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This paper describes the integration process between two tools in order to perform co-simulation for representation and analysis of dynamic environments in the context of smart grids. The integrated tools are Mosaik, a software to co-simulation management, and PADE, a software to multi-agent systems development. As a study case for demonstrate the integration, a scenary was utilized composed of a low voltage electricity distribution grid with 37 load bus, 20 photo-voltaic distributed generations, randomly connected to load bus, as well as, 20 PADE agents associated to distributed generation, modeling the behavior of electricity storage systems. The simulation results show the integration happening and demonstrate how useful is to model the dynamics of distributed electric resources with multi-agent systems.

Manual and remote controlled switches are commonly used in distribution networks to improve the reliability of electricity supply. This article aims to determine the number and placement of network switches in order to optimize both the investment costs and the reliability of distribution systems. Based on a mixed integer linear programming model, this paper proposes a methodology to obtain the cost/reliability Pareto front relative the simultaneous placement of manual and remote controlled switches, with the reliability measured by the expected energy not served index. The methodology is applied on a standard reliability test system (RBTS4) and a Pareto front is obtained as a result, which defines a set of non-dominated solutions. Additionally, a sensitivity analysis is performed to evaluate the results obtained by changes in system parameters. The proposed method provides a tool for the planning of electrical distribution networks, that assists in the decision making between conflicting objectives such as cost and reliability.

Este artigo apresenta um modelo de programa de resposta a demanda baseado em incentivos, cujo foco e otimizar os beneficios no trato da eletricidade do ponto de vista dos consumidores e do operador da rede eletrica. A modelagem do programa foi desenvolvida incluindo variaveis que necessitam ser previstas, tal como demanda e potencia de geracao solar fotovoltaica, para isso foram utilizadas redes neurais artificiais configuradas para cada caso. A otimizacao do modelo foi feita por meio de dois algoritmos diferentes, PSO e NSGA-II, validando os resultados obtidos. Por fim, o metodo e testado em dois casos distintos cenarios de demanda. A comparacao entre os lucros globais e individuais mostrou que a inclusao do programa de resposta a demanda e benefica do ponto de vista da rede eletrica.

O desempenho dos geradores fotovoltaicos e influenciado por diversas grandezas meteorologicas, sendo fundamental o conhecimento delas tanto para projecoes de geracao quanto para analises de performance de sistemas fotovoltaicos ja instalados. As estacoes meteorologicas, em muitos casos, sao instaladas em locais de dificil acesso e nem sempre sao acompanhadas de mecanismos de monitoramento que possibilitem o acesso remoto dos dados, sendo necessaria a coleta local dos mesmos. Nesse contexto, o presente trabalho consiste no desenvolvimento de um sistema de comunicacao baseado em placa de prototipagem eletronica e plataforma de Internet of things (IoT) ThingSpeak e um sistema supervisorio baseado no software gratuito ScadaBR. A solucao proposta para monitoramento disponibiliza os dados em tempo real local e remotamente, alem de apresentar uma interface amigavel e personalizada que apresentou bom funcionamento.

As the power distribution systems evolve mostly driven by the growth of distributed generation, microgrids emerge as a vital paradigm that enables boosting renewable energy deployment. Microgrids are small power systems that include conventional and renewable sources, storage systems and controllable loads. The operation of microgrids brings out some challenges related to economic dispatch due to the randomness of the renewable generation and the loads. This paper presents an optimal economic dispatch of a microgrid with distributed energy resources. In this study, enhanced distributed optimization methods of Consensus and Diffusion are used in the economic dispatch of an isolated microgrid, and a comparative evaluation between them regarding convergence, precision and computational effort is given. The results showed a suitable performance of both optimization methods with a better performance of the Diffusion method as to computational efforts.

