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Orientador: Walmir de Freitas Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-27T12:29:12Z (GMT). No. of bitstreams: 1 Pinto_AdrianoCosta_M.pdf: 2073375 bytes, checksum: e1c68a8598816ca4909e74ba53dee76d (MD5) Previous issue date: 2015 / Resumo: A crescente demanda por energia elétrica, por vezes em ritmo mais acelerado que os investimentos em expansão das redes de distribuição, tem levado as distribuidoras a operarem próximo aos limites aceitáveis, o que torna toda a operação da rede mais complexa. Um dos desafios atuais é estabelecer um efetivo controle de tensão e potência reativa (Volt/var) na rede buscando melhorar o nível de operação e de eficiência energética da rede. Muitas propostas para encontrar a solução do problema partiram de uma abordagem de forma desacoplada: o controle de tensão e o controle de potência reativa foram resolvidos separadamente. Neste trabalho, porém, foram estudados métodos de solução do problema visando à segurança da operação e à otimização global dos recursos da rede de modo integrado, ou seja, considerando a dependência entre tensão e potência reativa. Na literatura, grande parte dos trabalhos reportam soluções baseadas em modelos elétricos da rede de distribuição. Os métodos estudados nessa dissertação são baseados em técnicas de aprendizado de máquina com o objetivo de construir um modelo capaz de utilizar apenas as medições de tensão e corrente provenientes dos medidores instalados ao longo da rede e obter o melhor despacho dos ajustes dos dispositivos de controle, sem a necessidade de um modelo elétrico do sistema. A grande vantagem de não depender dos dados e modelo elétrico do sistema está associada às imprecisões tipicamente existentes na base de dados elétricos das concessionárias de distribuição de energia elétrica. Neste contexto, primeiramente, propõe-se o uso de aprendizado por reforço, no qual o agente interage com a rede enquanto acumula experiência de operação dos controles. A implementação através do algoritmo Q-Learning permite a construção de um operador virtual da rede de distribuição a partir dos dados provenientes dos medidores instalados em determinadas barras do sistema, dos quais é extraído o estado corrente da condição de carregamento da rede. Os principais aspectos da aplicação do método ao problema de controle integrado de tensão e potência reativa são simulados em redes típicas e as capacidades de aplicação prática ao cenário atual do sistema elétrico são discutidas. Em uma segunda etapa, propõe-se utilizar um algoritmo de aprendizado supervisionado através de Máquinas de Vetores de Suporte (em inglês, Support Vector Machine ¿ SVM), uma técnica eficientemente aplicada a problemas de mineração de dados. O modelo é implementado através de técnicas de classificação, que extraem características relevantes nos conjuntos de dados, a fim de otimizar a operação da rede para cada condição de carregamento, eliminando a necessidade de repetir o treinamento do modelo ou calcular uma nova solução do problema de otimização a cada novo cenário. Discute-se o desempenho do método baseado em SVM para diferentes características de entrada. Investiga-se ainda a generalização do modelo proposto na presença de ruídos nos dados e no caso de reconfiguração da rede. Estudos em sistemas típicos de distribuição mostram que o método proposto é eficiente na solução de problemas práticos do dia-a-dia das concessionárias, principalmente em ambientes com grande volume de dados / Abstract: The growing demand for electricity, sometimes at a faster rate than investments in distribution network expansion, has led utilities operating close to acceptable limits, which makes the network operation more complex. One of current challenges is to establish an effective voltage and reactive power control, improving the operation as well as the efficiency of the distribution network. There are many methods reported to find a solutions for the voltage and reactive power problem. Most of them have adopted a decoupled form, solving the voltage control and reactive power (Volt/var) control separately. However, in this work, methods for the problem solution aiming the operation safety and the global assets optimization are approached in an integrated fashion, i. e., considering the dependence between voltage and reactive power. Most papers reports solution based on electrical models of distribution network. In this dissertation, the methods studied are based on machine learning techniques aiming to build a model with directly power meter data using capability, and set optimal dispatch of controls devices adjustments, without the need of an electrical model of the system and, therefore, not susceptible to inaccuracies of the model of the distribution network under study. Firstly, it proposes a reinforcement learning use, in which the agent interacts with the network while earns control operating experience. The implementation, thought de Q-Learning algorithm allows a construction of a distribution network virtual operation from data obtained from the meters installed on buses. From the meter data, is extracted the current state of the network loading condition. The main aspects of the application of the method to the integrated voltage and reactive power control are simulated in a typical network and the possibilities of practical application in the current scenario of the electrical system are discussed. In a second step, an algorithm for supervised learning via the Support Vector Machine (SVM), a technique applied efficiently to problems in data mining is proposed. The model is implemented by classification techniques, extracting relevant features in the data sets from the power meters in order to optimize the operation of the network for each loading condition. Thus it eliminates the need to retraining model or calculating a new optimization problem solution for each new scenario. Discusses the performance based on different features for SVM model input. Also the generalization capabilities of the proposed model in the presence of noise and in the case of network reconfiguration are studied. Studies in typical distribution systems show that proposed method is a good candidate to solve the practical problem of the system, especially in large networks with large amounts of data / Mestrado / Energia Eletrica / Mestre em Engenharia Elétrica

