A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

A influência do acompanhamento em suporte digital na motivação dos alunos de saxofone: relatório de estágio

I (Prática pedagógica)- Esta secção do Relatório de Estágio pretende apresentar elementos referentes ao Estágio do Ensino Especializado da Música no ensino do saxofone, efectuado na Escola de Música Luís António Maldonado Rodrigues, no ano lectivo 2012/2013. Neste estágio foram envolvidos e analisados três alunos, em níveis distintos de desenvolvimento, mas com orientações semelhantes no que respeita à organização do trabalho. Para cada aluno foram realizados trinta planos de aula, uma planificação anual e três gravações vídeo/áudio em contexto de sala de aula, permitindo uma análise e reflexão mais profunda do trabalho docente. A secção é composta pela caracterização da escola onde se realizou o estágio, através da sua contextualização/funcionamento, dos seus espaços e equipamentos, recursos humanos existentes e organização pedagógica. Posteriormente é efectuada a caracterização dos três alunos envolvidos no estágio, baseada na experiência docente e nos conhecimentos fornecidos pelas Unidades Curriculares do Mestrado em Ensino da Música. Seguidamente descrevem-se as práticas lectivas desenvolvidas ao longo do ano lectivo por parte do docente, incorporando linhas orientadoras da docência aplicadas na prática pedagógica. É feita uma análise crítica da actividade docente no âmbito do estágio do Ensino Especializado da Música, e, por último, uma conclusão desta primeira secção. .

RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks

Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.

The generalized multiprocessor periodic resource interface model for hierarchical multiprocessor scheduling

Composition is a practice of key importance in software engineering. When real-time applications are composed it is necessary that their timing properties (such as meeting the deadlines) are guaranteed. The composition is performed by establishing an interface between the application and the physical platform. Such an interface does typically contain information about the amount of computing capacity needed by the application. In multiprocessor platforms, the interface should also present information about the degree of parallelism. Recently there have been quite a few interface proposals. However, they are either too complex to be handled or too pessimistic.In this paper we propose the Generalized Multiprocessor Periodic Resource model (GMPR) that is strictly superior to the MPR model without requiring a too detailed description. We describe a method to generate the interface from the application specification. All these methods have been implemented in Matlab routines that are publicly available.

Real-time scheduling with resource sharing on uniform multiprocessors

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a uniform multiprocessor platform where each task may access at most one of |R| shared resources and at most once by each job of that task. The resources have to be accessed in a mutually exclusive manner. We propose an algorithm, GIS-vpr, which offers the guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that allows a task to migrate only when it accesses or releases a resource, then our algorithm also meets the deadlines with the same restriction on the task migration, if given processors 4 + 6|R| times as fast. The proposed algorithm, by design, limits the number of migrations per job to at most two. To the best of our knowledge, this is the first result for resource sharing on uniform multiprocessors with proven performance guarantee.

Provably good scheduling of sporadic tasks with resource sharing on a two-type heterogeneous multiprocessor platform

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of |R| shared resources. There are m1 processors of type-1 and m2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3Cvpr also meets deadlines if given processors 4+6*ceil(|R|/min(m1,m2)) times as fast. As far as we know, it is the first result for resource sharing on heterogeneous platforms with provable performance.

Desafios e potencialidades da metodologia SROI : um estudo de caso

Mestrado em Controlo e Gestão dos Negócios

A multi-objective approach for the motion planning of redundant manipulators

Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

Resource sharing in global fixed-priority preemptive multiprocessor scheduling

In this paper we consider global fixed-priority preemptive multiprocessor scheduling of constrained-deadline sporadic tasks that share resources in a non-nested manner. We develop a novel resource-sharing protocol and a corresponding schedulability test for this system. We also develop the first schedulability analysis of priority inheritance protocol for the aforementioned system. Finally, we show that these protocols are efficient (based on the developed schedulability tests) for a class of priority-assignments called reasonable priority-assignments.

Provably good multiprocessor scheduling with resource sharing

We present a 12(1 + 3R/(4m)) competitive algorithm for scheduling implicit-deadline sporadic tasks on a platform comprising m processors, where a task may request one of R shared resources.

Capital social no ELSA-Brasil: confiabilidade teste-reteste do Resource Generator scale

OBJETIVO: Estimar a confiabilidade teste-reteste dos itens do Resource Generator scale para avaliação de capital social no Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil).MÉTODOS: A escala de capital social foi aplicada em subamostra de 281 participantes dos seis Centros de Investigação do ELSA, em duas oportunidades, com intervalo de sete a 14 dias. O instrumento é constituído por 31 itens que representam situações concretas para avaliar o acesso a diferentes tipos de recursos, além de avaliar a fonte dos recursos disponíveis (familiares, amigos ou conhecidos). A análise estatística foi realizada por meio de estatísticas kappa (k) e kappa ajustado pela prevalência (ka).RESULTADOS: Os recursos sociais investigados foram encontrados com grande frequência (acima de 50%). Em relação à presença ou ausência dos recursos, as estimativas de confiabilidade ajustadas pela prevalência (ka) variaram de 0,54 a 0,97. No que se refere à fonte de recurso, essas estimativas variaram de ka = 0,45 (alguém que tenha bons contatos com a mídia) a ka = 0,86 (alguém que se formou no Ensino Médio).CONCLUSÕES: A escala apresentou níveis adequados de confiabilidade, que variaram de acordo com o tipo de recurso.

Simulation relations, interface complexity, and resource optimality for real-time hierachical systems

Compositional schedulability analysis of hierarchical realtime systems is a well-studied problem. Various techniques have been developed to abstract resource requirements of components in such systems, and schedulability has been addressed using these abstract representations (also called component interfaces). These approaches for compositional analysis incur resource overheads when they abstract components into interfaces. In this talk, we define notions of resource schedulability and optimality for component interfaces, and compare various approaches.