Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Videovigilância, compressão e criptografia

Mestrado em Engenharia Electrotécnica e de Computadores

Semantic social network analysis

Mestrado em Engenharia Informática

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

Outermost european regions of the atlantic area network

This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327

Multiprocessor platform using LEON3 processor

The recent advances in embedded systems world, lead us to more complex systems with application specific blocks (IP cores), the System on Chip (SoC) devices. A good example of these complex devices can be encountered in the cell phones that can have image processing cores, communication cores, memory card cores, and others. The need of augmenting systems’ processing performance with lowest power, leads to a concept of Multiprocessor System on Chip (MSoC) in which the execution of multiple tasks can be distributed along various processors. This thesis intends to address the creation of a synthesizable multiprocessing system to be placed in a FPGA device, providing a good flexibility to tailor the system to a specific application. To deliver a multiprocessing system, will be used the synthesisable 32-bit SPARC V8 compliant, LEON3 processor.

Sistema de aquisição de dados em tempo real

Neste trabalho propus-me realizar um Sistema de Aquisição de Dados em Tempo Real via Porta Paralela. Para atingir com sucesso este objectivo, foi realizado um levantamento bibliográfico sobre sistemas operativos de tempo real, salientando e exemplificando quais foram marcos mais importantes ao longo da sua evolução. Este levantamento permitiu perceber o porquê da proliferação destes sistemas face aos custos que envolvem, em função da sua aplicação, bem como as dificuldades, científicas e tecnológicas, que os investigadores foram tendo, e que foram ultrapassando com sucesso. Para que Linux se comporte como um sistema de tempo real, é necessário configura-lo e adicionar um patch, como por exemplo o RTAI ou ADEOS. Como existem vários tipos de soluções que permitem aplicar as características inerentes aos sistemas de tempo real ao Linux, foi realizado um estudo, acompanhado de exemplos, sobre o tipo de arquitecturas de kernel mais utilizadas para o fazer. Nos sistemas operativos de tempo real existem determinados serviços, funcionalidades e restrições que os distinguem dos sistemas operativos de uso comum. Tendo em conta o objectivo do trabalho, e apoiado em exemplos, fizemos um pequeno estudo onde descrevemos, entre outros, o funcionamento escalonador, e os conceitos de latência e tempo de resposta. Mostramos que há apenas dois tipos de sistemas de tempo real o ‘hard’ que tem restrições temporais rígidas e o ‘soft’ que engloba as restrições temporais firmes e suaves. As tarefas foram classificadas em função dos tipos de eventos que as despoletam, e evidenciando as suas principais características. O sistema de tempo real eleito para criar o sistema de aquisição de dados via porta paralela foi o RTAI/Linux. Para melhor percebermos o seu comportamento, estudamos os serviços e funções do RTAI. Foi dada especial atenção, aos serviços de comunicação entre tarefas e processos (memória partilhada e FIFOs), aos serviços de escalonamento (tipos de escalonadores e tarefas) e atendimento de interrupções (serviço de rotina de interrupção - ISR). O estudo destes serviços levou às opções tomadas quanto ao método de comunicação entre tarefas e serviços, bem como ao tipo de tarefa a utilizar (esporádica ou periódica). Como neste trabalho, o meio físico de comunicação entre o meio ambiente externo e o hardware utilizado é a porta paralela, também tivemos necessidade de perceber como funciona este interface. Nomeadamente os registos de configuração da porta paralela. Assim, foi possível configura-lo ao nível de hardware (BIOS) e software (módulo do kernel) atendendo aos objectivos do presente trabalho, e optimizando a utilização da porta paralela, nomeadamente, aumentando o número de bits disponíveis para a leitura de dados. No desenvolvimento da tarefa de hard real-time, foram tidas em atenção as várias considerações atrás referenciadas. Foi desenvolvida uma tarefa do tipo esporádica, pois era pretendido, ler dados pela porta paralela apenas quando houvesse necessidade (interrupção), ou seja, quando houvesse dados disponíveis para ler. Desenvolvemos também uma aplicação para permitir visualizar os dados recolhidos via porta paralela. A comunicação entre a tarefa e a aplicação é assegurada através de memória partilhada, pois garantindo a consistência de dados, a comunicação entre processos do Linux e as tarefas de tempo real (RTAI) que correm ao nível do kernel torna-se muito simples. Para puder avaliar o desempenho do sistema desenvolvido, foi criada uma tarefa de soft real-time cujos tempos de resposta foram comparados com os da tarefa de hard real-time. As respostas temporais obtidas através do analisador lógico em conjunto com gráficos elaborados a partir destes dados, mostram e comprovam, os benefícios do sistema de aquisição de dados em tempo real via porta paralela, usando uma tarefa de hard real-time.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Influence of network effects on the diffusion of information systems: the case of open source

Doutoramento em Gestão

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Characterizing the timing behaviour of power-line communication by means of simulation

Although power-line communication (PLC) is not a new technology, its use to support communication with timing requirements is still the focus of ongoing research. Recently, a new infrastructure was presented, intended for communication using power lines from a central location to geographically dispersed nodes using inexpensive devices. This new infrastructure uses a two-level hierarchical power-line system, together with an IP-based network. Within this infrastructure, in order to provide end-toend communication through the two levels of the powerline system, it is necessary to fully understand the behaviour of the underlying network layers. The masterslave behaviour of the PLC MAC, together with the inherent dynamic topology of power-line networks are important issues that must be fully characterised. Therefore, in this paper we present a simulation model which is being used to study and characterise the behaviour of power-line communication.