Presented thesis analyses a function of the particular type of the nanopositioner with aim to suggest and construct an electronic device suitable for control of the nanopositioner slider. In presented material there is a description of the control signals and possibility of their generating in the respect of slider movement accuracy. The main goal of the thesis is to describe electronic units ranging from power supply, control processor unit part to end part that directly joint nanopositioner. There is also programme equipment for microcontroller and computer, communication description, movement measuring and calibration and draft for the close-up of the control loop for additional increase of the movement accuracy.

This project deals with a design of power and control circuits for a laboratory power supply source, consisting of a continuous conduction mode active rectifier and DC/DC converter. Detailed design of input rectifier with active power factor correction, DC/DC converter and control circuits with their implementation to digital signal processor are the project results.

Durch den Ausbau insbesondere wetterabhängiger erneuerbarer Energien steigen zukünftig die Anforderungen an die Bereitstellung von Flexibilität im Stromsektor. Wärmespeicher und Power-to-Heat-Anlagen in der Fernwärmeversorgung können einen großen Beitrag zur Bereitstellung von Flexibilität an der Schnittstelle von Strom- und Wärmesektor liefern. Die vorliegende Arbeit untersucht vor dem Hintergrund von unterschiedlichen regulatorischen Rahmenbedingungen, an welchen Märkten der Einsatz der Power-to-Heat-Anlagen aus Systemsicht den größten Mehrwert zur Integration von erneuerbaren Energien liefern kann. Mithilfe des Strommarktmodells MICOES-Europe wird der stündliche Kraftwerkseinsatz aller europäischen Kraftwerke vor dem Hintergrund des Ausbaus der erneuerbaren Energien untersucht. Ziel der gemischt-ganzzahligen Optimierung, die insbesondere techno-ökonomische Charakteristika thermischer Kraftwerke berücksichtigt, ist die kostenminimale Deckung des Strombedarfs im Großhandelsmarkt bei gleichzeitiger Erfüllung der Leistungsvorhaltung für Regelenergie. In Deutschland werden die größten Fernwärmenetze mit ihren zugehörigen Erzeugungsanlagen (Kraft-Wärme-Kopplungsanlagen, Heizwerke, Wärmespeicher) abgebildet und stündlich die optimale Deckung des Wärmebedarfs berechnet. In einem Szenario für das Jahr 2025 wird die Verfügbarkeit von 1.000 MW an Elektrokesseln in großen deutschen Fernwärmenetzen angenommen. Hierbei wird deren Einsatz nur am Spotmarkt oder nur für negative Sekundärregelleistung dem Fall gegenübergestellt, dass die Anlagen auf beiden Märkten agieren und sich situationsabhängig zwischen ihnen entscheiden können. Es werden dabei die Fälle verglichen, bei denen Elektrokessel entweder Abgaben auf den Stromverbrauch zahlen oder keine zusätzlichen Abgaben tragen müssen. Der Einsatz der Elektrokessel in Verbindung mit Wärmespeichern in der Fernwärmeversorgung kann den Einsatz der KWK-Anlagen so flexibilisieren, dass sich deren Stromerzeugung stärker an die Einspeisesituation der erneuerbaren Energien anpassen kann. Auf diese Weise kann in allen betrachteten Szenarien die marktbedingte Abregelung von erneuerbaren Energien verringert werden. Dabei sinken die CO2-Emissionen der Strom- und Wärmeversorgung ebenfalls in allen Szenarien. Die größten Reduktionen sowohl bei CO2-Emissionen als auch bei den variablen Kosten der Strom- und Wärmeerzeugung werden dabei in den Szenarien mit Teilnahme der Elektrokessel am Regelleistungsmarkt erreicht. Stellen Elektrokessel negative Sekundärregelleistung bereit, kann hierdurch die Must-run-Erzeugung thermischer Kraftwerke in Stunden mit hoher Einspeisung von erneuerbaren Energien deutlich gesenkt werden. Hierdurch ergibt sich ein großer Hebel für die Integration von Strom aus erneuerbaren Energien. / The requirements for the provision of flexibility in the power sector will increase in the future due to the expansion of the