Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Fuzzy clustering applied to a demand response model in a smatr grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Investment focused strategies in electricity markets using the ITEM-game simulator

This paper presents a methodology to establish investment and trading strategies of a power generation company. These strategies are integrated in the ITEM-Game simulator in order to test their results when played against defined strategies used by other players. The developed strategies are focused on investment decisions, although trading strategies are also implemented to obtain base case results. Two cases are studied considering three players with the same trading strategy. In case 1, all players also have the same investment strategy driven by a market target share. In case 2, player 1 has an improved investment strategy with a target share twice of the target of players 2 and 3. Results put in evidence the influence of the CO2 and fuel prices in the company investment decision. It is also observed the influence of the budget constraint which might prevent the player to take the desired investment decision.

A PV panel simulator based on a two quadrant DC/DC power converter with a sliding mode controller

The use of a solar photovoltaic (PV) panel simulator can be a valued tool for the design and evaluation of the several components of a photovoltaic system. This simulator is based on power electronic converter controlled in such a way that will behave as a PV panel. Thus, in this paper a PV panel simulator based on a two quadrant DC/DC power converter is proposed. This topology will allow to achieve fast responses, like suddenly changes in the irradiation and temperature. To control the power converter it will be used a fast and robust sliding mode controller. Therefore, with the proposed system I-V curve simulation of a PV panel is obtained. Experimental results from a laboratory prototype are presented in order to confirm the theoretical operation.

Endocrine disruptors mixtures: the real scenario of human exposure

Endocrine disrupting chemicals (EDCs) are exogenous agents that have the ability to interfere with/or mimic estrogenic hormones and, therefore can simultaneously and differentially trigger specific signaling pathways responsible for the nature and magnitude of biological responses in diverse cell types. Human exposure to EDCs, particularly at low-doses, is ubiquitous, persistent and occurs in complex mixtures. These compounds can bioaccumulate in lipid compartments of tissues forming a mixed “body burden” of contaminants of different origins. Although the independent action of chemicals has been considered the main principle in EDCs mixture toxicity, several effects cannot be predicted when analyzing single compounds individually. Based in a revision of the literature, focused in studies that evaluated EDCs mixtures, we hypothesize the scenario of a pregnant woman environmentally exposed to three different EDCs as a potential real scenario of human exposure supported by data describing where exposure to these compounds occur.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Quantifying chaos for ecological stoichiometry

The theory of ecological stoichiometry considers ecological interactions among species with different chemical compositions. Both experimental and theoretical investigations have shown the importance of species composition in the outcome of the population dynamics. A recent study of a theoretical three-species food chain model considering stoichiometry [B. Deng and I. Loladze, Chaos 17, 033108 (2007)] shows that coexistence between two consumers predating on the same prey is possible via chaos. In this work we study the topological and dynamical measures of the chaotic attractors found in such a model under ecological relevant parameters. By using the theory of symbolic dynamics, we first compute the topological entropy associated with unimodal Poincareacute return maps obtained by Deng and Loladze from a dimension reduction. With this measure we numerically prove chaotic competitive coexistence, which is characterized by positive topological entropy and positive Lyapunov exponents, achieved when the first predator reduces its maximum growth rate, as happens at increasing delta(1). However, for higher values of delta(1) the dynamics become again stable due to an asymmetric bubble-like bifurcation scenario. We also show that a decrease in the efficiency of the predator sensitive to prey's quality (increasing parameter zeta) stabilizes the dynamics. Finally, we estimate the fractal dimension of the chaotic attractors for the stoichiometric ecological model.

(Virtual) Agents for running electricity markets

This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.

Tsunami vulnerability assessment of Casablanca-Morocco using numerical modelling and GIS tools

Earthquakes and tsunamis along Morocco's coasts have been reported since historical times. The threat posed by tsunamis must be included in coastal risk studies. This study focuses on the tsunami impact and vulnerability assessment of the Casablanca harbour and surrounding area using a combination of tsunami inundation numerical modelling, field survey data and geographic information system. The tsunami scenario used here is compatible with the 1755 Lisbon event that we considered to be the worst case tsunami scenario. Hydrodynamic modelling was performed with an adapted version of the Cornell Multigrid Coupled Tsunami Model from Cornell University. The simulation covers the eastern domain of the Azores-Gibraltar fracture zone corresponding to the largest tsunamigenic area in the North Atlantic. The proposed vulnerability model attempts to provide an insight into the tsunami vulnerability of building stock. Results in the form of a vulnerability map will be useful for decision makers and local authorities in preventing the community resiliency for tsunami hazards.

