REXIB: Remote Experiments Interface Builder

Remote Experimentation is an educational resource that allows teachers to strengthen the practical contents of science & engineering courses. However, building up the interfaces to remote experiments is not a trivial task. Although teachers normally master the practical contents addressed by a particular remote experiment they usually lack the programming skills required to quickly build up the corresponding web interface. This paper describes the automatic generation of experiment interfaces through a web-accessible Java application. The application displays a list of existent modules and once the requested modules have been selected, it generates the code that enables the browser to display the experiment interface. The tools? main advantage is enabling non-tech teachers to create their own remote experiments.

Suporte à computação paralela e distribuída em Java: distribuição e execução de trabalho

Nos últimos anos começaram a ser vulgares os computadores dotados de multiprocessadores e multi-cores. De modo a aproveitar eficientemente as novas características desse hardware começaram a surgir ferramentas para facilitar o desenvolvimento de software paralelo, através de linguagens e frameworks, adaptadas a diferentes linguagens. Com a grande difusão de redes de alta velocidade, tal como Gigabit Ethernet e a última geração de redes Wi-Fi, abre-se a oportunidade de, além de paralelizar o processamento entre processadores e cores, poder em simultâneo paralelizá-lo entre máquinas diferentes. Ao modelo que permite paralelizar processamento localmente e em simultâneo distribuí-lo para máquinas que também têm capacidade de o paralelizar, chamou-se “modelo paralelo distribuído”. Nesta dissertação foram analisadas técnicas e ferramentas utilizadas para fazer programação paralela e o trabalho que está feito dentro da área de programação paralela e distribuída. Tendo estes dois factores em consideração foi proposta uma framework que tenta aplicar a simplicidade da programação paralela ao conceito paralelo distribuído. A proposta baseia-se na disponibilização de uma framework em Java com uma interface de programação simples, de fácil aprendizagem e legibilidade que, de forma transparente, é capaz de paralelizar e distribuir o processamento. Apesar de simples, existiu um esforço para a tornar configurável de forma a adaptar-se ao máximo de situações possível. Nesta dissertação serão exploradas especialmente as questões relativas à execução e distribuição de trabalho, e a forma como o código é enviado de forma automática pela rede, para outros nós cooperantes, evitando assim a instalação manual das aplicações em todos os nós da rede. Para confirmar a validade deste conceito e das ideias defendidas nesta dissertação foi implementada esta framework à qual se chamou DPF4j (Distributed Parallel Framework for JAVA) e foram feitos testes e retiradas métricas para verificar a existência de ganhos de performance em relação às soluções já existentes.

Development of procedures for the simulation of atmospheric flows over complex terrain, using OpenFOAM

The main purpose of this work was the development of procedures for the simulation of atmospheric ows over complex terrain, using OpenFOAM. For this aim, tools and procedures were developed apart from this code for the preprocessing and data extraction, which were thereafter applied in the simulation of a real case. For the generation of the computational domain, a systematic method able to translate the terrain elevation model to a native OpenFOAM format (blockMeshDict) was developed. The outcome was a structured mesh, in which the user has the ability to de ne the number of control volumes and its dimensions. With this procedure, the di culties of case set up and the high computation computational e ort reported in literature associated to the use of snappyHexMesh, the OpenFOAM resource explored until then for the accomplishment of this task, were considered to be overwhelmed. Developed procedures for the generation of boundary conditions allowed for the automatic creation of idealized inlet vertical pro les, de nition of wall functions boundary conditions and the calculation of internal eld rst guesses for the iterative solution process, having as input experimental data supplied by the user. The applicability of the generated boundary conditions was limited to the simulation of turbulent, steady-state, incompressible and neutrally strati ed atmospheric ows, always recurring to RaNS (Reynolds-averaged Navier-Stokes) models. For the modelling of terrain roughness, the developed procedure allowed to the user the de nition of idealized conditions, like an uniform aerodynamic roughness length or making its value variable as a function of topography characteristic values, or the using of real site data, and it was complemented by the development of techniques for the visual inspection of generated roughness maps. The absence and the non inclusion of a forest canopy model limited the applicability of this procedure to low aerodynamic roughness lengths. The developed tools and procedures were then applied in the simulation of a neutrally strati ed atmospheric ow over the Askervein hill. In the performed simulations was evaluated the solution sensibility to di erent convection schemes, mesh dimensions, ground roughness and formulations of the k - ε and k - ω models. When compared to experimental data, calculated values showed a good agreement of speed-up in hill top and lee side, with a relative error of less than 10% at a height of 10 m above ground level. Turbulent kinetic energy was considered to be well simulated in the hill windward and hill top, and grossly predicted in the lee side, where a zone of ow separation was also identi ed. Despite the need of more work to evaluate the importance of the downstream recirculation zone in the quality of gathered results, the agreement between the calculated and experimental values and the OpenFOAM sensibility to the tested parameters were considered to be generally in line with the simulations presented in the reviewed bibliographic sources.

