Design of a sea-level tsunami detection network for the Gulf of Cadiz

The devastating impact of the Sumatra tsunami of 26 December 2004, raised the question for scientists of how to forecast a tsunami threat. In 2005, the IOC-UNESCO XXIII assembly decided to implement a global tsunami warning system to cover the regions that were not yet protected, namely the Indian Ocean, the Caribbean and the North East Atlantic, the Mediterranean and connected seas (the NEAM region). Within NEAM, the Gulf of Cadiz is the more sensitive area, with an important record of devastating historical events. The objective of this paper is to present a preliminary design for a reliable tsunami detection network for the Gulf of Cadiz, based on a network of sea-level observatories. The tsunamigenic potential of this region has been revised in order to define the active tectonic structures. Tsunami hydrodynamic modeling and GIS technology have been used to identify the appropriate locations for the minimum number of sea-level stations. Results show that 3 tsunameters are required as the minimum number of stations necessary to assure an acceptable protection to the large coastal population in the Gulf of Cadiz. In addition, 29 tide gauge stations could be necessary to fully assess the effects of a tsunami along the affected coasts of Portugal, Spain and Morocco.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Garantia de qualidade de serviço (QOS) em arquitecturas MPLS

Os prestadores de serviços de telecomunicações e operadores de telecomunicações deparam-se com um aumento exponencial das necessidades de largura de banda. A evolução e massificação dos serviços Internet e Intranet pelos serviços públicos e privados deixaram de ser uma mera adaptação do protocolo TCP, à qualidade da ligação sendo uma necessidade a diferenciação do tráfego. As metodologias que asseguram uma qualidade de serviço no âmbito dos fornecedores de serviços internet são a forma de garantir uma qualidade de serviço adequada a cada tipo de tráfego. Estas metodologias são suportadas pela rede IP MPLS dos diversos operadores de telecomunicações no transporte dos diversos serviços dos seus clientes empresarias e domésticos no acesso à internet dos diversos serviços públicos de dados e voz e nas redes virtuais privadas. Os portais aplicacionais são a interface directa com o cliente para definição dos acordos de nível de serviço “Service Level Agreements” e a sua associação à especificação dos níveis de serviço “Service Level Specification”, para posterior relação com a definição de métricas adequadas à qualidade de serviço acordada com o cliente no desenho dos serviços de uma rede IP “MultiProtocol Label Switch”. A proposta consiste em criar uma metodologia para mapear as necessidades de serviços dos clientes em SLAs e registá-los numa base de dados, separando claramente a qualidade do serviço vista na óptica do operador em: arquitectura de rede de transporte, arquitectura do serviço e arquitectura de monitoria. Estes dados são mapeados em parâmetros e especificações de implementação dos serviços de suporte ao negócio do operador tendo em vista a criação de um “Work Flow” fim a fim. Paralelamente define-se os serviços a disponibilizar comercialmente, o conjunto de serviços suportados pela rede e tecnologia IP MPLS com a parametrização de ”Quality of Service Assurance” adequada a cada um, cria-se uma arquitectura de rede de suporte ao transporte base entre os diversos equipamentos agregadores de acessos através do “Backbone”, define-se uma arquitectura de suporte para cada tipo de serviço independente da arquitectura de transporte. Neste trabalho implementam-se algumas arquitecturas de QoS estudadas no IP MPLS em simuladores disponibilizados pela comunidade “Open Source” e analisamos as vantagens de desvantagens de cada uma. Todas as necessidades são devidamente equacionadas, prevendo o seu crescimento, desempenho, estabelecendo regras de distribuição de largura de banda e análise de desempenho, criando redes escaláveis e com estimativas de crescimento optimistas. Os serviços são desenhados de forma a adaptarem-se à evolução das necessidades aplicacionais, ao crescimento do número de utilizadores e evolução do próprio serviço.

Representações dos técnicos de intervenção precoce sobre as famílias e práticas de IP em contexto rural e urbano