usage of weather-dependent renewable energy sources. Heat storage and power-to-heat-plants (electric boilers) in the district heating supply can provide flexibility at the interface of the power and heat sector. At the moment the use of power-to-heat plants is only cost-effective on the control power market due to the current regulation. High charges for the direct use of electricity impede a use on the spot market. The present work examines from a system perspective on which market the use of electric boilers can provide the largest benefits for the integration of renewable energies considering different regu-latory frameworks. The year 2025 is considered where Germany aims to reach a share of 40 to 45 % renewable energy generation in the gross power consumption. For this purpose the hourly power plant dispatch of all European power plants is examined using the electricity market model MICOES-Europe. The model describes the wholesale electricity market and the control power market (secondary and tertiary reserve). The aim of the mixed-integer optimization is the calculation of the cost-minimal coverage of the electricity demand in the wholesale market while at the same time fulfilling the provision of control power. The optimization takes into account in particular the techno-economic characteristics of thermal power plants. In Germany, the largest district heating grids with their associated generation plants (combined heat and power plants, fossil-fuel and electric boilers, heat storage) are modelled and the optimal coverage of the heat demand is calculated for every hour. With the assumed payment of high electricity charges the use of electric boilers on the spot market is no business case in 2025. The situation changes in the scenario without electricity charges. Here, electric boilers reach between 1,050 and 2,140 full load hours. If the electric boilers provide negative secondary control power, the must-run generation of thermal power plants in hours with a high feed-in of renewable energies can be reduced significantly. This results in a large lever for the integration of renewable energies. Electric boilers reach up to 1,800 full load hours by providing control energy, if they provide control power all year round and without payment of electricity charges. The use of the electric boilers in combination with heat storages in the district heating system can make the dispatch of combined heat and power plants more flexible, so that their electricity generation can be better adapted to the feed-in situation of renewable energies. In this way, the market-dependent curtailment of renewable energies can be reduced in all scenarios. The CO2-emissions of the electricity and heat supply can be reduced by this technology in Germany. Furthermore, CO2-emissions in other European countries can be reduced as well due to effects of the power trade. The highest reductions in both CO2-emissions and variable costs of electricity and heat generation are achieved in the scenarios with electric boilers participating in the control power market.

This thesis is concerned with the generation control in small isolated power systems consisting of inverter interfaced generation systems. First the components of an individual distributed generation system (DGS) as well as the corresponding control schemes for active and reactive power flow are discussed and implemented. Then the contribution of multiple DGS to meet the requirement of the loads in both gridconnected and island operations are discussed. Having evaluated the performance of each developed model such as voltage source inverter, PQ and PV controlled as well as reference DGS, the impact of voltage degradation on power load control in isolated systems is analyzed. Finally a new method for generation control in a small power system based on power sharing between multiple DGS with voltage degradation consideration as the last alternative for sustaining the system is proposed and implemented.-11D