Deuterium NMR Study of Orientational Order in Cellulosic Network Microfibers

Deuterium NMR was used to investigate the orientational order in a composite cellulosic formed by liquid crystalline acetoxypropylcellulose (A PC) and demented nematic 4'-penty1-4-cyanobiphenyl (5CB-4 alpha d(2)) with the per centage of 85% A PC by weight Three forms of the composite including electro spun microfibers, thin film and bulk samples were analyzed The NMR results initially suggest two distinct scenarios, one whet e the 503-alpha d(2), is confined to small droplets with dimensions smaller than the magnetic coherence length and the other where the 503-alpha d(2) molecules arc aligned with the A PC network chains Polarized optical microscopy (POW from thin film samples along with all the NMR results show the presence of 5CB-alpha d(2) droplets in the composite systems with a nematic wetting layer at the APC-5CB-alpha d(2) interface that experiences and order disorder transition driven by the polymer network N-I transition The characterization of the APC network I-N transition shows a pronounced subcritical behavior within a heterogeneity scenario.

A flexible side information generation framework for distributed video coding

One of the most efficient approaches to generate the side information (SI) in distributed video codecs is through motion compensated frame interpolation where the current frame is estimated based on past and future reference frames. However, this approach leads to significant spatial and temporal variations in the correlation noise between the source at the encoder and the SI at the decoder. In such scenario, it would be useful to design an architecture where the SI can be more robustly generated at the block level, avoiding the creation of SI frame regions with lower correlation, largely responsible for some coding efficiency losses. In this paper, a flexible framework to generate SI at the block level in two modes is presented: while the first mode corresponds to a motion compensated interpolation (MCI) technique, the second mode corresponds to a motion compensated quality enhancement (MCQE) technique where a low quality Intra block sent by the encoder is used to generate the SI by doing motion estimation with the help of the reference frames. The novel MCQE mode can be overall advantageous from the rate-distortion point of view, even if some rate has to be invested in the low quality Intra coding blocks, for blocks where the MCI produces SI with lower correlation. The overall solution is evaluated in terms of RD performance with improvements up to 2 dB, especially for high motion video sequences and long Group of Pictures (GOP) sizes.

Tuning Iris Recognition for Noisy Images

The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

Simulação interactiva do mercado de energia eléctrica

A área de comercialização de energia eléctrica conheceu uma profunda mudança após a liberalização do sector eléctrico, que levou à criação de algumas entidades, as quais gerem os mercados de electricidade europeus. Relativamente a Portugal e Espanha, durante esse processo de liberalização, deu-se também um acordo que os levou à criação de um mercado conjunto, um mercado Ibérico (MIBEL). Dentro deste mercado estão contemplados dois operadores, sendo que um deles representa o pólo Português (OMIP) e o outro representa o pólo Espanhol (OMEL). O OMIP contempla os mercados a prazo, ou futuros, normalmente apresenta contratos de energia comercializada com durabilidade de semanas, meses, trimestres, semestres ou mesmo anos. Diariamente estes contratos poderão vencer no OMEL, que engloba os mercados, diário e intradiário. Este, ao contrário do OMIP negoceia para o dia seguinte (mercado diário) ou para uma determinada altura do dia (mercado intra diário). O mercado diário será o exemplo usado para a criação do simulador interactivo do mercado de energia eléctrica. Este será composto por diversos utilizadores (jogadores), que através de uma plataforma HTML irão investir em centrais de energia eléctrica, negociar licitações e analisar o funcionamento e resultados deste mercado. Este jogo subdividir-se-á então em 3 fases: 1. Fase de investimento; 2. Fase de venda (licitações); 3. Fase de mercado. Na fase do investimento, o jogador terá a possibilidade de adquirir unidades de geração de energia eléctrica de seis tipos de tecnologia: 1. Central a Carvão; 2. Central de Ciclo Combinado; 3. Central Hídrica; 4. Central Eólica; 5. Central Solar; 6. Central Nuclear. Com o decorrer das jogadas o jogador poderá aumentar a sua capacidade de investimento, com a venda de energia, sendo o vencedor aquele que mais saldo tiver no fim do número de jogadas previamente definidos, ou aquele que mais depressa atingir o saldo definido como limite pelo administrador do jogo. A nível pedagógico este simulador é muito interessante pois para além de o utilizador ficar a conhecer as tecnologias em causa e as vantagens e desvantagens das centrais de energia renovável e das centrais a combustíveis fósseis, este ganha igualmente uma sensibilidade para questões de nível ambiental, tais como o aumento dos gases de estufa e o degelo resultante do aquecimento global provocado por esses gases. Para além do conhecimento adquirido na parte de energia eléctrica este jogo dará a conhecer ao utilizador o funcionamento do mercado da energia eléctrica, bem como as tácticas que este poderá usar a seu favor neste tipo de mercado.

