944 resultados para Scholarship Incentive Award


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Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.

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In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

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Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

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In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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This Work Project seeks to analyze the viability, utility and best way of implementing mechanisms of double accounting and of insertion of low (or null) sales objectives in an incentives program. The main findings are that both processes are possible and to a certain extent advisable, although in very specific ways and with some limitations. Double accounting processes are especially effective between different segments and networks and should have a greater impact in the first evaluation periods of each case and the null objectives, albeit usable, are recommended to be always substituted by positive objectives, even if quite small. Moreover, it is concluded that the formal structure of the incentives program influences significantly these concepts, namely concerning the duration of the evaluation periods and the interaction of the objectives of different entities for both the vertical (hierarchic) and horizontal (individual and collective) levels.

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Within a research project on «academic excellence in the state school», this paper is a contribution to the sociological reflection on the cultural and organisational characteristics of the school and its relationship with the academic success of students. The data we present stem from a case study underway at a secondary school in the north of Portugal, referring to the universe of students that since 2003 have distinguished themselves for achieving grades equal to or greater than 18 (on a scale of 0 to 20) and have thus been included in the school’s Framework of Excellence. From a contextual approach to this educational practice, we focused on the cultural characteristics of the school/subject as analytical support for the study of school and non-school dimensions in their mutual connections. To this end, we used the information from document analysis and data collected from a questionnaire survey administered to more than two-thirds of the students included in the above-mentioned Framework of Excellence. Subsequently, we will use the data from this survey to understand the extent to which academic excellence is perceived as an indivisible social construction of the school’s political and organisational matrix, particularly in terms of the educational and teaching guidelines adopted by the management body. We will conclude by questioning the meaning of the school’s management policies regarding the emphasis on educational outcomes, with particular focus on the representations of excellent students in the processes of school leadership, teaching organisation, school merit and justice.

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Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2013