PM Motors for High Efficiency Applications

PM motors are suitable for nearly all applications, like pumps, elevators, compressors, blowers, extruders, generators, electric vehicles, servodrives, cooling towers, household appliances, etc. This paper will present some applications where the use of PM motors allowed for enhancements in energy efficiency and process quality.

Estudo de delaminação em compósitos de matriz polimérica

A aplicação do material compósito é neste momento bastante vasta, graças à combinação das suas características específicas, tais como, maior resistência específica e módulos específicos e melhor resistência à fadiga, quando comparados com os metais convencionais. Tais características, quando requeridas, tornam este material ideal para aplicações estruturais. Esta caminhada de sucesso iniciou desde muito cedo, quando o material compósito já era utilizado para fabrico de armas pelos mongóis e na construção civil pelos hebreus e egípcios, contudo, só a partir dos meados do século XX é que despertou interesses para aplicações mais modernas. Atualmente os materiais compósitos são utilizados em equipamentos domésticos, componentes elétricos e eletrónicos, passando por materiais desportivos, pela indústria automóvel e construção civil, até indústrias de grande exigência e visibilidade tecnológica como a aeronáutica, espacial e de defesa. Apesar das boas características apresentadas pelos materiais compósitos, no entanto, estes materiais têm tendência a perderem as suas propriedades quando submetidas a algumas operações de acabamento como a furação. A furação surge da necessidade de ligação de peças de um mesmo mecanismo. Os furos obtidos por este processo devem ser precisos e sem danos para garantir ligações de alta resistência e também precisas. A furação nos materiais compósitos é bastante complexa devido à sua heterogeneidade, anisotropia, sensibilidade ao calor e pelo facto de os reforços serem extremamente abrasivos. A operação de furação pode causar grandes danos na peça, como a delaminação a entrada, defeitos de circularidade do furo, danos de origem térmica e a delaminação à saída que se apresenta como o mais frequente e indesejável. Com base nesses pressupostos é que este trabalho foi desenvolvido de forma a tentar obter processos simples para determinação e previsão de danos em polímeros reforçados com fibras (de carbono neste caso) de forma a precavê-los. De forma a conseguir estes objetivos, foram realizados ensaios de início de delaminação segundo a proposta de Lachaud et al. e ensaios de pin-bearing segundo a proposta de Khashaba et al. Foram também examinadas extensões de danos de acordo com o modelo de Fator de delaminação ajustado apresentado por Davim et al. A partir dos ensaios, de pin-bearing, realizados foram analisadas influências do material e geometria da broca, do avanço utilizado na furação e de diferentes orientações de empilhamentos de placas na delaminação de laminados compósitos e ainda a influências dessas variáveis na força de rutura por pin-bearing. As principais conclusões tiradas daqui são que a delaminação aumenta com o aumento do avanço, o que já era esperado, as brocas em carboneto de tungsténio são as mais recomendas para a furação do material em causa e que a delaminação é superior para a placa cross-ply quando comparada com placas unidirecionais. Para a situação de ensaios de início de delaminação foram analisadas as influências da variação da espessura não cortada por baixo da broca/punção, de diferentes geometrias de brocas, da alteração de velocidade de ensaio e diferentes orientações de empilhamentos de placas na força de início de delaminação. Deste ensaio as principais conclusões são que a força de início de delaminação aumenta com o aumenta da espessura não cortada e a influência da velocidade de ensaio altera com a variação das orientações de empilhamento.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Intelligent supervisory control system for home devices using a cyber physical approach

Although we have many electric devices at home, there are just few systems to evaluate, monitor and control them. Sometimes users go out and leave their electric devices turned on what can cause energy wasting and dangerous situations. Therefore most of the users may want to know the using states of their electrical appliances through their mobile devices in a pervasive way. In this paper, we propose an Intelligent Supervisory Control System to evaluate, monitor and control the use of electric devices in home, from outside. Because of the transferring data to evaluate, monitor and control user's location and state of home (ex. nobody at home) may be opened to attacks leading to dangerous situations. In our model we include a location privacy module and encryption module to provide security to user location and data. Intelligent Supervising Control System gives to the user the ability to manage electricity loads by means of a multi-agent system involving evaluation, monitoring, control and energy resource agents.

