bem como da existência de pragas de insetos e de ervas daninhas, os pesticidas tem vindo a ser usados com maior frequência, tendo-se assistido a uma contaminação dos solos e águas subterrâneas, causando deste modo um risco para a saúde dos seres vivos. Neste sentido, vários fabricantes de pesticidas estão a desenvolver novas formulações contendo pesticidas encapsulados em nanopartículas como modo de aumentar a sua solubilidade em água, biodisponibilidade, volatilidade, estabilidade e eficácia. tendo por objetivo um desenvolvimento sustentável. Neste trabalho, procedeu-se ao estudo do encapsulamento do herbicida Oxadiargil (5-terc-butil-3-[2,4-dicloro-5-(2-propiniloxi)fenil]-1,3,4-oxadiazol-2(3H)-ona) com a 2-hidroxipropil-β-ciclodextrina (HP-β-CD). O estudo da formação do complexo de inclusão Oxadiargil - HP-β-CD foi realizado em diferentes meios, água desionizada, tampão acetato pH = 3,46 e pH = 5,34 e tampão fosfato pH = 7,45, com o objetivo de determinar e comparar a sua constante de estabilidade. Verificou-se, em qualquer dos casos, a ocorrência de uma relação linear entre o aumento da solubilidade do Oxadiargil e o aumento da concentração de HP-β-CD, com um declive inferior a um, o que indicia a formação de um complexo na proporção estequiométrica de 1:1. Os resultados obtidos permitiram concluir que o processo de complexação Oxadiargil - HP-β-CD não é muito influenciado pela constituição e pelo pH do meio. De facto, as constantes de estabilidade obtidas para a água desionizada e soluções-tampão pH = 3,46, pH = 5,34 e pH = 7,45 foram de 919 ± 25, 685 ± 13, 623 ± 17 e 753 ± 9, respetivamente. A solubilidade do complexo obtido nos estudos realizados, em diferentes meios, é cerca de 23 a 32 vezes superior à observada para o Oxadiargil livre. De forma a caracterizar o complexo Oxadiargil - HP-β-CD procedeu-se à sua síntese utilizando o método de “kneading”. O composto obtido foi caracterizado por Ressonância Magnética Nuclear (RMN) tendo-se confirmado a formação de um complexo de inclusão na proporção estequiométrica de 1:1. O complexo obtido é mais solúvel e porventura mais estável quimicamente. O encapsulamento permite uma redução da aplicação dos pesticidas diminuindo assim os custos e o impacto negativo no ambiente. Com a nanotecnologia é possível a libertação controlada dos pesticidas, aumentando a sua eficácia e fornecendo os meios necessários para um desenvolvimento sustentável.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

TEA: Timing and Energy Aware compression architecture for Efficient Configuration in CGRAs

Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

Energy analysis of Multi-legged Locomotion Systems

4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

Energy Harvesting for Autonomous Underwater Vehicles

In this study, energy production for autonomous underwater vehicles is investigated. This project is part of a bigger project called TURTLE. The autonomous vehicles perform oceanic researches at seabed for which they are intended to be kept operational underwater for several months. In order to ful l a long-term underwater condition, powerful batteries are combined with \micro- scale" energy production on the spot. This work tends to develop a system that generates power up to a maximum of 30 W. Latter energy harvesting structure consists basically of a turbine combined with a generator and low-power electronics to adjust the achieved voltage to a required battery charger voltage. Every component is examined separately hence an optimum can be de ned for all, and subsequently also an overall optimum. Di erent design parameters as e.g. number of blades, solidity ratio and cross-section area are compared for di erent turbines, in order to see what is the most feasible type. Further, a generator is chosen by studying how ux distributions might be adjusted to low velocities, and how cogging torque can be excluded by adapted designs. Low-power electronics are con gured in order to convert and stabilize heavily varying three-phase voltages to a constant, recti ed voltage which is usable for battery storage. Clearly, di erent component parameters as maximum power and torque are matched here to increase the overall power generation. Furthermore an overall maximum power is set up for achieving a maximum power ow at load side. Due to among others typical low velocities of about 0.1 to 0.5 m/s, and constructing limits of the prototype, the vast range of components is restricted to only a few that could be used. Hence, a helical turbine is combined in a direct drive mode to a coreless-stator axial- ux permanent-magnet generator, from which the output voltage is adjusted subsequently by a recti er, impedance matching unit, upconverter circuit and an overall control unit to regulate di erent component parameters. All these electronics are combined in a closed-loop design to involve positive feedback signals. Furthermore a theoretical con guration for the TURTLE vehicle is described in this work and a solution is proposed that might be implemented, for which several design tests are performable in a future study.

