880 resultados para strategic management, generic competitive strategies, recession, response strategies, case study


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The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

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This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

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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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Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

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Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

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Energy Resources Management can play a very relevant role in future power systems in SmartGrid context, with high penetration of distributed generation and storage systems. This paper deals with the importance of resources management in incident situation. The system to consider a high penetration of distributed generation, demand response, storage units and network reconfiguration. A case study evidences the advantages of using a flexible SCADA to control the energy resources in incident situation.

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Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

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Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

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Mestrado em Contabilidade

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Na presente comunicação apresentamos parte dos resultados de um estudo de caso desenvolvido pelos autores no âmbito do Observatório de Segurança Escolar (OSE). A investigação a que nos propusemos resulta do desenvolvimento e aprofundamento de estudos que a equipa do OSE tem vindo a realizar nos últimos 6 anos (Sebastião, Campos, Alves e Merlini: 2010; Sebastião, Campos e Merlini: 2011) e justifica-se pela necessidade de análises contextualizadas da problemática de violência na escola, no sentido de contribuir para futuras estratégias e mecanismos de intervenção e prevenção sobre esta forma de violência. Tendo como ponto de partida os dados estatísticos nacionais sobre os incidentes de violência nas escolas1, procurámos compreender como os traços identificados a nível nacional se traduzem e são reconfigurados territorialmente. Em particular, saber porque é que escolas situadas em territórios com condições sociais idênticas apresentam níveis de violência e abordagens de regulação diferenciadas. Partindo de uma abordagem meso analítica do fenómeno de violência na escola, que engloba as perspetivas organizacional (Burns e Flam: 2000; Mouzelis: 2000; Torres e Palhares: 2010; Lima: 2001) e ecológica (Fuchs: 2008; Machado: 2008; Carvalho, 2010; Leal: 2010), o estudo privilegiou uma estratégia metodológica intensiva e desenvolveu-se em três territórios do Concelho de Sintra. Nesta apresentação o foco analítico incide sobre as estratégias e mecanismos acionados pelas escolas nos processos de regulação (prevenção e intervenção) das ocorrências de violência na escola, considerando a diversidade de condições contextuais e organizacionais. Ou seja, analisamos o modo como as escolas respondem aos incidentes e procuram pacificar os seus quotidianos e as condições em que o fazem. Tendo em conta as possibilidades de ação encontradas, identificámos um conjunto de fatores significativos nos processos de regulação da violência, entre os quais destacamos: as lideranças e práticas organizacionais; as orientações para a intervenção e a importância da priorização da violência e os instrumentos para intervir, como a constituição de gabinetes de mediação de conflitos. Face às condições para agir, verificámos que as escolas demonstram ter margem para adequar, planear e implementar estratégias de resposta, adotando modalidades de resolução da conflitualidade/violência, diversificadas, independentemente desta ter origem, ou não, em condições externas à escola.

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The development of economical relations increases the interaction between organizations and stakeholders. It is no more acceptable to manage an organization under a transactional perspective where suppliers had a fundamental role. Nowadays organizations are being managed under a relational perspective where relations and relationship management in general have consequences in identity management (Hakansson e Snehota, 1989, 1995). A correct perception and management of identity is necessary to achieve distinctiveness in the competitive environment. This way, identity is influenced by relations with stakeholders in general and particularly with competitors. The ICIG concept states that identity is related with the values of the organization and it helps creating distinctiveness in the competitive environment (Van Riel, Balmer, 1997); Baker and Balmer (1997) state that identity is what the organization is; Suvatjis and de Chernatony (2005) refer that expressing identity is a dynamic process that evolves the use of a management model to face context changes; Kapferer (1991) states that brand identity is the project, the self conception of the brand. After reviewing and confronting literature under the plethora of identities’ concepts and perspectives (He, Balmer, 2007) one can’t find an integrative answer with all the elements that contribute to identity of organizations. The authors are strongly interested to contribute to the elimination of this limitation and to answer to strategic management needs. In a marketing context one can find: - the corporate identity approach that is focused in the distinctive attributes of an organization (Abratt, Balmer, Marwick e Fill, Stuart, Balmer and Gray, Alessandri, Suvatjis and de Chernatony) - the brand identity approach (related with the application of corporate identity studies to brands) - Kapferer, Semprini, Aaker, de Chernatony). Kapferer (1991), one of the most prolific authors in this field was the first author to integrate identity in a brand concept. In his view, identity is an emission concept. This idea is shared also by Aaker (1996). Yet, identity has to be managed in a competitive environment which is constantly changing. After reviewing and confronting literature, authors select concepts that are generally accepted by the investigators in order to design a model to analyze and manage identity: - corporate identity models: personality, image/reputation, culture, philosophy, mission, strategy, structure, communication - some of these concepts derive from identity models and others from identity management models; - brand identity models – Kapferer (1991, 2008) identity prism, witch is basis of literature in this field: culture, physical facet, personality, relationship (between brand and consumer), reflected consumer, consumers` self-concept. After discussion authors decide to include other concept in line with other authors` view: country of origin (Aaker, 1996). A discussion eliminates the twin concepts and the final selection is as follows: personality, image/reputation, culture (including philosophy and mission), strategy, structure, communication, culture, physical facet, relationship (between brand and consumer), reflected consumer, consumers` self-concept and according to authors` reflections “relationships” deriving from competitors` actions in competitive environment. Competitors’ actions and decisions have a stronger influence in the organizations` positioning than any other stakeholder as stated before. This is a work in progress towards a new model in identity analysis and management so an exploratory study will follow inquiring experts on identity in order to evaluate these concepts and correct the theoretical perspectives.

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Dissertação de Mestrado em Gestão de Empresas/MBA.

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Mestrado em Controlo e Gestão dos Negócios