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

A general overview on hybrid and electric vehicles

The economical and environment impacts of fossil energies increased the interest for hybrid, battery and fuel-cell electric vehicles. Several demanding engineering challenges must be faced, motivated by different physical domains integration. This paper aims to present an overview on hybrid (HEV) and electric vehicles (EV) basic structures and features. In addition, it will try to point out some of the most relevant challenges to overcome for HEV and EV may be a solid option for the mobility issue. New developments in energy storage devices and energy management systems (EMS) are crucial to achieve this goal.

FMFT electric schematic revision/update

The recent update of the R-Fieldbus testbed to the new Flexible Manufacturing Field Trial – FMFT – brought up the need for a complete revision of its electric schematic.This document comes as a sort of appendix to the Technical Report “Flexible Manufacturing Field Trial”, providing a reliable source of information about the FMFT electric schematic for further developments and/or maintenances.

WeSenseNET - Plataforma de Visualização, Gestão Remota e Agregação Múltipla de Dados

Nos últimos anos, o avanço da tecnologia e a miniaturização de diversos componentes de electrónica associados a novos conceitos têm permitido nascer novas ideias e projectos, que até há alguns anos não passariam de ficção científica. Talvez o exemplo mais acabado seja actualmente o smartphone, um pequeno bloco de hardware e software, com capacidade de processamento que ultrapassa várias vezes o dos computadores com uma dúzia de anos. Estas capacidades têm sido utilizadas em comunicações, blocos de notas, agendas e até entretenimento. No entanto, podem ser reutilizadas para ajudar a resolver algumas limitações/constrangimentos da actualidade. Dentro destes destacam-se a gestão de recursos escassos. Com efeito, o consumo de energia eléctrica tem aumentado como consequência directa do desenvolvimento global e aumento do número de aparelhos eléctricos. Uma percentagem significativa de energia eléctrica tem sido produzida através de recursos não-renováveis de energia. No entanto, a dependência energética, associada à subida de preços e a redução das emissões de gases do efeito estufa, estimula o desenvolvimento de novas soluções que permitam lidar com esta situação. O desempenho energético por sua vez depende não só das características da estrutura, mas também do comportamento do utilizador. O desempenho energético dos edifícios é muito importante, uma vez que os respectivos consumos são responsáveis por mais de metade do total da energia produzida. Desta forma, a fim de alcançar um melhor desempenho é importante não só considerar o desempenho de estrutura, mas também monitorizar o comportamento do utilizador. Esta última questão coloca várias limitações, uma vez que depende muito do tipo de utilizador. Um dos conceitos actuais emergentes são as chamadas redes de sensores sem fio. Com esta tecnologia, pequenos módulos podem ser desenvolvidos com muitas possibilidades de conectividade, com elevado poder de processamento e com grande autonomia, sem serem excessivamente caros. Isto proporciona os meios para implementar vários dispositivos em toda a instalação, para recolher uma variedade de dados, sendo posteriormente armazenados num servidor. Os blocos fundamentais da infra-estrutura de sensores do projecto foram concebidos na Evoleo Technologies em simultâneo com o decorrer do estágio. Estes blocos recolhem dados específicos na instalação, e periodicamente enviam para o servidor central os valores recolhidos, onde são armazenados e colocados à disposição do utilizador. Os dados recolhidos podem então ser apresentados ao utilizador, proporcionando um registo de consumo de energia associado a um dado período de tempo. Uma vez que todos os dados são armazenados no servidor, podem ser efectuados estudos para determinar o uso típico, possíveis problemas em aparelhos, a qualidade da energia eléctrica, etc., permitindo determinar onde a energia está a ser eventualmente desperdiçada e fornecendo dados ao utilizador para que este possa proceder a alterações, tendo por base dados recolhidos num dado período. O objectivo principal deste trabalho passa por estabelecer a ligação entre o nível máquina e o nível de utilizador, isto é, uma plataforma de interacção entre dispositivos e administrador da instalação. Fornecer os dados de uma forma fácil e sem necessidade de instalação de software específico em cada dispositivo que se pretenda utilizar para monitorizar foi uma das principais preocupações das fases de concepção do projecto.

Support System for Rational Use of Electric Energy

This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.