Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

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.

Towards a future SCADA

Currently, Power Systems (PS) already accommodate a substantial penetration of DG and operate in competitive environments. In the future PS will have to deal with largescale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. This cannot be done with the traditional PS operation. SCADA (Supervisory Control and Data Acquisition) is a vital infrastructure for PS. Current SCADA adaptation to accommodate the new needs of future PS does not allow to address all the requirements. In this paper we present a new conceptual design of an intelligent SCADA, with a more decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). Once a situation is characterized, data and control options available to each entity are re-defined according to this context, taking into account operation normative and a priori established contracts. The paper includes a case-study of using future SCADA features to use DER to deal with incident situations, preventing blackouts.

The role of demand response in future power systems

Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Emergency energy resource management in SmartGrids

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.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Auction of financial transmission rights in electricity market environment

An auction model is used to increase the individual profits for market players with products they do not use. A Financial Transmission Rights Auction has the goal of trade transmission rights between Bidders and helps them raise their own profits. The ISO plays a major rule on keep the system in technical limits without interfere on the auctions offers. In some auction models the ISO decide want bids are implemented on the network, always with the objective maximize the individual profits for all bidders in the auction. This paper proposes a methodology for a Financial Transmission Rights Auction and an informatics application. The application receives offers from the purchase and sale side and considers bilateral contracts as Base Case. This goal is maximize the individual profits within the system in their technical limits. The paper includes a case study for the 30 bus IEEE test case.

An integrated system to support electricity tariff contract definition

This paper presents an integrated system that helps both retail companies and electricity consumers on the definition of the best retail contracts and tariffs. This integrated system is composed by a Decision Support System (DSS) based on a Consumer Characterization Framework (CCF). The CCF is based on data mining techniques, applied to obtain useful knowledge about electricity consumers from large amounts of consumption data. This knowledge is acquired following an innovative and systematic approach able to identify different consumers’ classes, represented by a load profile, and its characterization using decision trees. The framework generates inputs to use in the knowledge base and in the database of the DSS. The rule sets derived from the decision trees are integrated in the knowledge base of the DSS. The load profiles together with the information about contracts and electricity prices form the database of the DSS. This DSS is able to perform the classification of different consumers, present its load profile and test different electricity tariffs and contracts. The final outputs of the DSS are a comparative economic analysis between different contracts and advice about the most economic contract to each consumer class. The presentation of the DSS is completed with an application example using a real data base of consumers from the Portuguese distribution company.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

The Greatest lover: a post-colonial rewriting of My Fair Lady

INTRODUCTION The popular Hong Kong comedy, The Greatest Lover, re-incarnates one of the most popular western musicals, My Fair Lady. OBJECTIVES 1. To find out in what major ways My Fair Lady was rewritten as the Hong Kong Cantonese movie, Gungzi Docing (The Greatest Lover). 2. To find out the socio-political, socio-linguistic, and gender ideology behind the rewriting. METHODOLOGY 1. To note the similarity of the themes for both works – a creator falling in love with his/her creation, and class prejudice and cross-class romance. 2. To note how the times of The Greatest Lover differ from that of My Fair Lady. 3. To note how the main characters in The Greatest Lover differ from My Fair Lady in terms of profession, gender, etc. 4. To note how the plot of The Greatest Lover differs from that of My Fair Lady. 5. To note how focus on language in The Greatest Lover compares with that in My Fair Lady. 6. To discuss the ideological implications of the differences noted above, e.g. women in Hong Kong today have much higher status than women in Victorian England; the conflict between local Hong Kong people and both legal and illegal immigrants from Mainland China is even more serious than that between the British upper middle class and the lower class during the Victorian period. 7. Andre Lefevere (1992) argues that translation and adaptation are rewriting informed and influenced by the rewriter’s ideology, among other things. 8. Both Aline Remael (1995) and Patrick Cattrysse (1992) think that film adaptation is a kind of translation. 9. Sirkkus Aaltonen (2000) argues that drama translation mirrors the ideologies of the target society. CONCLUSION 1. The Greatest Lover projects local cultural significance onto My Fair Lady by helping us to appreciate an important Western work of art through the Hong Kong Cantonese perspective. 2. Broader issues in translation and intercultural studies are also considered.

A actual regulação do crédito ao consumo

"Consumidores somos todos nós como impressivamente se ex­pressou John F. Kennedy em 15 de Março de 1962. E diríamos que "consumidores de credito "somos muitos. É neste contexto que assume especial relevância a recente aprovação, no nosso ordenamento jurídico, de nova normativa reguladora do crédito ao consumo. Por outro lado, será de realçar o comando consti­tucional que prevê a protecção dos consumidores. De facto, prescreve o artigo 60° da Constituição da República Portuguesa que "os consu­midores têm direito à qualidade dos bens e serviços consumidos, à for­mação e à informação, à protecção da saúde, da segurança e dos seus interesses económicos, bem como à reparação dos danos". lmporta, pois, conhecer em rigor as normas que actualmente re­gem o acesso e a regulação dos contratos de crédito ao consumo, num contexto de harmonização comunitária deste instituto jurídico-económico. Será oportuno, sobretudo, compreender de que forma o diploma que actualmente rege a matéria em questão protege de modo mais vin­cado a parte considerada economicamente mais débil.

Estágio profissional: Câmara Municipal da Trofa

Relatório de Estágio apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria Orientador: Rodrigo Mário Oliveira Carvalho, Dr. Coorientador: Vicente António Fernandes Seixas, Dr.

Gestão do risco em mercados de energia eléctrica recorrendo ao VaR por simulação de Monte Carlo

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia.

Sistema de suporte à negociação numa empresa de prestação de serviços médicos

Nesta dissertação foram estudados métodos de apoio à negociação com o objectivo de encontrar o melhor modelo de negociação para uma empresa prestadora de serviços médicos. O modelo utilizado foi o WinWin e para testar o modelo foi desenvolvido um sistema de apoio à negociação com os clientes. A aplicação foi desenvolvida com o objectivo de conseguir optimizar percursos e reduzir custos, dentro de certas condições, da forma mais eficiente possível, e que fosse de acordo aos interesses do processo de negociação e do contrato com o cliente. Com isto, a aplicação foi testada com 70 contratos, tendo conseguido simular vários grafos que conseguiam alocar todas as consultas dos contratos de forma a respeitar os objectivos impostos por este, e sendo eficientes no sentido de reduzir os custos e tempo de deslocação, diminuindo consequentemente os custos do contrato para o cliente. A redução dos custos para o cliente permite à empresa prestadora de serviços médicos ser mais competitiva face aos seus concorrentes, assim como possuir uma maior margem de manobra face ao processo de negociação, pois também através das simulações conseguem ter uma noção mais precisa dos custos totais de um contrato, diminuindo assim possíveis riscos de um contrato mal estimado.