O desempenho dos modulos fotovoltaicos e influenciado principalmente pelos indices de radiacao incidente e pela temperatura do ar. Embora a elevacao da temperatura cause um pequeno aumento na corrente gerada, tal elevacao pode resultar em uma reducao significativa de tensao diminuindo a potencia maxima fornecida pelo sistema. Assim, o conhecimento da temperatura do modulo fotovoltaico e da temperatura do ar e importante na analise da eficiencia da geracao fotovoltaica. Nesse contexto, o presente trabalho trata do desenvolvimento de um sistema de aquisicao de dados de temperatura de baixo custo baseado na plataforma de prototipagem Arduino MEGA e em um ambiente web voltado para aplicacoes de Internet das Coisas, o Thingspeak. O presente trabalho faz parte do Projeto Prioritario de Eficiencia Energetica e Minigeracao de Energia Fotovoltaica da Unilab em parceria com a Enel.

Wind power has contributed significantly to the increase in electricity generation, but a decision-making tool capable of dealing with its variability and limited predictability is necessary. For this purpose, a novel self-adaptive approach for kernel recursive least-squares machines named multiple challengers is introduced in this work, which is successfully used to produce very short-term wind power forecasts at eight wind farms in Australia. The proposed method is based on a competitive tracking method, and the algorithm deals with some common difficulties of kernel methods, e.g., the increasing kernel matrix size associated with time and memory complexities and the overfitting problem. The proposed method always considers the new information received by the model, thus identifying changes in the time series, avoiding abrupt loss of information and maintaining a controlled number of examples since there is an adaptive selection of the active kernel. It works with the smallest dictionary possible, reducing the probability of overfitting. Five minute-ahead wind power forecasts are produced and evaluated in terms of point forecast skill scores and calibration. The results of the proposed method are compared with those provided by other kernel-based versions of the recursive least-squares algorithm, an online version of the extreme learning machine method, and the persistence time series model. An increase in the number of kernels used in the ensemble system can lead to better results when compared with those of single-kernel models.

Este trabalho tem como objetivo apresentar o desenvolvimento e implantação de um sistema de aquisição de dados, supervisão e gerenciamento de uma MR instalada na Universidade Federal do Ceará. A MR possui três subsistemas monofásicos de geração fotovoltaica, os quais operam conectados à rede, mas possuem características de operação distintas: SFV-1 é capaz de operar em modo on-grid e off-grid com o suporte de um sistema de baterias; SFV-2 possui dois conjuntos (strings) de módulos FV, que podem operar conectados em série, em paralelo ou com apenas uma string; e SFV-3 pode ser conectado a qualquer uma das três fases da rede, segundo decisão do operador. Para desenvolver o sistema de supervisão e gerenciamento, foram usados o software Elipse Power para o SCADA, o SoMachine para programação do CLP e da IHM da MR e o SQL Server para criação do banco de dados. Testes foram realizados para avaliar o desempenho das funções de gerenciamento e do SCADA na supervisão e operação de cada subsistema FV, sob diferentes condições de operação da MR. As telas gráficas criadas no SCADA comprovaram o devido funcionamento do sistema supervisório e o registro das grandezas coletadas no banco de dados criado para a MR.

Com o crescimento do número de veículos elétricos (VEs) nos últimos dez anos, cresce a preocupação e o desafio para as redes elétricas de distribuição com o volume adicional de carga e a mobilidade aleatória dos VEs. O gerenciamento do carregamento de um número elevado de VEs será fundamental para a adoção bem-sucedida dessa nova tecnologia de transporte. Este artigo apresenta uma estratégia de controle e otimização para gerenciar o carregamento de VEs, visando a redução de perdas elétricas. O carregamento é realizado em função da potência disponível de uma estação de carregamento presente em um estacionamento. Para tanto, dois estudos de caso são realizados, para 10 VEs e para 100 VEs. O objetivo é alcançado com a aplicação do algoritmo de consenso que precisa apenas de informações trocadas entre VEs vizinhos. O controle distribuído possui um baixo custo computacional e de comunicação em relação a outras arquiteturas de controle. O gerenciamento de carregamento de VEs baseado em consenso é adaptativo ao número variável de VEs. Os resultados demonstram que a coordenação de carregamento pode ser eficientemente realizada por consenso.

