A energia das ondas e o seu aproveitamento

As crises energéticas surgidas no decorrer do último século, incluindo a crise do petróleo, obrigaram o Homem a procurar cada vez mais fontes de energia alternativas e preferencialmente inesgotáveis. Desta situação, resultou uma forte aposta na exploração das fontes de energias renováveis, que são uma das principais alternativas para responder a um aumento de procura, e também, face às exigências de consumos actuais, beneficiando de ao se apostar numa energia limpa e renovável existir uma forte redução nos impactes ambientais que outras fontes de energia não apresentam. O aproveitamento dos recursos provenientes de fontes de energia renováveis para a produção de energia já existe há vários anos, e, em alguns casos, atingiram já um estado de maturidade considerável, como é caso da energia eólica. Em comparação, o mesmo já não acontece com a energia das ondas. Embora o oceano apresente um recurso com enorme potencial para ser explorado, incluindo as ondas e correntes oceânicas, os dispositivos tecnológicos necessários para a exploração deste recurso encontram-se maioritariamente ainda em fase experimental, havendo casos pontuais que atingiram a fase pré-comercial. Assim, não existe até à data um dispositivo padrão para a exploração da energia das ondas em grande escala, contrariamente ao que acontece com a energia eólica. Para esta situação, contribuiu o elevado número de dispositivos patenteados para a exploração da energia das ondas, nenhum deles com vantagens significativas relativamente a outros, e também, devido ao facto de a exploração deste tipo de energia não poder ser feito de igual modo na costa ou a muitos quilómetros dela. Na presente dissertação são apresentados alguns dos principais dispositivos existentes para a extracção de energia proveniente das ondas oceânicas, com especial atenção para os dispositivos de coluna de água oscilante.

Grid Integration of Offshore Wind Farms Using Modular Marx Multilevel Converters

This paper proposes the use of a Modular Marx Multilevel Converter, as a solution for energy integration between an offshore Wind Farm and the power grid network. The Marx modular multilevel converter is based on the Marx generator, and solves two typical problems in this type of multilevel topologies: modularity and dc capacitor voltage balancing. This paper details the strategy for dc capacitor voltage equalization. The dynamic models of the converter and power grid are presented in order to design the converter ac output voltages and the dc capacitor voltage controller. The average current control is presented and used for power flow control, harmonics and reactive power compensation. Simulation results are presented in order to show the effectiveness of the proposed (MC)-C-3 topology.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Adaptable control for electrical generation at irregural wind speeds

The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

A new wind farm in Santiago Island, cape verde - simulation and economic studies

Ensuring sustainable development conditions is presently world widely recognized as a critically important goal. This makes the use of electricity generation technologies based on renewable energy sources very relevant. Developing countries depend on an adequate availability of electrical energy to assure economic progress and are usually characterized by a high increase in electricity consumption. This makes sustainable development a huge challenge but it can also be taken as an opportunity, especially for countries which do not have fossil resources. This paper presents a study concerning the expansion of an already existent wind farm, located in Praia, the capital of Cape Verde Republic. The paper includes results from simulation studies that have been undertaken using PSCAD software and some economic considerations.

Dispachability improvement of wind generation by the virtual power producers

Nowadays, there is a growing environmental concern about were the energy that we use comes from, bringing the att ention on renewable energies. However, the use and trade of renewable e nergies in the market seem to be complicated because of the lack of guara ntees of generation, mainly in the wind farms. The lack of guarantees is usually addressed by using a reserve generation. The aggregation of DG p lants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of wind generation technologies, making them valuable in electricity markets. This paper presents some resul ts obtained with a simulation tool (ViProd) developed to support VPPs in the analysis of their operation and management methods and of their strat egies effects.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Evaluation of 99mTc-Sestamibi as a potential tool to investigate PgP activity in inflammation

Introduction: In the XXI Century ’s Society the scientific investigation process has been growing steadily , and the field of the pharmaceutical research is one of the most enthusiastic and relevant . Here, it is very important to correlate observed functional alterations with possibly modified drug bio distribution patterns . Cancer, inflammation and inf ection are processes that induce many molecular intermediates like cytokines, chemokines and other chemical complexes that can alter the pharmacokinetics of many drugs. One cause of such changes is thought to be the modulator action of these complexes in t he P - Glyco p rotein activity, because they can act like inducers/inhibitors of MDR - 1 expression. This protein results from the expression of MDR - 1 gene, and acts as an ATP energy - dependent efflux pump, with their substrates including many drugs , like antiretrovirals, anticancers, anti - infectives, immunosuppressants, steroids or opioids . Objectives: Because of the lack of methods to provide helpful information in the investigation of in vivo molecular changes in Pgp activity during infection/infl ammation processes, and its value in the explanation of the altered drug pharmacokinetic, this paper want to evaluate the potential utility of 99m Tc - Sestamibi scintigraphy during this kind of health sciences investigation. Although the a im is indeed to create a technique to the in vivo study of Pgp activity, this preliminary Project only reaches the in vitro study phase, assumed as the first step in a n evaluation period for a new tool development. Materials and Methods: For that reason , we are performing in vitro studies of influx and efflux of 99m Tc - Sestamibi ( that is a substrate of Pgp) in hepatocytes cell line (HepG2). We are interested in clarify the cellular behavior of this radiopharmaceutical in Lipopolysaccharide(LPS) stimulated cells ( well known in vitro model of inflammation) to possibly approve this methodology. To validate the results, the Pgp expression will be finally evaluated using Western Blot technique. Results: Up to this moment , we still don’t have the final results, but we have already enough data to let us believe that LPS stimulation induce a downregulation of MDR - 1, and consequently Pgp, which could conduce to a prolonged retention of 99m Tc - Sestamibi in the inflamed cells . Conclusions: If and when this methodology demonstrate the promising results we expect, one will be able to con clude that Nuclear Medicine is an important tool to help evidence based research also on this specific field .