Effects of the paralysis tick, Ixodes holocyclus, on the electrocardiogram of the Spectacled Flying Fox, Pteropus conspicillatus

Objective To evaluate cardiac electrical function in the Spectacled Flying Fox (bat) infested with Ixodes holocyclus. Design Prospective clinical investigation of bats treated for naturally occurring tick toxicity. Procedure ECGs were performed on bats with tick toxicity (n = 33), bats that recovered slowly (n = 5) and normally (n = 5) following treatment for tick toxicity, and on normal bats with no history of tick toxicity (n = 9). Results Bats with tick toxicity had significantly prolonged corrected QT intervals, bradycardia and rhythm disturbances which included sinus bradydysrhythmia, atrial standstill, ventricular premature complexes, and idioventricular bradydysrhythmia. Conclusions The QT prolongation observed on ECG traces of bats with tick toxicity reflected delayed ventricular repolarisation and predisposed to polymorphic ventricular tachycardia and sudden cardiac death in response to sympathetic stimulation. The inability to document ventricular tachycardia in bats shortly before death from tick toxicity may be explained by a lack of sympathetic responsiveness attributable to the unique parasympathetic innervation of the bat heart, or hypothermiainduced catecholamine receptor down-regulation. Bradycardia and rhythm disturbances may be attributable to hypothermia.

Thermal degradation of Pb(Zr0.53Ti0.47)O3/poly(vinylidene fluoride) composites as a function of ceramic grain size and concentration

Poly(vinylidene fluoride)/Pb(Zr0.53Ti0.47)O3,([PVDF]1−x/[PZT]x) composites of volume fractions x and (0–3) type connectivity were prepared in the form of thin films. PZT powders with average grain sizes of 0.2, 0.84, and 2.35 μm in different volume fraction of PZT up to 40 % were mixed with the polymeric matrix. The influence of the inorganic particle size and its content on the thermal degradation properties of the composites was then investigated by means of thermo-gravimetric analysis. It is observed that filler size affects more than filler concentration the degradation temperature and activation energy of the polymer. In the same way and due to their larger specific area, smaller particles leave larger solid residuals after the polymer degradation. The polymer degradation mechanism is not significantly modified by the presence of the inorganic fillers. On the other hand, an inhibition effect occurs due to the presence of the fillers, affecting particularly the activation energy of the process.

Impacto da integração dos veículos eléctricos nos edifícios multi-habitacionais, nas redes de distribuição de baixa tensão e no diagrama de carga nacional

Associado à escassez dos combustíveis fósseis e ao desejado controlo de emissões nocivas para a atmosfera, assistimos no mundo ao desenvolvimento do um novo paradigma — a mobilidade eléctrica. Apesar das variações de maior ou menor arbítrio político dos governos, do excelente ou débil desenvolvimento tecnológico, relacionados com os veículos eléctricos, estamos perante um caminho, no que diz respeito à mobilidade eléctrica, que já não deve ser encarado como uma moda mas como uma orientação para o futuro da mobilidade. Portugal tendo dado mostras que pretende estar na dianteira deste desafio, necessita equacionar e compreender em que condições existirá uma infra-estrutura nacional capaz de fazer o veículo eléctrico vingar. Assim, neste trabalho, analisa-se o impacto da mobilidade eléctrica em algumas dessas infra-estruturas, nomeadamente nos edifícios multi-habitacionais e redes de distribuição em baixa tensão. São criados neste âmbito, quatro perfis de carregamento dos EVs nomeadamente: nas horas de chegada a casa; nas horas de vazio com início programado pelo condutor; nas horas de vazio controlado por operador de rede (“Smart Grid”); e um cenário que contempla a utilização do V2G. Com a obrigação legal de nos novos edifícios serem instaladas tomadas para veículos eléctricos, é estudado, com os cenários anteriores a possibilidade de continuar a conceber as instalações eléctricas, sem alterar algumas das disposições legais, ao abrigo dos regulamentos existentes. É também estudado, com os cenários criados e com a previsão da venda de veículos eléctricos até 2020, o impacto deste novo consumo no diagrama de carga do Sistema Eléctrico Nacional. Mostra-se assim que a introdução de sistemas inteligentes de distribuição de energia [Smartgrid e vehicle to grid” (V2G)] deverá ser encarada como a solução que por excelência contribuirá para um aproveitamento das infra-estruturas existentes e simultaneamente um uso acessível para os veículos eléctricos.

Short-term wind forecasting for energy resources scheduling

This paper proposes a wind power forecasting methodology based on two methods: direct wind power forecasting and wind speed forecasting in the first phase followed by wind power forecasting using turbines characteristics and the aforementioned wind speed forecast. The proposed forecasting methodology aims to support the operation in the scope of the intraday resources scheduling model, namely with a time horizon of 5 minutes. This intraday model supports distribution network operators in the short-term scheduling problem, in the smart grid context. A case study using a real database of 12 months recorded from a Portuguese wind power farm was used. The results show that the straightforward methodology can be applied in the intraday model with high wind speed and wind power accuracy. The wind power forecast direct method shows better performance than wind power forecast using turbine characteristics and wind speed forecast obtained in first phase.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

Residential energy resources management by a SCADA system in case of excess wind generation

The end consumers in a smart grid context are seen as active players. The distributed generation resources applied in smart home system as a micro and small-scale systems can be wind generation, photovoltaic and combine heat and power facility. The paper addresses the management of domestic consumer resources, i.e. wind generation, solar photovoltaic, combined heat and power, electric vehicle with gridable capability and loads, in a SCADA system with intelligent methodology to support the user decision in real time. The main goal is to obtain the better management of excess wind generation that may arise in consumer’s distributed generation resources. The optimization methodology is performed in a SCADA House Intelligent Management context and the results are analyzed to validate the SCADA system.

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.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.