985 resultados para Non-technical losses
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Mode of access: Internet.
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Mode of access: Internet.
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Considering the rapid growth of call centres (CCs) in India, its implications for businesses in the UK and a scarcity of research on human resource management (HRM) related issues in Indian CCs, this research has two main aims. First, to highlight the nature of HRM systems relevant to Indian call centres. Second, to understand the significance of internal marketing (IM) in influencing the frontline employees’ job-related attitudes and performance. Rewards being an important component of IM, the relationships between different types of rewards as part of an IM strategy, attitudes and performance of employees in Indian CCs will also be examined. Further, the research will investigate which type of commitment mediates the link between rewards and performance and why. The data collection will be via two phases. The first phase would involve a series of in-depth interviews with both the managers and employees to understand the functioning of CCs, and development of suitable HRM systems for the Indian context. The second phase would involve data collection through questionnaires distributed to the frontline employees and supervisors to examine the relationships among IM, employee attitudes and performance. Such an investigation is expected to contribute to development of better theory and practice.
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This paper presents ELECON - Electricity Consumption Analysis to Promote Energy Efficiency Considering Demand Response and Non-technical Losses, an international research project that involves European and Brazilian partners. ELECON focuses on energy efficiency increasing through consumer´s active participation which is a key area for Europe and Brazil cooperation. The project aims at significantly contributing towards the successful implementation of smart grids, focussing on the use of new methods that allow the efficient use of distributed energy resources, namely distributed generation, storage and demand response. ELECON puts together researchers from seven European and Brazilian partners, with consolidated research background and evidencing complementary competences. ELECON involves institutions of 3 European countries (Portugal, Germany, and France) and 4 Brazilian institutions. The complementary background and experience of the European and Brazilian partners is of main relevance to ensure the capacities required to achieve the proposed goals. In fact, the European Union (EU) and Brazil have very different resources and approaches in what concerns this area. Having huge hydro and fossil resources, Brazil has not been putting emphasis on distributed renewable based electricity generation. On the contrary, EU has been doing huge investments in this area, taking into account environmental concerns and also the economic EU external dependence dictated by huge requirements of energy related products imports. Sharing these different backgrounds allows the project team to propose new methodologies able to efficiently address the new challenges of smart grids.
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The increasing importance of the integration of distributed generation and demand response in the power systems operation and planning, namely at lower voltage levels of distribution networks and in the competitive environment of electricity markets, leads us to the concept of smart grids. In both traditional and smart grid operation, non-technical losses are a great economic concern, which can be addressed. In this context, the ELECON project addresses the use of demand response contributions to the identification of non-technical losses. The present paper proposes a methodology to be used by Virtual Power Players (VPPs), which are entities able to aggregate distributed small-size resources, aiming to define the best electricity tariffs for several, clusters of consumers. A case study based on real consumption data demonstrates the application of the proposed methodology.
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Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Esta dissertação de mestrado tem como finalidade analisar a gestão das perdas não técnicas de energia elétrica e entender as metodologias adotadas nos projeto de combate a essas perdas desenvolvidas pelas concessionárias de distribuição. Trazendo, assim, à superfície, a importância de uma gestão eficiente das perdas comerciais para se obter uma boa manutenção dos seus índices. É no sistema de distribuição de energia onde ocorre a maior porcentagem das perdas dos sistemas elétricos de potência. Sendo, portanto, a parte do sistema elétrico com maior potencial para redução das perdas. Assim, o enfoque desta dissertação é fazer uma análise das perdas não técnicas, das formas de atuação sobre elas e das metodologias utilizadas pelas concessionárias atualmente, as quais serão apresentadas através de um estudo de caso.
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Pós-graduação em Engenharia Elétrica - FEIS
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.
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The past decade has witnessed a sharp increase in published research on energy and buildings. This paper takes stock of work in this area, with a particular focus on construction research and the analysis of non-technical dimensions. While there is widespread recognition as to the importance of non-technical dimensions, research tends to be limited to individualistic studies of occupants and occupant behavior. In contrast, publications in the mainstream social science literature display a broader range of interests, including policy developments, structural constraints on the diffusion and use of new technologies and the construction process itself. The growing interest of more generalist scholars in energy and buildings provides an opportunity for construction research to engage a wider audience. This would enrich the current research agenda, helping to address unanswered problems concerning the relatively weak impact of policy mechanisms and new technologies and the seeming recalcitrance of occupants. It would also help to promote the academic status of construction research as a field. This, in turn, depends on greater engagement with interpretivist types of analysis and theory building, thereby challenging deeply ingrained views on the nature and role of academic research in construction.