O presente estudo visou caraterizar as representações que técnicos de intervenção precoce têm sobre famílias que vivem em meio rural e em meio urbano que recebem apoio das equipas. Foram realizadas entrevistas semi-diretivas, os participantes e entrevistados foram dez docentes com intervenção educativa nas equipas, cinco em apoio direto a famílias de meio rural e cinco a realizar intervenções com famílias de meio urbano. Deste estudo resultaram vários dados qualitativos que depois de analisados e discutidos, levaram a diversas conclusões que vem dar respostas às questões e problemática iniciais. As famílias inseridas nestes contextos têm características que as diferenciam; habilitações, recursos, necessidades e comportamentos em comunidade. Tem aspetos culturais que influenciam as suas atitudes, participação e autonomia e são ou não decisivas no desenvolvimento da criança. Em contexto rural as famílias apresentam um maior número de necessidades comparativamente às famílias de meio urbano. As maiores necessidades das famílias em contexto rural situam-se nas questões financeiras, de formação e apoio técnico e especializado. As maiores necessidades das famílias de contexto urbano situam-se ao nível do fraco apoio familiar e das redes sociais. As necessidades comuns situam-se nas necessidades de informação e promoção da autonomia e competências parentais. As visitas e intervenções domiciliares podem permitir melhorar a identificação das necessidades e recursos das famílias e compreender melhor os critérios de referência de algumas crianças. As oportunidades de aprendizagem são maiores nestes encontros em domicílio, estão presentes em muitos casos, elementos da família alargada, que muitas vezes tem um papel fundamental na educação e estimulação destas crianças. Os docentes de IP em intervenção em contexto urbano, comparativamente com os docentes inseridos em contexto rural, apoiam famílias que na generalidade abrangem áreas profissionais mais vantajosas financeiramente. Estas famílias terão á partida melhores condições para aceder a mais recursos e apoios. Nos dois contextos existe uma necessidade comum, falta de informação e alguma autonomia e competências parentais em relação ao crescimento das crianças. A realização de iii encontros de pais ou criação de grupos de pais que tenham por base a partilha de experiencias e informação, estão planeadas mas não são uma realidade nestas equipas. Nas práticas de qualidade, o profissional deve atuar nos contextos naturais como, a família, ou a comunidade, mas pode incluir também rotinas, brincadeiras, festas etc. cenários que facilitem o dia-a-dia. As famílias têm contextos e rotinas próprias que os profissionais devem identificar, os dados que recolhemos indicam essa necessidade de proceder a avaliação mais atenta das necessidades das famílias. As práticas recomendadas e o enquadramento legislativo são tidos em conta pelos docentes e profissionais das equipas, os recursos documentais são na sua maioria comuns, a todas as equipas participantes, seguindo as orientações e documentos/minutas facultadas pela comissão coordenadora do SNIPI (Sistema Nacional de Intervenção Precoce na Infância) Apesar das recomendações teóricas para práticas de qualidade centradas na família, verificamos que estas fazem parte das preocupações destes docentes, mas nem sempre são implementadas. A problemática da criança parece ser ainda o ponto mais importante dos programas e planos de intervenção e mesmo o critério decisivo para delinear a duração e frequência das intervenções, seja em contexto urbano ou rural. - ABSTRACT This study aimed to characterize the families of rural and urban areas that receive support from Early Intervention Teams. It has been proposed yet whether professionals IP suit their practices to the characteristics of these families and communities integrated in different cultural contexts. Interviews were conducted semidirective, participants were ten respondents and teachers with educational intervention teams, five in direct support to families in rural areas and five interventions with families in urban areas. This study resulted in a number of qualitative data that then analyzed and discussed, led to several conclusions that comes to answer the questions and problems early. The families included in these contexts have characteristics that differentiate them; qualifications, resources, needs and behaviors in the community. Has cultural aspects that influence their attitudes, participation and autonomy and are not decisive in the development of the child. In the rural households have a greater number of needs compared to urban families. The greatest needs of families in rural settings are located in financial matters, training and technical support and expertise. The greatest needs of the urban households are located at the level of weak family support and social networks. Common needs lie in information needs and promoting autonomy and parenting skills. The home visits and interventions may allow improved identification of needs and resources of families and understand the benchmarks of some children. Learning opportunities are greater in these meetings at home, are present in many cases, elements of the extended family, which often plays a key role in education and stimulation of these children. Teachers IP intervention in the urban compared with rural teachers placed in context, support families in general include professional areas more financially advantageous. These families will have better starting conditions for access to more resources and support. In both contexts there is a common need, lack of information and some autonomy and parenting skills in relation to the growth of children. The meetings of parents or creating parent groups that are based on the sharing of information and experiences are planned but are not a reality in these teams. In quality practices, the professional must act in natural contexts like the family or the community, but may also include routines, jokes, and parties’ etc. scenarios that v facilitate the day-to-day. Families have their own contexts and routines that professionals should identify, collect the data indicate that the need for more careful assessment of the needs of families. Best practices and legislative environment are taken into account by teachers and professional teams, the documentary resources are mostly common to all participating teams, following the guidelines and documents / drafts provided by the coordinating committee SNIPI (National Intervention Early Childhood) Despite the theoretical recommendations for quality practices family-centered, we see that these are part of the concerns of teachers, but are not always implemented. The issue of child seems to be still the most important programs and plans and even the decisive criterion for delineating the duration and frequency of interventions whether in urban or rural.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

Reentrant Phase Diagram of Network Fluids

We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Maximum penetration of microgeneration photovoltaic panels in distribution network

In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking 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.

Optimal location of gas supply units in natural gas system network

Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.