O aumento da participação de usinas eólicas com conversores de frequência e a redução de participação das plantas de geração convencional nas matrizes mundiais têm contribuído para a redução da inércia dos sistemas de potência, trazendo novos desafios no contexto da estabilidade do sistema. Esse artigo apresenta uma adaptação dos modelos genéricos de aerogeradores WECC Tipo III e Tipo IV para atendimento ao código de rede brasileiro no que se refere à estabilidade de frequência. Foi realizado um estudo de estabilidade em um sistema de teste com alta participação de usinas eólicas, com o objetivo de demonstrar a importância da participação das usinas eólicas para a estabilidade de frequência do sistema, utilizando controle de inércia virtual. O comportamento do sistema é avaliado, em uma condição de falta, através da taxa de variação da frequência e do nadir da primeira oscilação da frequência, com e sem o controle de inércia virtual da usina eólica. Os resultados de simulação mostram que as usinas eólicas devem participar do controle de frequência para garantir a estabilidade dos sistemas elétricos de potência, e assim permitir um desenvolvimento sustentável dos sistemas elétricos futuros.

Este artigo analisa a influência do tipo de conexão dos transformadores trifásicos na propagação dos afundamentos de tensão causados por curtos-circuitos no sistema elétrico. Neste sentido, o artigo apresenta a modelagem matemática dos tipos de afundamentos de tensão, baseada na norma IEEE 1668-2017. Verifica-se que, ao se propagarem através de transformadores trifásico, os afundamentos de tensão podem ter suas características alteradas. É apresentada uma ferramenta didática desenvolvida no Matlab App Designer, com o objetivo de auxiliar a análise da propagação dos afundamentos de tensão e permitir melhor compreensão desse distúrbio na qualidade da energia elétrica. Além disso, testes experimentais foram realizados em laboratório com o objetivo de validar a modelagem matemática e a interface gráfica desenvolvida.

Operational research has made meaningful contributions to practical forecasting in organizations. An area of substantial activity has been in nonlinear modeling. Based on Particle Swarm Optimization, we discuss a nonlinear method where a self-adaptive approach, named as Particle Swarm Optimization with aging and weakening factors, was applied to training a Focused Time Delay Neural Network. Three freely available benchmark datasets were used to demonstrate the features of the proposed approach compared to the Backpropagation algorithm, Differential Evolution and the Particle Swarm Optimization method when applied for training the artificial neural network. Even acknowledging that the effort in comparing methods across multiple empirical datasets is certainly substantial, the proposed algorithm was used to produce 30 min, 1, 3 and 6 h ahead predictions of wind speed at one site in Brazil. The use of the proposed algorithm goes further than only training the artificial neural network, but also searching the best number of hidden neurons and number of lags. The results have shown that the modified Particle Swarm Optimization algorithm obtained better results in all predictions horizons, and the use of it has remarkably reduced the training time.

Power distribution systems are evolving from passive to active by the application of distributed generation and storage technologies, demand flexibility, and communication infrastructure. The ever-increasing penetration of distributed renewable generation within distribution networks promotes numerous opportunities which actively engage distribution systems and consumers in the power system operation. Flexible demand should play an important role in these systems as compensate uncertainties caused by the new generation resources, such as solar photovoltaic. This work proposes a retail electricity market model for active distribution system that addresses some future challenges power systems may face. The market mechanisms are modeled in a simulator that uses a stochastic optimization procedure to guide the decision making of individual players. To evaluate the proposed model, a case study is simulated and the results show that the defined market architecture with a stochastic optimization provides a good strategy for energy resources management and system stability.

