Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Utilization of remote experimentation in mobile devices for education

In this paper the authors intend to demonstrate the utilization of remote experimentation (RE) using mobile computational devices in the Science areas of the elementary school, with the purpose to develop practices that will help in the assimilation process of the subjects taught in classroom seeking to interlink them with the daily students? activities. Allying mobility with RE we intend to minimize the space-temporal barrier giving more availability and speed in the information access. The implemented architecture utilizes technologies and freely distributed softwares with open code resources besides remote experiments developed in the Laboratory of Remote Experimentation (RExLab) of Federal University of Santa Catarina (UFSC), in Brazil, through the physical computation platform of the ?open hardware of construction of our own. The utilization of open code computational tools and the integration of hardware to the 3D virtual worlds, accessible through mobile devices, give to the project an innovative face with a high potential for reproducibility and reusability.

Sistema de Torre de Refrigeração

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

Reason Maintenance Systems: Tools for Foundations-based Belief Revision

Dynamic and distributed environments are hard to model since they suffer from unexpected changes, incomplete knowledge, and conflicting perspectives and, thus, call for appropriate knowledge representation and reasoning (KRR) systems. Such KRR systems must handle sets of dynamic beliefs, be sensitive to communicated and perceived changes in the environment and, consequently, may have to drop current beliefs in face of new findings or disregard any new data that conflicts with stronger convictions held by the system. Not only do they need to represent and reason with beliefs, but also they must perform belief revision to maintain the overall consistency of the knowledge base. One way of developing such systems is to use reason maintenance systems (RMS). In this paper we provide an overview of the most representative types of RMS, which are also known as truth maintenance systems (TMS), which are computational instances of the foundations-based theory of belief revision. An RMS module works together with a problem solver. The latter feeds the RMS with assumptions (core beliefs) and conclusions (derived beliefs), which are accompanied by their respective foundations. The role of the RMS module is to store the beliefs, associate with each belief (core or derived belief) the corresponding set of supporting foundations and maintain the consistency of the overall reasoning by keeping, for each represented belief, the current supporting justifications. Two major approaches are used to reason maintenance: single-and multiple-context reasoning systems. Although in the single-context systems, each belief is associated to the beliefs that directly generated it—the justification-based TMS (JTMS) or the logic-based TMS (LTMS), in the multiple context counterparts, each belief is associated with the minimal set of assumptions from which it can be inferred—the assumption-based TMS (ATMS) or the multiple belief reasoner (MBR).

Exploring distributed computing tools through data mining tasks

Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Computational analysis of quinoxalines N,N-Dioxide and ITS Derivates

A quinoxalina e seus derivativos são uma importante classe de compostos heterocíclicos, onde os elementos N, S e O substituem átomos de carbono no anel. A fórmula molecular da quinoxalina é C8H6N2, formada por dois anéis aromáticos, benzeno e pirazina. É rara em estado natural, mas a sua síntese é de fácil execução. Modificações na estrutura da quinoxalina proporcionam uma grande variedade de compostos e actividades, tais como actividades antimicrobiana, antiparasitária, antidiabética, antiproliferativa, anti-inflamatória, anticancerígena, antiglaucoma, antidepressiva apresentando antagonismo do receptor AMPA. Estes compostos também são importantes no campo industrial devido, por exemplo, ao seu poder na inibição da corrosão do metal. A química computacional, ramo natural da química teórica é um método bem desenvolvido, utilizado para representar estruturas moleculares, simulando o seu comportamento com as equações da física quântica e clássica. Existe no mercado uma grande variedade de ferramentas informaticas utilizadas na química computacional, que permitem o cálculo de energias, geometrias, frequências vibracionais, estados de transição, vias de reação, estados excitados e uma variedade de propriedades baseadas em várias funções de onda não correlacionadas e correlacionadas. Nesta medida, a sua aplicação ao estudo das quinoxalinas é importante para a determinação das suas características químicas, permitindo uma análise mais completa, em menos tempo, e com menos custos.

Optimização do corte de chapas

O presente trabalho visa denotar a importância de ferramentas e técnicas utilizadas como apoio à tomada de decisão. Foi proposto um problema de corte cujo objectivo primordial procura minimizar o desperdício gerado resultante do processo de obtenção de um produto, utilizando um caso representativo de um produto em chapa, fabricado por uma empresa que conta três décadas de laboração contínua, proposeram-se e realizaram-se estudos no sentido de solucionar recursos causadores de desperdício. Neste trabalho aplicou-se um problema de corte bi-dimensional a uma indústria que recorre ao fabrico de produtos em chapa, por forma a minimizar o desperdício relativo ao processo utilizado. Propôs-se quatro alternativas à solução actual realizada na empresa, que passa pela disposição e combinação de vários tipos de cortes-padrão que podem ser executados nas diferentes dimensões de matéria-prima disponibilizada. Estas alternativas têm como vantagem apresentar reduções que se traduzam significativas para os custos implícitos à realização do processo produtivo. Os estudos computacionais praticados mostraram que as soluções propostas como alternativa obtiveram melhores resultados que os obtidos pela empresa, excepto num caso.