Desenfumagem em edifícios: parque de estacionamento coberto (retail - Oeiras parque)

Os parques de estacionamento surgiram da necessidade de disponibilização de espaço de parqueamento de veículos que fazem parte do quotidiano do Homem, no entanto devido ao facto de poderem ser confinados ou subterrâneos requerem a instalação de ventilação forçada (ventiladores axiais e ventiladores de impulso). Este trabalho tem como objectivo a análise, utilizando métodos de simulação numérica da ventilação forçada criada pelos ventiladores de impulso e pelos ventiladores axiais instalados num parque de estacionamento subterrâneo. Vão ser comparadas várias simulações com situações diferentes em termos de condições de fronteira, obstruções ao escoamento, etc., por forma a tirar conclusões sobre o comportamento do parque numa situação de emergência, ou seja, num incêndio. Este comportamento vai ter em conta a eficiência de evacuação dos gases libertados, as temperaturas no parque que permitem verificar onde estão localizados os gases mais quentes e os campos de velocidade do ar que permitem uma visualização do escoamento e até certo ponto a turbulência do mesmo. No final pretende-se concluir por meio de comparação com outros documentos consultados, a “confiabilidade” do software usado (FDS-Fire Dynamics Simulator) e adicionalmente tirar conclusões sobre o projecto do parque, nomeadamente sobre a necessidade de introdução de alterações.

Manutenção proactiva de sistemas AVAC com recurso aos sistemas inteligentes multiagente

Nos tempos actuais os equipamentos para Aquecimento Ventilação e Ar Condicionado (AVAC) ocupam um lugar de grande importância na concepção, desenvolvimento e manutenção de qualquer edifício por mais pequeno que este seja. Assim, surge a necessidade premente de racionalizar os consumos energéticos optimizando-os. A alta fiabilidade desejada nestes sistemas obriga-nos cada vez mais a descobrir formas de tornar a sua manutenção mais eficiente, pelo que é necessário prevenir de uma forma proactiva todas as falhas que possam prejudicar o bom desempenho destas instalações. Como tal, torna-se necessário detectar estas falhas/anomalias, sendo imprescíndivel que nos antecipemos a estes eventos prevendo o seu acontecimento num horizonte temporal pré-definido, permitindo actuar o mais cedo possível. É neste domínio que a presente dissertação tenta encontrar soluções para que a manutenção destes equipamentos aconteça de uma forma proactiva e o mais eficazmente possível. A ideia estruturante é a de tentar intervir ainda numa fase incipiente do problema, alterando o comportamento dos equipamentos monitorizados, de uma forma automática, com recursos a agentes inteligentes de diagnóstico de falhas. No caso em estudo tenta-se adaptar de forma automática o funcionamento de uma Unidade de Tratamento de Ar (UTA) aos desvios/anomalias detectadas, promovendo a paragem integral do sistema apenas como último recurso. A arquitectura aplicada baseia-se na utilização de técnicas de inteligência artificial, nomeadamente dos sistemas multiagente. O algoritmo utilizado e testado foi construído em Labview®, utilizando um kit de ferramentas de controlo inteligente para Labview®. O sistema proposto é validado através de um simulador com o qual se conseguem reproduzir as condições reais de funcionamento de uma UTA.