Advances in power systems motivated by the increasing demand of generation sources connected to the power distribution system have brought several benefits, such as losses reduction and improved voltage profile. However, further research must be conducted to avoid the disadvantages and to improve the benefits. This paper applies differential evolution meta-heuristic to perform sizing and placement of Distributed Generation units in radial distribution networks in order to reduce active power losses. Besides, the proposed algorithm allows an evaluation of the active power losses behavior when compared to the number of generating units placed and dimensioned by the algorithm. Simulations have been performed using the IEEE 33-bus and IEEE 69-bus for evaluating the proposed methodology. The results obtained demonstrate the ability of the algorithm for placing and sizing Distributed Generation units in addition to evaluate the optimal number of generating units to minimize the active power losses in the networks.

Coordination of directional overcurrent relays is most often made based on manual procedures. However, due to its complexity and time-consuming, these procedures have been formulated as an optimization problem. The aim of this paper is to present a directional Bat Algorithm (dBA) as a potential algorithm for optimal coordination of directional overcurrent relays. The dBA performance was compared to others metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) when applied to a nine-bus benchmark test system. The obtained results showed that dBA overcame GA, PSO and BA with less total operating time and faster convergence with similar computational effort.

Reliability is a fundamental concept for Power Systems and the application of efficient Switch Placement is a valuable tool for improvements. The goal of this paper is to present an approach for efficient switch placement in Power Distribution Systems using Pareto optimality of a multi-objective function to improve reliability of distribution power systems based on an index that is reasoned on the number of consumers unsupplied. The discrete Pareto front considers the trade-off between the number of switches and the number of deenergized customers. The cost-reliability dilemma solution uses a Particle Swarm Optimization algorithm to achieve a set of solutions assumed to be effective. Then, this set of solutions is subjected to a contingency evaluation in order to select the solutions that enable unconstrained system restoration within its limits of current and voltage. The approach is applied to the medium voltage distribution network of Ceara’s Federal University campus. The approach is an important tool to support the planning of power distribution system.

The advance on smart grid calls for the development and application of distributed intelligent control strategies based on open platforms that provides interoperability. The distributed control must be able to ensure reliable and secure operation of the power systems and enhance supply quality to consumers. The development of a multi-agent system for automatic restoration system (MARS) applied to a real power distribution network is presented. The agents of the MARS are embedded in external hardware to the intelligent electronic devices (IEDs) and communicate with each other via standard Foundation for Intelligent Physical Agents open protocols. To evaluate the MARS performance, a computer simulator was developed in Java to represent the distribution system. Experimental tests were performed in laboratory with the simulator integrated to the MARS via TCP/IP. The tests results have shown that the MARS was able to locate and isolate branches under permanent fault condition and restore healthy branches efficiently through a given switching sequence taking into account the system operational constraints. The proposed MARS has proved the effectiveness of distributed control scheme based on multi-agent system that runs independently of the current technologies of the IEDs of control and protection.

Microgrids are presently receiving great attention and are considered the future trend for power distribution systems. This paper presents the control and management of a microgrid with distributed energy resources connected to a single bus. The microgrid management system uses a centralized and heuristic approach that considers the stochastic production of a photovoltaic power source, the use of a fuel cell, the state of charge of batteries, the variable load profile, and the flag-color of electricity tariff. The goal of the control and management system is the reliable and economic using of energy resources and their integration to power distribution systems while preserving the power quality. The responses regarding the control system of the power inverters connected to the distributed energy resources in the microgrid are evaluated during grid connection, standalone operation, and transition between the aforementioned operating modes. Simulation results prove that the control and management strategy is suitable in all operating conditions of the microgrid. The whole system composed of distributed energy resources, power electronic systems, and their respective control approaches that allow power management were developed in PSCAD/EMTDC simulation program.