Controlo inteligente de um Sistema de Levitação Magnética

A levitação magnética tem sido um tema bastante investigado sobretudo devido à sua utilização em sistemas ferroviários de transportes. É o método ideal quando existe a necessidade em aplicações de restringir do contacto físico, ou a conveniência, em termos energéticos, de eliminar o atrito. O princípio de funcionamento é simples, um eletroíman cria uma força sobre um objeto ferromagnético que contraria a gravidade. Contudo um sistema de levitação por atração é instável e não linear, o que significa a necessidade de implementar um controlador para satisfazer as características de estabilidade desejadas. Ao longo deste projeto serão descritos os procedimentos teóricos e práticos que foram tomados na criação de um sistema de levitação eletromagnética. Desde a conceção física do sistema, como escolha do sensor, condicionamento de sinal ou construção do eletroíman, até aos procedimentos matemáticos que permitiram a modelação do sistema e criação de controladores. Os controladores clássicos, como o PID ou em avanço de fase, foram projetados através da técnica do Lugar Geométrico de Raízes. No projeto do controlador difuso, pelo contrário não se fez uso da modelação do sistema ou de qualquer relação matemática entre as variáveis. A utilização desta técnica de controlo destacou-se pela usa simplicidade e rapidez de implementação, fornecendo um bom desempenho ao sistema. Na parte final do relatório os resultados obtidos pelos diferentes métodos de controlo são analisados e apresentadas as respetivas conclusões. Estes resultados revelam que para este sistema, relativamente aos outros métodos, o controlador difuso apresenta o melhor desempenho tanto ao nível da resposta transitória, como em regime permanente.

Energy-aware Task Allocation onto Unrelated Heterogeneous Multicore Platform for Mixed Criticality Systems

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Energy-efficient MAC protocols for WBANs: Opportunities and challenges

Wireless body area networks (WBANs) are expected to play a significant role in smart healthcare systems. One of the most important attributes of WBANs is to increase network lifetime by introducing novel and low-power techniques on the energy-constrained sensor nodes. Medium access control (MAC) protocols play a significant role in determining the energy consumption in WBANs. Existing MAC protocols are unable to accommodate communication requirements in WBANs. There is a need to develop novel, scalable and reliable MAC protocols that must be able to address all these requirements in a reliable manner. In this special issue, we attracted high quality research and review papers on the recent advances in MAC protocols for WBANs.

Dynamic stability metrics for the container loading problem

The Container Loading Problem (CLP) literature has traditionally evaluated the dynamic stability of cargo by applying two metrics to box arrangements: the mean number of boxes supporting the items excluding those placed directly on the floor (M1) and the percentage of boxes with insufficient lateral support (M2). However, these metrics, that aim to be proxies for cargo stability during transportation, fail to translate real-world cargo conditions of dynamic stability. In this paper two new performance indicators are proposed to evaluate the dynamic stability of cargo arrangements: the number of fallen boxes (NFB) and the number of boxes within the Damage Boundary Curve fragility test (NB_DBC). Using 1500 solutions for well-known problem instances found in the literature, these new performance indicators are evaluated using a physics simulation tool (StableCargo), replacing the real-world transportation by a truck with a simulation of the dynamic behaviour of container loading arrangements. Two new dynamic stability metrics that can be integrated within any container loading algorithm are also proposed. The metrics are analytical models of the proposed stability performance indicators, computed by multiple linear regression. Pearson’s r correlation coefficient was used as an evaluation parameter for the performance of the models. The extensive computational results show that the proposed metrics are better proxies for dynamic stability in the CLP than the previous widely used metrics.