Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

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.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

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.

Relatório final de estágio numa equipa de futebol profissional tratamento conservador de pubalgia no futebol – estudo de caso

O estágio curricular é uma unidade do 2º semestre inserida no Mestrado em Fisioterapia, opção Desporto. Foi realizado de Janeiro a Maio de 2011, no Centro Desportivo de Fátima com a equipa de futebol sénior. Sendo o futebol uma área em enorme expansão e sobre a qual recaem as mais diversas atenções (financeiras, técnicas, médicas e dos media), e dado aos escassos recursos disponíveis, torna-se um desafio crescente actuar no plantel sénior das equipas de futebol. É cada vez mais desafiante para o profissional de saúde saber usufruir da disponibilização de recursos tendo em conta que qualquer lesão implica graves consequências, não só do ponto de vista clínico, mas também do ponto de vista económico para o atleta, clube e seguradora. Dado que o futebol é um desporto muito dinâmico, em que todos os detalhes são importantes para decisão de um jogo, e como a competição leva à necessidade de aperfeiçoar constantemente as qualidades físicas para a prática desportiva, a avaliação física deve ser encarada como a principal ferramenta para iniciar as sessões de treino. Segundo Massada (2003), cerca de 60 a 70% das lesões ocorridas são minor, ou seja, acarretam poucos problemas funcionais no imediato, no entanto, estas lesões não devem ser menosprezadas, pois a nível clínico e funcional podem determinar graves consequências e levar a cronicidade, comprometendo o desempenho do atleta. Assim sendo, o fisioterapeuta deve estar munido de ferramentas diagnósticas e de avaliação especializadas na área, para minimizar as consequências das lesões, quer para o atleta, quer para o próprio clube. Outra competência do fisioterapeuta é a identificação e desenvolvimento das questões relevantes para investigação, que contribuem para o progresso do conhecimento e para a evolução técnica. Como parte da prática clínica na área do desporto, surge também a prevenção das lesões desportivas, de extrema importância, principalmente ao delinear estratégias e informar para a redução de ocorrência de lesões, diminuindo recidivas ou casos de cronicidade e, consequentemente, bom desempenho desportivo. Tendo isto em conta, ao longo do estágio foi elaborado um relatório final, seguidamente apresentado. Inicialmente é realizada a caracterização da instituição e equipa, seguido dos casos clínicos emergentes e de acompanhamento com os planos de intervenção elaborados, e um estudo de caso sobre a pubalgia. Finalmente, em anexo, apresenta-se a acção de prevenção realizada juntos aos jogadores e recolha bibliográfica para elaboração do estudo de caso.

Flexibility in a Stackelberg leadership with differentiated goods

We study the effects of product differentiation in a Stackelberg model with demand uncertainty for the first mover. We do an ex-ante and ex-post analysis of the profits of the leader and of the follower firms in terms of product differentiation and of the demand uncertainty. We show that even with small uncertainty about the demand, the follower firm can achieve greater profits than the leader, if their products are sufficiently differentiated. We also compute the probability of the second firm having higher profit than the leading firm, subsequently showing the advantages and disadvantages of being either the leader or the follower firm.

Neural networks for condition monitoring of wind turbines gearbox

Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.

A fractional perspective to financial indices

The application of mathematical methods and computer algorithms in the analysis of economic and financial data series aims to give empirical descriptions of the hidden relations between many complex or unknown variables and systems. This strategy overcomes the requirement for building models based on a set of ‘fundamental laws’, which is the paradigm for studying phenomena usual in physics and engineering. In spite of this shortcut, the fact is that financial series demonstrate to be hard to tackle, involving complex memory effects and a apparently chaotic behaviour. Several measures for describing these objects were adopted by market agents, but, due to their simplicity, they are not capable to cope with the diversity and complexity embedded in the data. Therefore, it is important to propose new measures that, on one hand, are highly interpretable by standard personal but, on the other hand, are capable of capturing a significant part of the dynamical effects.

Delay approximation of fractional integrals

This paper explores the calculation of fractional integrals by means of the time delay operator. The study starts by reviewing the memory properties of fractional operators and their relationship with time delay. Based on the time response of the Mittag-Leffler function an approximation of fractional integrals consisting of time delayed samples is proposed. The tuning of the approximation is optimized by means of a genetic algorithm. The results demonstrate the feasibility of the new perspective and the limits of their application.