The development of self-healing systems in the context of power distribution networks has increased significantly over the last years. However, such feature causes changes in the power grid structure, which may affect the coordination of protection systems. This work proposes a self-healing system (SHS) integrated with an adaptive protection system (APS) based on multi-agent systems (MAS). This approach aims at minimizing adverse impacts caused by the network restoration on the protection systems of distribution networks that contain distributed generation (DG). The SHS uses negotiation among agents to maximize the number of restored loads, while the agents of the APS reset the protection settings after changes occur in the network topology and state of DGs. The APS is capable of changing the current setting group and, if necessary, calculating new settings that can be sent to the relays to ensure the accurate coordination of protection systems. The proposed schemes are evaluated in a test workbench using commercial digital relays in different scenarios comprising DG penetration levels and network topology changes. The results clearly demonstrate that this strategy is fast and reliable when enhancing and providing robustness to the self-healing procedure.

This work presents a modified design procedure for an LCL filter topology that takes into account the optimization of the current control loop in terms of both robustness and dynamic performances. The proposed approach considers some issues that are usually neglected by the most common design methodologies, e.g., the nonlinear variation of the inductances as a function of the frequency and instantaneous currents. Based on the analysis of the equations that describe the behavior of the filter, a novel methodology that integrates the design of the filter inductances, a feedforward controller, and an active damping method is developed. As a result, the complexity of the feedback control system can be reduced and a simple proportional-integral (PI) controller is employed in the current control loop, with low steady-state error and simple tuning. Experimental results are discussed to validate the theoretical assumptions.

Distribution networks have increased reliability and security with the penetration of distributed generation and the application of automation functions that imply in topological reconfiguration. These changes however have effect on the protection systems and bring challenges to the planning and operation of the distribution networks. Therefore, this work proposes an adaptive protection system (APS) that aims to mitigate the impacts of distributed generation and topological reconfiguration in the protection system. The proposed system is activated by topological change, the switch on/off of generation units and change in the magnitude of the feeder currents. The APS is able to change the relays setting groups as well as to calculate and send to the relays a new setting. The application tool was developed in MATLAB and communicates with relays via Telnet protocol. Tests have been performed using a commercial relay and a computational model of a real distribution network.

In recent years, distributed generation based on renewable sources has contributed to the expansion of the global electricity matrix, reduction of environmental impacts and meeting demand growth. Although DGs have several benefits, the increasing insertion of wind and solar photovoltaic sources can cause impacts on the grid, which need to be analyzed and mitigated if necessary. This work aims to present the evaluation of the integration of photovoltaic solar generation in the electricity distribution network of the Pici Campus of the Federal University of Ceara. The design of the PV systems was developed using PVsyst software, and load, loss, voltage variation and power factor analyzes were performed with ANAREDE software, considering generation and demand variations on one weekday under maximum load demand and on a Sunday on low demand. The EasyPower® software was used to assess the impact on the coordination of campus network protection. The obtained results showed that the impacts were significant with reduction in FP and minimum variation of tension. For the condition where the generation was greater than the load, the reverse power flow caused an appreciable increase in the feeder loading and an increase of the technical losses, whereas, for the condition in which the generation was smaller than the load, there was a decrease in feeder loading and in technical losses. Regarding the electrical protection aspects, there was a loss of coordination of the protection, and there could be undue trips in the reclosers, and a non-appreciable increase in short-circuit levels.

Among the renewable energy sources, wind power has gained a prominent position worldwide due to the increasing application in the conversion into electric energy. The wind electricity generation has become the object of study of the impacts on the power grid of a generation with variable output power. This paper aims to model and simulate a wind turbine emulator using a three-phase induction motor (TIM) of squirrel cage rotor, which operates with variable speed. The direct field-oriented control (DFOC) has been applied to control the TIM speed. The flux observer used was the current-voltage model. Simulations in the MATLAB/Simulink simulator, using real wind speed data, made the full system validation. The simulation results have shown that the used control strategy responded satisfactorily to the wind speeds by observing an immediate follow-up of the reference speeds.

