Intelligent power system

Artificial intelligence techniques are being widely used to face the new reality and to provide solutions that can make power systems undergo all the changes while assuring high quality power. In this way, the agents that act in the power industry are gaining access to a generation of more intelligent applications, making use of a wide set of AI techniques. Knowledge-based systems and decision-support systems have been applied in the power and energy industry. This article is intended to offer an updated overview of the application of artificial intelligence in power systems. This article paper is organized in a way so that readers can easily understand the problems and the adequacy of the proposed solutions. Because of space constraints, this approach can be neither complete nor sufficiently deep to satisfy all readers’ needs. As this is amultidisciplinary area, able to attract both software and computer engineering and power system people, this article tries to give an insight into themost important concepts involved in these applications. Complementary material can be found in the reference list, providing deeper and more specific approaches.

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures supported by an FTT-SE Network

Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

Marketing e imagem: o caso do Hospital de Santa Maria - Porto

O sector da saúde ocupa, actualmente, um espaço muito visível na nossa sociedade, quer seja em termos económicos como sociais. Os utentes têm alterado as suas atitudes, tendo vindo a preocupar-se e a exigir cada vez mais dos serviços de saúde. Estas mudanças têm conduzido as Organizações a desenvolver serviços mais orientados para o marketing. Desta forma, reconhece-se a importância dessa avaliação como forma de aumentar os níveis de satisfação dos utentes e da eficiência organizacional. A estratégia de Marketing, passa pela escolha dos mercados alvo, da sua posição competitiva face aos seus concorrentes, que permita atender os seus utentes. Neste contexto, o Marketing poderá desempenhar um papel preponderante na rentabilidade e competitividade das Organizações, pelo que se achou pertinente desenvolver as estratégias de Marketing numa Instituição Privada de Saúde. Assim, no âmbito do 2º. Ano de Mestrado de Gestão das Organizações, ramo Unidades de Saúde, foi realizado um estágio na área do Marketing e Imagem, que teve lugar no Hospital de Santa Maria – Porto. Assim, com este relatório pretende-se reflectir sobre as actividades desenvolvidas, desde a conceptualização à realização das mesmas, e o seu impacto na Organização e, simultaneamente, disponibilizar um instrumento de avaliação da Unidade Curricular.

Optimização da estação de tratamento de águas residuais de Crestuma

O presente trabalho, elaborado entre Fevereiro e Julho de 2011, pretendeu analisar o impacto de algumas estratégias de optimização, adoptadas no âmbito da gestão de processo. As soluções estudadas tiveram como objectivo fazer face a alguns problemas de funcionamento da estação de tratamento de águas residuais (ETAR) de Crestuma, com recurso aos meios existentes. Para esse efeito foi realizada uma análise ao histórico dos registos de exploração referentes ao período de Janeiro de 2008 a Julho de 2011, pois foi considerado que este seria o período necessário para a análise e apuramento de resultados conclusivos. A ETAR fica situada na freguesia de Crestuma, actualmente com 2619 habitantes, localizada na confluência do regato de Vessadas com o rio Douro. Destina-se a tratar as águas residuais provenientes do sistema de drenagem de três localidades, S. Fioso, S. Picoto e S. Vessada, contribuindo para a despoluição do rio Douro. Genericamente, a ETAR tem apresentado um desempenho bastante satisfatório, respeitando os valores limites de emissão previstos na legislação actual (Decreto-Lei 152/97). A permanência de grandes quantidades de lama no processo, associada a uma elevada idade das lamas, está na origem da sua má sedimentabilidade, dificultando, por sua vez, a sua remoção do sistema. Com objectivo de se conseguir remover as lamas biológicas de uma forma mais eficiente, foi adoptada uma estratégia que compreendeu duas etapas. Com a finalidade de melhorar a sedimentabilidade, numa primeira etapa foi introduzido no processo um produto biológico, composto essencialmente por fungos, comercialmente conhecido por Optibiom 7450L. Com vista a obter-se uma maior eficiência na desidratação das lamas, a segunda etapa consistiu na substituição do polímero usado na lama espessada, por outro, de composição diferente, comercialmente conhecido por Easy 6040. Com as alterações introduzidas, foi possível obter um melhor controlo do processo e convergir para parâmetros de funcionamento mais próximos dos valores referidos na bibliografia. As alterações mais relevantes foram verificadas nos valores de sólidos suspensos totais (SST) no reactor biológico e na recirculação, tendo-se obtido valores médios de 3846 e 9716 mg/L, respectivamente (correspondendo a valores anteriores ao tratamento de 5301 e 7430 mg/L). Assim, a razão entre as concentrações de SST na corrente de recirculação e no reactor biológico passou de 1,4 para 2,6. A idade das lamas diminuiu de 42 para 36 dias com a adição do polímero Easy 6040 e o índice volumétrico de lamas apresentou uma redução, de 134 mL/g para 100 mL/g, o que se traduziu numa melhor sedimentabilidade das lamas. Desta forma, obteve-se uma diminuição de 33,3% no volume de lama produzida por m3 de afluente tratado, bem como uma redução de 27% no número de horas de funcionamento da centrífuga e um decréscimo ligeiro no consumo global de energia da ETAR (0,89%). Conclui-se que as alterações introduzidas no processo, adição de um produto biológico composto por fungos (Optibiom 7450L) e substituição do polímero usado na lama espessada por outro de composição diferente (Easy 6040), conduziram a uma melhoria no funcionamento do tratamento biológico da ETAR de Crestuma.

