963 resultados para RESOURCE AVAILABILITY


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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).

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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.

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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.

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This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

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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.

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Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

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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 .

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Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

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10th International Temperate Reefs Symposium, The University of Western Australia, 12-17 de janeiro.

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Dissertação de Mestrado em Ambiente, Saúde e Segurança.

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A verificação das Características Garantidas associadas aos equipamentos, em especial dos aerogeradores, incluídos no fornecimento de Parques Eólicos, reveste-se de particular importância devido, principalmente, ao grande volume de investimento em jogo, ao longo período necessário ao retorno do mesmo, à incerteza quanto à manutenção futura das actuais condições de remuneração da energia eléctrica produzida e ainda à falta de dados históricos sobre o período de vida útil esperado para os aerogeradores. Em face do exposto, é usual serem exigidas aos fornecedores, garantias do bom desempenho dos equipamentos, associadas a eventuais penalidades, quer para o período de garantia, quer para o restante período de vida útil, de modo a minimizar o risco associado ao investimento. No fornecimento de Parques Eólicos existem usualmente três tipos de garantias, nomeadamente, garantia de Curva de Potência dos aerogeradores, garantia de Disponibilidade dos equipamentos ou garantia de Produção de Energia. Estas poderão existir isoladamente ou em combinação, dependendo das condições contratuais acordadas entre o Adjudicatário e o Fornecedor. O grau de complexidade e/ou trabalho na implementação das mesmas é variável, não sendo possível afirmar qual delas é a mais conveniente para o Adjudicatário, nem qual a mais exacta em termos de resultados. Estas dúvidas surgem em consequência das dificuldades inerentes à recolha dos próprios dados e também da relativamente ampla margem de rearranjo dos resultados permitido pelas normas existentes, possibilitando a introdução de certo tipo de manipulações nos dados (rejeições e correlações), as quais podem afectar de forma considerável as incertezas dos resultados finais dos ensaios. Este trabalho, consistiu no desenvolvimento, execução, ensaio e implementação de uma ferramenta informática capaz de detectar de uma forma simples e expedita eventuais desvios à capacidade de produção esperada para os aerogeradores, em função do recurso verificado num dado período. Pretende ser uma ferramenta manuseável por qualquer operador de supervisão, com utilização para efeitos de reparações e correcção de defeitos, não constituindo contudo uma alternativa a outros processos abrangidos por normas, no caso de aplicação de penalidades. Para o seu funcionamento, são utilizados os dados mensais recolhidos pela torre meteorológica permanente instalada no parque e os dados de funcionamento dos aerogeradores, recolhidos pelo sistema SCADA. Estes são recolhidos remotamente sob a forma de tabelas e colocados numa directoria própria, na qual serão posteriormente lidos pela ferramenta.

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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.

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Trabalho de Projecto de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil

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We live in a changing world. At an impressive speed, every day new technological resources appear. We increasingly use the Internet to obtain and share information, and new online communication tools are emerging. Each of them encompasses new potential and creates new audiences. In recent years, we witnessed the emergence of Facebook, Twitter, YouTube and other media platforms. They have provided us with an even greater interactivity between sender and receiver, as well as generated a new sense of community. At the same time we also see the availability of content like it never happened before. We are increasingly sharing texts, videos, photos, etc. This poster intends to explore the potential of using these new online communication tools in the cultural sphere to create new audiences, to develop of a new kind of community, to provide information as well as different ways of building organizations’ memory. The transience of performing arts is accompanied by the need to counter that transience by means of documentation. This desire to ‘save’ events reaches its expression with the information archive of the different production moments as well as the opportunity to record the event and present it through, for instance, digital platforms. In this poster we intend to answer the following questions: which online communication tools are being used to engage audiences in the cultural sphere (specifically between theater companies in Lisbon)? Is there a new relationship with the public? Are online communication tools creating a new kind of community? What changes are these tools introducing in the creative process? In what way the availability of content and its archive contribute to the organization memory? Among several references, we will approach the two-way communication model that James E. Grunig & Todd T. Hunt (1984) already presented and the concept of mass self-communication of Manuel Castells (2010). Castells also tells us that we have moved from traditional media to a system of communication networks. For Scott Kirsner (2010), we have entered an era of digital creativity, where artists have the tools to do what they imagined and the public no longer wants to just consume cultural goods, but instead to have a voice and participate. The creativity process is now depending on the public choice as they wander through the screen. It is the receiver who owns an object which can be exchanged. Virtual reality has encouraged the receiver to abandon its position of passive observer and to become a participant agent, which implies a challenge to organizations: inventing new forms of interfaces. Therefore, we intend to find new and effective online tools that can be used by cultural organizations; the best way to manage them; to show how organizations can create a community with the public and how the availability of online content and its archive can contribute to the organizations’ memory.