The onshore wind power is consolidated; the challenge is to reach the same level of maturity for offshore exploitation. Brazil has no offshore wind power plants and there are few studies in this direction. This paper aims to estimate the offshore wind resources in the State of Ceara, in Brazil. The investigation uses a mesoscale atmospheric computer model, the Regional Atmospheric Modeling System (RAMS), with horizontal resolution of 2 km, which estimates the offshore average wind speed, average wind direction, power density and turbulence taking into account the bathymetry data and navigation routes along the coast of Ceara. The wind potential was evaluated in three representative periods, La Nina, El Nino and Neutral year, analyzing the dry and rainy season for each period. The results indicate an average wind speed above 8 m/s and power density above 720 W/m 2 no matter the period evaluated, in the dry season. The predominant wind direction in the observed dry periods was from East to West and the turbulence intensity is smaller during dry season of El Nino. Besides, the bathymetry of the State of Ceara is shallow and the large ships route is far beyond the coast, offering no danger to future endeavors.

Customer satisfaction counts very much to the electric power distribution companies. The improvement of reliability indices is an effective way to achieve this goal. The optimal placement of power switches is a desirable procedure because while it reduces investment in network assets, it also reduces the number of customers not supplied by outages and, accordingly, improves system reliability. This paper proposes a multiobjective optimization approach for switch placement based on the particle swarm optimization method applied to radial distribution networks of power utilities. The proposed algorithm gives a set of solutions instead of a single one. It intends to be a valuable and flexible tool for planning modern and reliable power distribution networks. Simulation results when using the IEEE 123-node test system and the Roy Billinton Test System are presented as testbeds.

O extenso uso da automacao previsto para redes eletricas inteligentes traz desafios relacionados a dificuldade de integrar uma grande quantidade de dados de sensores, medidores, atuadores, controles e dispositivos de protecao. As ferramentas de aplicacao desenvolvidas para redes eletricas inteligentes dependem de formatos de dados padronizados e abertos para troca de dados. A comunicacao efetiva depende de um modelo comum de informacoes sobre a rede eletrica. O Common Information Model (CIM) do IEC 61970 fornece uma definicao consistente e estrutura de dados usando modelagem orientada a objetos. Namodelagem topologica de redes de distribuicao, a estrutura de dados de rede fornecida pela Representacao de No-Profundidade (NDE) tem sido amplamente utilizada por sua eficiencia computacional. Este trabalho tem como objetivo apresentar um Sistema Configurador e Simulador de Rede (NCSS) capaz de gerar metadados da rede eletrica no padrao CIM e converte-los em metamodelos NDE integrados a ferramentas de calculo de fluxo de potencia e curto-circuito. O NCSS foi projetado para o desenvolvimento, teste e validacao de sistemas de automacao voltados para sistemas de distribuicao de energia eletrica.

Nos ultimos anos, a presenca de geracao distribuida (DG) nos sistemas de distribuicao de energia eletrica cresceu bas-tante. Uma forma eficaz de aproveitar os beneficios das DGs e agrega-las com suas cargas em um subsistema chamado microrrede. Este artigo apresenta uma abordagem de controle distribuida primaria e secundaria aplicada a uma micror-rede que engloba uma unidade de geracao fotovoltaica trifasica de 5 kW, um sistema de turbina eolica com conversor pleno de 15 kW e uma microturbina a gas de 10 kW. A bem estabelecida tecnica de controle por inclinacao foi aplicada para o controle primario da microrrede. O restabelecimento dos desvios de frequencia e tensao do valor nominal foi realizado por uma estrategia de controle secundaria. O controle secundario baseado em multiagentes foi desenvolvido usando uma plataforma de codigo aberto chamada PADE (Python Agent Development Environment). As simulacoes da microrreda foram realizadas utilizando o software PSCAD, que fornece uma biblioteca de gerenciamento e controle, escrita em linguagem de programacao Python 3, possibilitando a integracao com a plataforma PADE. O desempenho do controle por inclinacao foi observado atraves do compartilhamento apropriado de potencia das fontes da microrre-de. A comunicacao entre o PSCAD e o PADE foi realizada, possibilitando a leitura de dados da simulacao e o envio de comandos, em tempo real.

