Celorico Wireless

Mestrado em Engenharia Informática

Modelização do despacho económico de Gás Natural

Com as variações e instabilidade dos preços do petróleo, assim como as políticas europeias para adoção de estratégias para o desenvolvimento sustentável, têm levado à procura de forma crescente de novas tecnologias e fontes de energia alternativas. Neste contexto, tem-se assistido a políticas energéticas que estimulam o aumento da produção e a utilização do gás natural, visto que é considerado uma fonte de energia limpa. O crescimento do mercado do gás natural implica um reforço significativo das redes de transporte deste combustível, quer ao nível do armazenamento e fornecimento, quer ao nível dos gasodutos e da sua gestão. O investimento em gasodutos de transporte implica grandes investimentos, que poderiam não ser remunerados da forma esperada, sendo um dos motivos para que exista em Portugal cinco distritos se veem privados deste tipo de infraestruturas. O transporte de gás natural acarreta custos elevados para os consumidores, tanto maiores quanto maior forem as quantidades de gás transacionadas e quanto maior for o percurso pelo gás natural percorrido. Assim assume especial importância a realização de um despacho de gás natural: quais as cargas que cada unidade de fornecimento de gás irá alimentar, qual a quantidade de gás natural que cada UFGs deve injetar na rede, qual o menor percurso possível para o fazer, o tipo de transporte que será utilizado? Estas questões são abordadas na presente dissertação, por forma a minimizar a função custo de transporte, diminuindo assim as perdas na rede de alta pressão e os custos de transporte que serão suportados pelos consumidores. A rede de testes adotada foi a rede nacional de transporte, constituída por 18 nós de consumos, e os tipos de transporte considerados, foram o transporte por gasoduto físico e o transporte através de gasoduto virtual – rotas de transporte rodoviário de gás natural liquefeito. Foram criados diversos cenários, baseados em períodos de inverno e verão, os diferentes cenários abrangeram de forma distinta as variáveis de forma a analisar os impactos que estas variáveis teriam no custo relativo ao transporte de gás natural. Para dar suporte ao modelo de despacho económico, foi desenvolvida uma aplicação computacional – Despacho_GN com o objetivo de despachar as quantidades de gás natural que cada UFG deveria injetar na rede, assim como apresentar os custos acumulados relativos ao transporte. Com o apoio desta aplicação foram testados diversos cenários, sendo apresentados os respectivos resultados. A metodologia elaborada para a criação de um despacho através da aplicação “Despacho_GN” demonstrou ser eficiente na obtenção das soluções, mostrando ser suficientemente rápida para realizar as simulações em poucos segundos. A dissertação proporciona uma contribuição para a exploração de problemas relacionados com o despacho de gás natural, e sugere perspectivas futuras de investigação e desenvolvimento.

QoS em WIMAX – Análise e avaliação de módulos para simulação com o ns-2

Mestrado em Engenharia Electrotécnica e de Computadores

Swordfish: an Autonomous Surface Vehicle for Network Centric Operations

The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).

Identificação das categorias mais relevantes da classificação internacional de funcionalidade, incapacidade e saúde para os terapeutas ocupacionais que exercem funções em unidades de cuidados continuados integrados

As constantes alterações das realidades sociais e epidemiológicas em associação ao envelhecimento populacional conduziram a insuficiências dos Sistemas Social e de Saúde que requerem uma reestruturação ao nível da adequação dos cuidados de saúde a prestar, pelo que, em resposta a esta necessidade foi criada a Rede Nacional de Cuidados Continuados Integrados. O presente estudo, de natureza qualitativa e carácter exploratório, tem como objectivo compreender a percepção dos Terapeutas Ocupacionais que trabalham em Unidades de Cuidados Continuados Integrados relativamente às categorias que considerem mais relevantes da Classificação Internacional da Funcionalidade, Incapacidade e Saúde, tendo sido aplicada uma entrevista a 8 profissionais a exercer funções em Unidades da Zona Norte, resultante de um processo de amostragem não probabilística e de conveniência. Como método de recolha de dados foi aplicada uma entrevista semi-estruturada, cujo guião foi construído após revisão bibliográfica, tendo por base as categorias definidas pelo modelo da Classificação Internacional da Funcionalidade, Incapacidade e Saúde e, posteriormente, analisado por um painel de peritos, tendo-se procedido à realização de uma entrevista piloto a um elemento, sem que esta contasse para a análise. A partir da análise das entrevistas realizadas procedemos à identificação das unidades de significado, tendo os conceitos sido ligados às categorias da Classificação que o representam de uma forma mais adequada, de acordo com as linking rules, tendo sido identificadas as categorias mais relevantes para os Terapeutas Ocupacionais a exercer funções em Unidades de Cuidados Continuados Integrados. Com a realização deste estudo, que pretende ser um primeiro passo para a criação de um futuro Core Set em Cuidados Continuados, foi-nos possível verificar que o maior número de categorias foram observadas no componente Actividades e Participação, tendo sido contabilizadas 70 (40,7%). Por outro lado, o componente Estruturas do corpo é o que integra menor número, contando com 19 categorias (11,05%). Assim, pensamos que a criação de um Core Set em Cuidados Continuados poderá beneficiar e facilitar a comunicação entre os profissionais destas equipas. No entanto, é importante ressalvar que a terminologia desta Classificação deverá ser utilizada de uma forma concertada com a linguagem específica da Terapia Ocupacional. Palavras-chave: Classificação Internacional da Funcionalidade, Incapacidade e Saúde, Core Set, Terapeutas Ocupacionais, Unidades de Cuidados Continuados Integrados.

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.

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.

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.