Thesis: M.S., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1980 / Includes bibliographical references. / by Conrado Orta, Jr. / M.S. / M.S. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

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Ocean wave energy is a promising renewable source to contribute to supplying the world’s energy demand. The Division of Electricity at Uppsala University is developing a technology to capture energy from ocean waves with a wave energy converter (WEC) consisting of a linear permanent magnet generator and a point absorber. The linear generator is placed on sea bed and is driven directly by the floating absorber. Since March 2006, multiple wave energy converters have been deployed on the Swedish west coast outside the town of Lysekil. The technology is verified by long-term operation during at sea and satisfactory reliability of the electricity generation. This thesis focuses on developing advanced control strategies for fully coupled wave energy converters subject to constraints. A nonlinear control strategy is studied in detail for a single WEC subject to constraints under regular and irregular waves. Besides, two coordinated control strategies are developed to investigate the performance of a wave energy farm subject to constraints. The performance of the WECs using these control strategies are investigated in case studies, and optimal PTO damping coefficients are found to maximize the output power. The results show that these control strategies can significantly improve the performance of the WECs, in terms of mean power, compared to a conventional control. Besides these control strategies, a wave-to-wire simulation platform is built to study the power generation control of the WEC subject to constraints.  The wave-to-wire simulation platform allows both nonlinear and linear control force. The results show that there is a good agreement between the desired value and the actual value after advanced control.

Esta proposta de pesquisa visa avaliar métodos de projeto de controladores em dois níveis, composto por controladores descentralizados e centralizado, utilizando sinais de medição fasorial sincronizada. Pesquisas iniciais foram realizadas utilizando a abordagem baseada na resolução da equação de Riccati num sistema multimáquinas, considerando aquisição de dados via medição fasorial sincronizada e atrasos de tempo nos canais de comunicação da entrada e da saída do controlador centralizado. Esta pesquisa propõe o projeto e avaliação de controladores centralizados através das abordagens baseadas na resolução da equação de Riccati, Desigualdades Matriciais Lineares e Algoritmos Genéticos. O projeto consiste em obter um controlador centralizado robusto a variações de carga e topologia do sistema, além de possíveis perdas de links de comunicação da entrada e da saída do controlador centralizado com o sistema elétrico. A fim de verificar a eficácia das abordagens de projeto foram utilizados o Sistema Equivalente Sul-Sudeste Brasileiro e o Sistema Simplificado Australiano. Além disso, simulações dinâmicas dos sistemas com aplicação de contingências foram realizadas com o propósito de se avaliar os controladores centralizados obtidos através de um modelo linear. Os resultados alcançados mostram semelhança e eficiência das abordagens quando se consideram múltiplos pontos de operação do sistema. A abordagem baseada em Algoritmos Genéticos se sobressai de acordo com os resultados obtidos para os sistemas-teste mencionados por propiciar um controlador centralizado robusto a múltiplos pontos de operação e possíveis perdas de links de comunicação. / This research proposal aims to compare control design methods on two levels, consisting of centralized and decentralized controllers, using signals synchronized phasor measurement. Initial researches have been conducted using the approach in solving the Riccati equation in a multi-machine system, considering data acquisition via synchronized phasor measurement and time delays in the communication channels of input and output of the centralized controller. This research proposes the design and comparison of centralized controllers through approaches based on resolution of the Riccati equation, Linear Matrix Inequalities and Genetic Algorithms. The project is to achieve a robust centralized controller to load variations and system topology changes and possible loss of communication of the input and output of the centralized controller with the electrical system. In order to verify the effectiveness of design approaches were used the Southern-Southeastern Brazil Equivalent Equivalent and Australian Simplified System. In addition, simulations of the dynamic systems with application of contingency were performed in order to evaluate the centralized controlling obtained by a linear model. The results show similarity and efficiency of the approaches when considering multiple system operating points. The Genetic Algorithms-based approach stands out according to the results obtained for the test systems mentioned, as demonstrated by the results, because it provides a robust centralized controller to multiple points of operation and possible loss of communication links.