Leilão de direitos de transmissão financeiros de energia eléctrica em ambiente de mercado

Os direitos de transmissão (Transmission Rigths – TRs) correspondem, na sua essência, a contratos que conferem aos seus proprietários o direito de transmitir energia eléctrica, por um determinado caminho, a um preço fixo. Na actualidade vive-se uma era de liberalização dos mercados de energia eléctrica nos quais, no caso concreto dos mercados de TRs, os diversos agentes podem ceder os TRs que possuem a outros agentes desde que cumpram certos requisitos impostos pelo sistema na figura do seu operador de sistema (Independent System Operator – ISO). Neste sentido, o ISO oferece, aos diversos agentes do mercado, algumas ferramentas que lhes permite transaccionar, sob sua orientação, os seus respectivos TRs fazendo-se cumprir todos os requisitos indispensáveis para o efeito. A mais popular dessas ferramentas, nos principais mercados energético da actualidade, é o leilão. Com o presente trabalho de dissertação é pretendido apresentar-se um modelo para a resolução do problema inerente a um leilão de TRs em ambiente de mercado, neste caso concreto de direitos de transmissão financeiros de energia eléctrica (Financial Transmission Rigths – FTRs). Neste sentido foi desenvolvido um simulador informático (SIM_AuctFTR) que implementa um modelo para este tipo de problemas. Este trabalho foi estruturado essencialmente em três etapas com objectivos inerentes. Assim, numa primeira fase da realização deste trabalho, foi realizado um estudo de diversos conceitos e metodologias inerentes ao problema de leilão de FTRs em ambiente de mercado, suportado por uma sólida base bibliográfica. A segunda fase tratou-se do desenvolvimento do algoritmo da aplicação computacional que solucione um problema de um leilão de FTRs. O SIM_AuctFTR foi desenvolvido sobre o pressuposto da maximização dos rendimentos financeiros provenientes da atribuição dos FTRs propostos a leilão, tendo estes últimos de coabitar no sistema respeitando as restrições técnicas a que este são inerentes, mesmo na eventualidade da ocorrência de contingências de nível ‘n-1’. Por último, numa terceira fase, partindo da aplicação desenvolvida, foram realizados 4 casos de estudos com outras tantas redes eléctricas de forma a testar a robustez da ferramenta desenvolvida.

Six thinking hats for electricity markets simulation: adapting meeting tools to agent decision

In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

Engineering real-time applications with WorldFIP: tools and analysis

WorldFIP is standardised as European Norm EN 50170 - General Purpose Field Communication System. Field communication systems (fieldbuses) started to be widely used as the communication support for distributed computer-controlled systems (DCCS), and are being used in all sorts of process control and manufacturing applications within different types of industries. There are several advantages in using fieldbuses as a replacement of for the traditional point-to-point links between sensors/actuators and computer-based control systems. Indeed they concern economical ones (cable savings) but, importantly, fieldbuses allow an increased decentralisation and distribution of the processing power over the field. Typically DCCS have real-time requirements that must be fulfilled. By this, we mean that process data must be transferred between network computing nodes within a maximum admissible time span. WorldFIP has very interesting mechanisms to schedule data transfers. It explicit distinguishes to types of traffic: periodic and aperiodic. In this paper we describe how WorldFIP handles these two types of traffic, and more importantly, we provide a comprehensive analysis for guaranteeing the real-time requirements of both types of traffic. A major contribution is made in the analysis of worst-case response time of aperiodic transfer requests.

Tools for simulation output analysis

This technical report presents a description of the output data files and the tools used to validate and to extract information from the output data files generated by the Repeater-Based Hybrid Wired/Wireless Network Simulator and the Bridge-Based Hybrid Wired/Wireless Network Simulator.

Drilling delamination outcomes on glass and sisal reinforced plastics

Nowadays, fibre reinforced plastics are used in a wide variety of applications. Apart from the most known reinforcement fibres, like glass or carbon, natural fibres can be seen as an economical alternative. However, some mistrust is yet limiting the use of such materials, being one of the main reasons the inconsistency normally found in their mechanical properties. It should be noticed that these materials are more used for their low density than for their high stiffness. In this work, two different types of reinforced plates were compared: glass reinforced epoxy plate and sisal reinforced epoxy plate. For material characterization purposes, tensile and flexural tests were carried out. Main properties of both materials, like elastic modulus, tensile strength or flexural modulus, are presented and compared with reference values. Afterwards, plates were drilled under two different feed rates: low and high, with two diverse tools: twist and brad type drill, while cutting speed was kept constant. Thrust forces during drilling were monitored. Then, delamination area around the hole was assessed by using digital images that were processed using a computational platform previously developed. Finally, drilled plates were mechanically tested for bearing and open-hole resistance. Results were compared and correlated with the measured delamination. Conclusions contribute to the understanding of natural fibres reinforced plastics as a substitute to glass fibres reinforced plastics, helping on cost reductions without compromising reliability, as well as the consequence of delamination on mechanical resistance of this type of composites.