This paper presents a new approach that provides scaling the LCL-filter inductances based on the harmonic analysis of the filter output current. The approach considers the filter design together with the inverter control, both together, improving the system stability and the dynamic response. The model and general guidelines for selecting the filter parameters, taking into account the variation of the grid equivalent inductor and the use of non-linear inductances, are presented. The proposed control system makes use of feed-forward control in order to increase performances of the feedback control and eliminates the need of synchronization procedure. Simulation tests with a 15 kW three-phase VSI with a LCL filter have proved the effectiveness of the proposed approach.

This paper presents a multi-agent-based system for the automatic restoration of power distribution networks supported by micro grids. The multi-agent automatic restoration system (MARS) is composed of eight types of agents: switch agents (AC), feeder agents (AL), tie switch agents (AE), connection point agent (APC), generation agent (AG), demand agent (AD), storage agent (AA), and dispatch generation agent (AGC). The agents work together in order to restore costumers load after a fault occurs in the utility power grid. The MARS was developed in JADE (Java Agent Development Framework), which is written in Java. Case studies are supposed to demonstrate the performance of the proposed MARS when applied to a medium-voltage power distribution network and a microgrid. The distribution network and the micro grid are modeled in Matlab-Simulink environment, while the communication tools between JADE and Simulink are also developed. Simulation results demonstrate that MARS presents a suitable performance, providing fast and reliable recovery of the power distribution network. It also evidences the capability of multi-agent system techniques in the automation and decision support of smart grids.

This article presents a new approach that provides scaling the LCL-filter inductances based on the harmonic analysis of the filter output current. The approach considers the filter design together with the inverter control, both together, improving the system stability and the dynamic response. The model and general guidelines for selecting the filter parameters, taking into account the variation of the grid equivalent inductor, are presented. The proposed control system makes use of a simple PI since the feed-forward controller removes from the feedback controller the control on the grid current and eliminates the need of synchronization procedure. Simulation tests with a 15 kW three-phase VSI in series with an LCL filter have proved the effectiveness of the proposed approach.

When a permanent fault occurs in a power distribution system, the network can be reconfigured in order to restore the supply of some loads situated on non-faulty paths. This paper presents an algorithm developed in Python for optimize the automatic reconfiguration and restoration of radial power distribution systems after the occurrence of a permanent fault. It uses the Multi-objective Evolutionary Algorithm technique and the Step Method in order to optimize all objectives of a given problem, thus providing a greater number of possible solutions. The goals set to the multi-objective function are the maximization of restored customers, minimization of Joule losses and the number of switching maneuvers in the network for the restoration, which are subject to operational constraints. The software features a set of non-dominated solutions, providing the operator with the option to choose from several effective configurations. The grid is modeled by using the node-depth representation (NDR), and the operating constraints evaluated by the forward / backward sweep load flow method. The 16-bus IEEE test system and a proposed 41-bus test system are used to analyze the response of the developed application, which presents good performance and can be safely used by radial distribution system operators.

The growth of energy consumption, the ever extensive use of conventional fossil fuels from exhaustible resources and concerns about the environment have led to the development of sustainable renewable energy as a necessary global requirement. Today, the trend in the electrical sector is the generation of electrical power at low voltage. Distributed generation at low voltage enables consumers to contribute to the country’s energy mix system without large investments by governments. This means that dwellers are able to produce and inject electrical power into the grid thus enjoying the status of energy producer and also reducing the burden on the national electrical grid system. In order for this system to produce high quality energy in a safe and coordinated manner, stringent health & safety and technical measures must be implemented. Moreover, such systems require strong legal support and well-established contracts. Technical training of personnel, implementation of well established planned/corrective maintenance systems and electrical spare part availability are also crucial to the reliability and long term operation of such systems. The aims of the paper are to present the basis for development of renewable energy for household usage in countries such as Germany, Denmark, Spain and Brazil, in terms of technical requirements for electrical generation and grid connection at low voltage. In Brazil about 70% of the electricity comes from hydropower and around 50% of its automobiles run on renewable biofuel, which results in a low per capita emission. The country however faces some tough barriers to overcome in order to implement household generation from renewable sources. These will be discussed in due course.