Innovation through virtual communities of Practice: motivation and constraints in the knowledge-creation process

Communities of Practice are places which provide a sound basis for organizational learning, enabling knowledge creation and acquisition thus improving organizational performance, leveraging innovation and consequently increasing competitively. Virtual Communities of Practice (VCoP‟s) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. The ongoing case study, described here, aims to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of the VCoP‟s to which they belong. Based on a literature review, we have identified several factors that influence such processes; they will be used to analyse the results of interviews carried out with the leaders of VCoP‟s in four multinationals. As future work, a questionnaire will be developed and administered to the other members of these VCoP‟s

Virtual communities of practice: investigating motivations and constraints in the processes of knowledge creation and transfer

With accelerated market volatility, faster response times and increased globalization, business environments are going through a major transformation and firms have intensified their search for strategies which can give them competitive advantage. This requires that companies continuously innovate, to think of new ideas that can be transformed or implemented as products, processes or services, generating value for the firm. Innovative solutions and processes are usually developed by a group of people, working together. A grouping of people that share and create new knowledge can be considered as a Community of Practice (CoP). CoP’s are places which provide a sound basis for organizational learning and encourage knowledge creation and acquisition. Virtual Communities of Practice (VCoP's) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. Nevertheless, it is known that not all CoP's and VCoP's share the same levels of performance or produce the same results. This means that there are factors that enable or constrain the process of knowledge creation. With this in mind, we developed a case study in order to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of VCoP's. Results show that organizational culture and professional and personal development play an important role in these processes. No interviewee referred to direct financial rewards as a motivation factor for participation in VCoPs. Most identified the difficulty in aligning objectives established by the management with justification for the time spent in the VCoP. The interviewees also said that technology is not a constraint.

Virtual communities of practice: examining the motivations and constraints in their knowledge creation and knowledge transfer preocesses

Paper accepted for the OKLC 2009 - International Conference on Organizational Learning, Knowledge and Capabilities (26-28th, April 2009, Amsterdam, the Netherlands).

Stabilization constraints from different-average public debt levels in a Monetary Union with country-size asymmetry

In the sequence of the recent financial and economic crisis, the recent public debt accumulation is expected to hamper considerably business cycle stabilization, by enlarging the budgetary consequences of the shocks. This paper analyses how the average level of public debt in a monetary union shapes optimal discretionary fiscal and monetary stabilization policies and affects stabilization welfare. We use a two-country micro-founded New-Keynesian model, where a benevolent central bank and the fiscal authorities play discretionary policy games under different union-average debt-constrained scenarios. We find that high debt levels shift monetary policy assignment from inflation to debt stabilization, making cooperation welfare superior to noncooperation. Moreover, when average debt is too high, welfare moves directly (inversely) with debt-to-output ratios for the union and the large country (small country) under cooperation. However, under non-cooperation, higher average debt levels benefit only the large country.

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.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

Inexact restoration approaches to solve mathematical program with complementarity constraints

Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases. This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions. The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.

Numerical experiments with a modified regularization scheme for mathematical programs with complementarity constraints

On this paper we present a modified regularization scheme for Mathematical Programs with Complementarity Constraints. In the regularized formulations the complementarity condition is replaced by a constraint involving a positive parameter that can be decreased to zero. In our approach both the complementarity condition and the nonnegativity constraints are relaxed. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.

Estratégias de oferta em leilões simétricos no âmbito dos mercados liberalizados de electricidade

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

A feedback-based decentralised coordination model for distributed open real-time systems

Moving towards autonomous operation and management of increasingly complex open distributed real-time systems poses very significant challenges. This is particularly true when reaction to events must be done in a timely and predictable manner while guaranteeing Quality of Service (QoS) constraints imposed by users, the environment, or applications. In these scenarios, the system should be able to maintain a global feasible QoS level while allowing individual nodes to autonomously adapt under different constraints of resource availability and input quality. This paper shows how decentralised coordination of a group of autonomous interdependent nodes can emerge with little communication, based on the robust self-organising principles of feedback. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The proposed protocol is general enough to be used in a wide range of scenarios characterised by a high degree of openness and dynamism where coordination tasks need to be time dependent. As the reported results demonstrate, it requires less messages to be exchanged and it is faster to achieve a globally acceptable near-optimal solution than other available approaches.

Nano-CF: a Coordination Framework for macro-programming in wireless sensor networks

Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.