Mobile device-to-device distributed computing using data sets

The rapidly increasing computing power, available storage and communication capabilities of mobile devices makes it possible to start processing and storing data locally, rather than offloading it to remote servers; allowing scenarios of mobile clouds without infrastructure dependency. We can now aim at connecting neighboring mobile devices, creating a local mobile cloud that provides storage and computing services on local generated data. In this paper, we describe an early overview of a distributed mobile system that allows accessing and processing of data distributed across mobile devices without an external communication infrastructure. Copyright © 2015 ICST.

Server to Mobile Device Communication: A Case Study

Develop a client-server application for a mobile environment can bring many challenges because of the mobile devices limitations. So, in this paper is discussed what can be the more reliable way to exchange information between a server and an Android mobile application, since it is important for users to have an application that really works in a responsive way and preferably without any errors. In this discussion two data transfer protocols (Socket and HTTP) and three serialization data formats (XML, JSON and Protocol Buffers) were tested using some metrics to evaluate which is the most practical and fast to use.

Aplicação de Internet of Things em casas inteligentes - Serviço Aplicacional

Engenharia Informática, Área de Especialização em Arquiteturas, Sistemas e Redes

Light memory operation based on a double pin SiC device

Experimental optoelectronic characterization of a p-i'(a-SiC:H)-n/pi(a-Si:H)-n heterostructure with low conductivity doped layers shows the feasibility of tailoring channel bandwidth and wavelength by optical bias through back and front side illumination. Front background enhances light-to-dark sensitivity of the long and medium wavelength range, and strongly quenches the others. Back violet background enhances the magnitude in short wavelength range and reduces the others. Experiments have three distinct programmed time slots: control, hibernation and data. Throughout the control time slot steady light wavelengths illuminate either or both sides of the device, followed by the hibernation without any background illumination. The third time slot allows a programmable sequence of different wavelengths with an impulse frequency of 6000Hz to shine upon the sensor. Results show that the control time slot illumination has an influence on the data time slot which is used as a volatile memory with the set, reset logical functions. © IFIP International Federation for Information Processing 2015.

Modelling a cable structure for a new wind energy production device

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Mecânica Especialização em Concepção e Produção

GAIC: Um sistema inteligente e flexível para simulação e apoio à participação de pequenos e médios consumidores na gestão ativa de cargas no âmbito de smart grids

A liberalização dos mercados de energia e a utilização intensiva de produção distribuída tem vindo a provocar uma alteração no paradigma de operação das redes de distribuição de energia elétrica. A continuidade da fiabilidade das redes de distribuição no contexto destes novos paradigmas requer alterações estruturais e funcionais. O conceito de Smart Grid vem permitir a adaptação das redes de distribuição ao novo contexto. Numa Smart Grid os pequenos e médios consumidores são chamados ao plano ativo das participações. Este processo é conseguido através da aplicação de programas de demand response e da existência de players agregadores. O uso de programas de demand response para alcançar benefícios para a rede encontra-se atualmente a ser estudado no meio científico. Porém, existe a necessidade de estudos que procurem benefícios para os pequenos e médios consumidores. O alcance dos benefícios para os pequenos e médios consumidores não é apenas vantajoso para o consumidor, como também o é para a rede elétrica de distribuição. A participação, dos pequenos e médios consumidores, em programas de demand response acontece significativamente através da redução de consumos energéticos. De modo a evitar os impactos negativos que podem provir dessas reduções, o trabalho aqui proposto faz uso de otimizações que recorrem a técnicas de aprendizagem através da utilização redes neuronais artificiais. Para poder efetuar um melhor enquadramento do trabalho com as Smart Grids, será desenvolvido um sistema multiagente capaz de simular os principais players de uma Smart Grid. O foco deste sistema multiagente será o agente responsável pela simulação do pequeno e médio consumidor. Este agente terá não só que replicar um pequeno e médio consumidor, como terá ainda que possibilitar a integração de cargas reais e virtuais. Como meio de interação com o pequeno e médio consumidor, foi desenvolvida no âmbito desta dissertação um sistema móvel. No final do trabalho obteve-se um sistema multiagente capaz de simular uma Smart Grid e a execução de programas de demand response, sSendo o agente representante do pequeno e médio consumidor capaz de tomar ações e reações de modo a poder responder autonomamente aos programas de demand response lançados na rede. O desenvolvimento do sistema permite: o estudo e análise da integração dos pequenos e médios consumidores nas Smart Grids por meio de programas de demand response; a comparação entre múltiplos algoritmos de otimização; e a integração de métodos de aprendizagem. De modo a demonstrar e viabilizar as capacidades de todo o sistema, a dissertação inclui casos de estudo para as várias vertentes que podem ser exploradas com o sistema desenvolvido.

Using Baseline Methods to Identify Non-technical Losses in the Context of Smart Grids

Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Smart Grid Market Using Joint Energy and Ancillary Services Bids

The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM – a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Reactive power management strategies in future smart grids

The reactive power management in distribution network with large penetration of distributed energy resources is an important task in future power systems. The control of reactive power allows the inclusion of more distributed recourses and a more efficient operation of distributed network. Currently, the reactive power is only controlled in large power plants and in high and very high voltage substations. In this paper, several reactive power control strategies considering a smart grids paradigm are proposed. In this context, the management of distributed energy resources and of the distribution network by an aggregator, namely Virtual Power Player (VPP), is proposed and implemented in a MAS simulation tool. The proposed methods have been computationally implemented and tested using a 32-bus distribution network with intensive use of distributed resources, mainly the distributed generation based on renewable resources. Results concerning the evaluation of the reactive power management algorithms are also presented and compared.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Smart Grid Communication Technologies in the Brazilian Electrical Sector

Intelligent electrical grids can be considered as the next generation of electrical energy transportation. The enormous potential leads to worldwide focus of research on the technology of smart grids. This paper aims to present a review of the Brazilian electricity sector in context with the integration of communication technologies for smart grids. The work gives an overview of the generation, transmission and distribution of electrical energy in the Brazil and a brief summary of the current electricity market. Smart grid technologies are introduced and the requirements for the Brazilian power system are pointed out. Various technologies for communication within an intelligent network are presented and their characteristics, advantages and disadvantages are compared to the Brazilian conditions. In addition, a summary is given of current pilot projects for Smart Grid technologies within Brazil, as well as a presentation of individual selected projects.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Smart Metering Como Ferramenta de Eficiência Energética

As smart grids e os smart meters, ou redes inteligentes e medidores inteligentes, respectivamente, estão cada vez mais próximos dos consumidores residenciais pelo mundo. Vários países vêm desenvolvendo estudos focados nos impactos decorrentes da introdução destas tecnologias. Uma das principais vantagens está relacionada à eficiência energética, ou conscientização da população em prol de um consumo mais eficiente. Estes benefícios são sentidos diretamente pelo consumidor através da economia nas contas de energia elétrica e pelas concessionárias através da minimização das perdas de transmissão e distribuição, estabilidade do sistema, menor carregamento nos horários de pico, entre outros. Neste artigo são apresentados dois projetos que demonstram o potencial de economia de energia através dos medidores inteligentes e das redes inteligentes. O primeiro realizado na Coreia, com foco na instalação de smart meters e o impacto da utilização de interfaces com o usuário. O segundo realizado em Portugal, com foco no controle das cargas em uma residência com geração distribuída.