This paper focuses on the steady-state analysis of location and control of distributed power generators encompassing a virtual power plant (VPP). The significant increase worldwide in distributed generation from renewable energy has been largely due to the concern with the environment, the grid access and the strong support policies for the promotion of renewable electricity. Deployment of distributed power plants has contributed to the new concept of VPP as a solution to handle the mix of conventional and distributed energy sources. Produced energy from even small scale generators will be utilized in energy markets and can contribute to the enhancement of the electrical power system. When aggregated, the group of DG would gain access and visibility across the energy markets and the system operation will benefit from optimal use of all available capacity and increased efficiency of operation.

As the wind power technologies evolve from one to another breakthrough and the wind power plants continue its ever increasing penetration in the power system it is a matter of time when the wind power production will be comparable to or even larger than the conventional power generation. In this paper the growth and advances of the wind power industry are described. Relevant aspects related to large-scale integration of wind power into the power system are discussed as the challenges arising from market liberalization, electricity networks innovation, the limited predictability of wind and the voltage and frequency control capabilities.

Distributed generation systems based on renewable energies, such as solar and wind energy sources, are nowadays one of the most promising ways to meet the power demand increase, the customer interests to generate electricity and the environmental issues. The scattering of small solar and wind generators should be promoted as a way to reduce the impact of the non-programmable production of these sorts of sources. For that, cost-effective solutions are sought to step up the use of these sources. This paper deals with the design and performance analysis of a cost-effective converter applied to control the power output of a small double fed induction generator for wind turbines connected to a low voltage network. A four-quadrant converter, suitable for low voltage and smart grids applications, is proposed and its characteristics are illustrated.

This paper presents the automation of the power distribution system of the Pici Campus of the Federal University of Ceara. The paper aims to present the integration via protocol Open Platform Communications (OPC) of an application program for automatic restoration and a commercial Supervisory Control and Data Acquisition (SCADA). OPC ensures different application programs with proprietary protocols share real-time information making them possible to interoperate. The SCADA system monitors and controls the 13.8 kV network across the campus gathering information at the Microsoft SQL Server 2012 database - Express version. The automatic restoration system is an application software developed in C# using Microsoft Visual Studio 2010. The self-healing application program contributes to increase the reliability of the power distribution system of the university campus. Tests in laboratory were performed successfully in order to evaluate the communication performance.

The Offshore Wind Energy is a technology already widely developed in the European Union with approximately 5GW installed by the end of 2012. In Brazil there are few studies in this segment and potential analysis is essential to indicate the possible locations where parks at sea. The analysis using periods of El Niño and La Niña periods showed that even in the presence of extreme events Ceará coast shows values of mean wind speed will favor the installation of offshore wind farms. A Energia Eólica Offshore já é uma tecnologia amplamente desenvolvida na União Europeia com aproximadamente 5GW instalados até o final de 2012. No Brasil, são poucos os estudos neste segmento e a análise do potencial é essencial para indicar os possíveis locais de implantação de parques no mar. A análise feita, utilizando períodos de El Niño e La Niña, mostrou que mesmo em períodos com presença de eventos extremos, a costa cearense apresenta valores de velocidade média do vento favoráveis á instalação de parques eólicos offshore.

This paper addresses the topic of distributed generation with a focus point of common coupling protection of a microgrid to the distribution system. It describes the regulatory and normative aspects of access to Brazilian distribution system, as well as effects caused by the connection of distributed generation on the network. It also proposes the necessary settings to the protection relay to the point of common coupling and performs tests using a testing equipment of protection relays.