762 resultados para Buyback programs


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LUDA is a research project of Key Action 4 "City of Tomorrow & Cultural Heritage" of the programme "Energy, Environment and Sustainable Development" within the Fifth Framework Programme of the European Commission

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A critical analysis of the Supplementary Feeding Programs which have been undertaken around the world is presented. Although only a few programs have been rigorously evaluated it seems that in relation to their main objectives, most of them have not proved to be successful. Some suggestions for improvement are put forward and the particular case of the Brazilian programs is assessed in detail.

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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.

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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

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Objective: To assess different factors influencing adiponectinemia in obese and normal-weight women; to identify factors associated with the variation (Δ) in adiponectinemia in obese women following a 6-month weight loss program, according to surgical/non-surgical interventions. Methods: We studied 100 normal-weight women and 112 obese premenopausal women; none of them was on any medical treatment. Women were characterized for anthropometrics, daily macronutrient intake, smoking status, contraceptives use, adiponectin as well as IL-6 and TNF-α serum concentrations. Results: Adiponectinemia was lower in obese women (p < 0.001), revealing an inverse association with waist-to-hip ratio (p < 0.001; r = –0.335). Normal-weight women presented lower adiponectinemia among smokers (p = 0.041); body fat, waist-to-hip ratio, TNF-α levels, carbohydrate intake, and smoking all influence adiponectinemia (r 2 = 0.436). After weight loss interventions, a significant modification in macronutrient intake occurs followed by anthropometrics decrease (chiefly after bariatric procedures) and adiponectinemia increase (similar after surgical and non-surgical interventions). After bariatric intervention, Δ adiponectinemia was inversely correlated to Δ waist circumference and Δ carbohydrate intake (r 2 = 0.706). Conclusion: Anthropometrics, diet, smoking, and TNF-α levels all influence adiponectinemia in normal-weight women, although explaining less than 50% of it. In obese women, anthropometrics modestly explain adiponectinemia. Opposite to non-surgical interventions, after bariatric surgery adiponectinemia increase is largely explained by diet composition and anthropometric changes.

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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.

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After a historical introduction, the bulk of the thesis concerns the study of a declarative semantics for logic programs. The main original contributions are: ² WFSX (Well–Founded Semantics with eXplicit negation), a new semantics for logic programs with explicit negation (i.e. extended logic programs), which compares favourably in its properties with other extant semantics. ² A generic characterization schema that facilitates comparisons among a diversity of semantics of extended logic programs, including WFSX. ² An autoepistemic and a default logic corresponding to WFSX, which solve existing problems of the classical approaches to autoepistemic and default logics, and clarify the meaning of explicit negation in logic programs. ² A framework for defining a spectrum of semantics of extended logic programs based on the abduction of negative hypotheses. This framework allows for the characterization of different levels of scepticism/credulity, consensuality, and argumentation. One of the semantics of abduction coincides with WFSX. ² O–semantics, a semantics that uniquely adds more CWA hypotheses to WFSX. The techniques used for doing so are applicable as well to the well–founded semantics of normal logic programs. ² By introducing explicit negation into logic programs contradiction may appear. I present two approaches for dealing with contradiction, and show their equivalence. One of the approaches consists in avoiding contradiction, and is based on restrictions in the adoption of abductive hypotheses. The other approach consists in removing contradiction, and is based in a transformation of contradictory programs into noncontradictory ones, guided by the reasons for contradiction.

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OBJECTIVE Assessment of prevalence of health promotion programs in primary health care units within Brazil’s health system. METHODS We conducted a cross-sectional descriptive study based on telephone interviews with managers of primary care units. Of a total 42,486 primary health care units listed in the Brazilian Unified Health System directory, 1,600 were randomly selected. Care units from all five Brazilian macroregions were selected proportionally to the number of units in each region. We examined whether any of the following five different types of health promotion programs was available: physical activity; smoking cessation; cessation of alcohol and illicit drug use; healthy eating; and healthy environment. Information was collected on the kinds of activities offered and the status of implementation of the Family Health Strategy at the units. RESULTS Most units (62.0%) reported having in place three health promotion programs or more and only 3.0% reported having none. Healthy environment (77.0%) and healthy eating (72.0%) programs were the most widely available; smoking and alcohol use cessation were reported in 54.0% and 42.0% of the units. Physical activity programs were offered in less than 40.0% of the units and their availability varied greatly nationwide, from 51.0% in the Southeast to as low as 21.0% in the North. The Family Health Strategy was implemented in most units (61.0%); however, they did not offer more health promotion programs than others did. CONCLUSIONS Our study showed that most primary care units have in place health promotion programs. Public policies are needed to strengthen primary care services and improve training of health providers to meet the goals of the agenda for health promotion in Brazil.

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ABSTRACT OBJECTIVE To describe methods and challenges faced in the health impact assessment of vaccination programs, focusing on the pneumococcal conjugate and rotavirus vaccines in Latin America and the Caribbean. METHODS For this narrative review, we searched for the terms "rotavirus", "pneumococcal", "conjugate vaccine", "vaccination", "program", and "impact" in the databases Medline and LILACS. The search was extended to the grey literature in Google Scholar. No limits were defined for publication year. Original articles on the health impact assessment of pneumococcal and rotavirus vaccination programs in Latin America and the Caribbean in English, Spanish or Portuguese were included. RESULTS We identified 207 articles. After removing duplicates and assessing eligibility, we reviewed 33 studies, 25 focusing on rotavirus and eight on pneumococcal vaccination programs. The most frequent studies were ecological, with time series analysis or comparing pre- and post-vaccination periods. The main data sources were: health information systems; population-, sentinel- or laboratory-based surveillance systems; statistics reports; and medical records from one or few health care services. Few studies used primary data. Hospitalization and death were the main outcomes assessed. CONCLUSIONS Over the last years, a significant number of health impact assessments of pneumococcal and rotavirus vaccination programs have been conducted in Latin America and the Caribbean. These studies were carried out few years after the programs were implemented, meet the basic methodological requirements and suggest positive health impact. Future assessments should consider methodological issues and challenges arisen in these first studies conducted in the region.

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Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia.

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XSLT is a powerful and widely used language for transforming XML documents. However, its power and complexity can be overwhelming for novice or infrequent users, many of whom simply give up on using this language. On the other hand, many XSLT programs of practical use are simple enough to be automatically inferred from examples of source and target documents. An inferred XSLT program is seldom adequate for production usage but can be used as a skeleton of the final program, or at least as scaffolding in the process of coding it. It should be noted that the authors do not claim that XSLT programs, in general, can be inferred from examples. The aim of Vishnu—the XSLT generator engine described in this chapter—is to produce XSLT programs for processing documents similar to the given examples and with enough readability to be easily understood by a programmer not familiar with the language. The architecture of Vishnu is composed by a graphical editor and a programming engine. In this chapter, the authors focus on the editor as a GWT Web application where the programmer loads and edits document examples and pairs their content using graphical primitives. The programming engine receives the data collected by the editor and produces an XSLT program.

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Impact Assessment and Project Appraisal, vol. 22, n.1, March 2004, p. 47–62

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Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.