Desenvolvimento de um Code Set para a escrita manual baseado na classificação internacional de funcionalidade versão crianças e jovens

Compreender a funcionalidade de uma criança é um desafio persistente em contextos de saúde e educação. Na tentativa de superar esse desafio, em 2007, a Organização Mundial de Saúde desenvolveu a Classificação Internacional de Funcionalidade, Incapacidade e Saúde para Crianças e Jovens (CIF-CJ) como o primeiro sistema de classificação universal para documentar a saúde e funcionalidade da criança. Apesar de a CIF-CJ não ser um instrumento de avaliação e intervenção, tem, no entanto, a capacidade de servir de enquadramento para o desenvolvimento de ferramentas adaptadas às necessidades dos seus utilizadores. Considerando que no contexto escolar, a escrita manual encontra-se entre as atividades mais requeridas para a participação plena de uma criança, parece ser pertinente a definição de um conjunto de códigos destinados a caracterizar o perfil de funcionalidade de uma criança, no que se refere à escrita manual. O objetivo deste estudo foi, pois, o desenvolvimento de um conjunto preliminar de códigos baseado na CIF-CJ que possa vir a constituir um code set para a escrita manual. Dada a complexidade do tema e atendendo a que se pretende alcançar consenso entre os especialistas sobre quais as categorias da CIF-CJ que devem ser consideradas, optou-se pela utilização da técnica de Delphi. A escolha da metodologia seguiu a orientação dos procedimentos adotados pelo projeto Core Set CIF. De dezoito profissionais contactados, obtiveram-se respostas de sete terapeutas ocupacionais com experiência em pediatria, que participaram em todas as rondas. No total, três rondas de questionários foram realizadas para atingir um consenso, com um nível de concordância, previamente definido, de 70%. Deste estudo resultou um conjunto preliminar de códigos com 54 categorias da CIF-CJ (16 categorias de segundo nível, 14 categorias de terceiro nível e uma categoria de quarto nível), das quais 31 são categorias das funções do corpo, uma categoria das estruturas do corpo, 12 categorias de atividades e participação e 10 categorias de fatores ambientais. Este estudo é um primeiro passo para o desenvolvimento de um code set para a escrita manual baseado na CIF-CJ , sendo claramente necessário a realização de mais pesquisas no contexto do desenvolvimento e da validação deste code set.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

MASCEM Restructuring: Ontologies For Scenarios Generation in Power Systems Simulators

The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Remuneration Structure Definition for Distributed Generation Units and Demand Response Participants Aggregation

The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

Impact of Distributed Generation in the Transmission System Expansion Planning

In this work, the impact of distributed generation in the transmission expansion planning will be simulated through the performance of an optimization process for three different scenarios: the first without distributed generation, the second with distributed generation equivalent to 1% of the load, and the third with 5% of distributed generation. For modeling the expanding problem the load flow linearized method using genetic algorithms for optimization has been chosen. The test circuit used is a simplification of the south eastern Brazilian electricity system with 46 buses.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.