997 resultados para Offline optimization
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.
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The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.
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The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.
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Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.
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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia
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Atualmente a vantagem competitiva de uma empresa passa pela sua rápida adaptação às variações de procura do mercado, sendo necessário garantir elevados níveis de produtividade e, simultaneamente, grande flexibilidade, indispensável ao fabrico de pequenos lotes. A necessidade de ajuste do processo e a diminuição da média de vida do produto levam a paragens cada vez mais frequentes da célula de fabrico para programação e afinação, com consequentes perdas de produtividade. De forma a dar resposta a estes problemas, neste trabalho é testada a viabilidade da utilização da programação e simulação offline de tarefas de lixamento na Grohe Portugal, complementando a solução com o desenvolvimento de um novo método de afinação do programa, permitindo uma adaptação às flutuações do processo produtivo. Para isso foi necessário analisar o estado da arte dos robôs industriais na área de acabamento superficial e respetivos métodos de programação. Em seguida, após um trabalho prévio rigoroso de preparação e modelação da célula de trabalho, é possível fazer a programação offline das várias rotinas e trajetórias complexas que compõem um ciclo de lixamento de um produto, contribuindo para o aumento da qualidade do produto final sem comprometer os níveis de produtividade. Nesta dissertação são descritos e detalhados alguns dos procedimentos fulcrais no sucesso da aplicação deste método de programação. Por último é feita uma nova abordagem ao método de ajuste ponto-a-ponto convencional, desenvolvendo-se para isso um sistema de ajuste automático do programa, dotando o robô da capacidade de se adaptar às variações do processo, assegurando a consistência do mesmo. Foram realizados testes em pequena escala, extrapolando-se os resultados para a aplicação deste novo método no processo produtivo da Grohe Portugal, como forma de complemento ao método convencional de ajuste ponto-a-ponto do programa, reduzindo o tempo de paragem da célula de trabalho.
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Dissertação para obtenção do Grau de Doutor em Engenharia Química, especialidade de Engenharia Bioquímica
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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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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Field Lab of Entrepreneurial Innovative Ventures
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The objective of this work project is to analyse and discuss the importance of the “Cost to Serve” as a differentiation key factor, by accessing cost to serve customers of a Portuguese subsidiary of a multinational company, which is operating in the sector of fast moving consumer goods (FMCG) – Unilever – Jerónimo Martins (UJM). I will also suggest and quantify key proposals to decrease costs and increase customers’ value. Hence, the scope of this work project is focused on logistics and distribution processes of the company supply chain.
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This work project focuses on developing new approaches which enhance Portuguese exports towards a defined German industry sector within the information technology and electronics fields. Firstly and foremost, information was collected and a set of expert and top managers’ interviews were performed in order to acknowledge the demand of the German market while identifying compatible Portuguese supply capabilities. Among the main findings, Industry 4.0 presents itself as a valuable opportunity in the German market for Portuguese medium sized companies in the embedded systems area of expertise for machinery and equipment companies. In order to achieve the purpose of the work project, an embedded systems platform targeting machinery and equipment companies was suggested as well as it was developed several recommendations on how to implement it. An alternative approach for this platform was also considered within the German market namely the eHealth sector having the purpose of enhancing the current healthcare service provision.
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The present paper is a personal reflection on a work project carried out to promote exports from Portugal to Germany in the IT area, under consideration of the deliverables required by the clients CCILA and Anetie. The project outcome approaches the fact that the majority of the Portuguese market players has disadvantages in size and does rarely coordinate activities among each other, which hinders them to export successfully on a broad scale. To bring together Portuguese delivery potential and German market demand, expert interviews were conducted. Based on the findings, a concept was developed to overcome the domestic collaboration issues in order to strengthen the national exports in the identified sector - embedded systems implementation services for machinery and equipment companies.
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This work project regards a challenge presented by a Portuguese organization on the retail sector, SONAEMC, which is a case study of how and why fruit shrinkage occurs in the fruit supply chain within their convenience stores. A qualitative research methodology enabled to infer in which stages throughout the chain shrinkage’s causes occur and, to conclude that internal rules for procedures and processes are not always followed and whose compliance would be enough to reduce fruit shrinkage. The key conclusion is that if fruit stock loss is reduced by as much as 15% the category’s profitability could increase about 8%.
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Phosphorus (P) is becoming a scarce element due to the decreasing availability of primary sources. Therefore, recover P from secondary sources, e.g. waste streams, have become extremely important. Sewage sludge ash (SSA) is a reliable secondary source of P. The use of SSAs as a direct fertilizer has very restricted legislation due to the presence of inorganic contaminants. Furthermore, the P present in SSAs is not in a plant-available form. The electrodialytic (ED) process is one of the methods under development to recover P and simultaneously remove heavy metals. The present work aimed to optimize the P recovery through a 2 compartment electrodialytic cell. The research was divided in three independent phases. In the first phase, ED experiments were carried out for two SSAs from different seasons, varying the duration of the ED process (2, 4, 6 and 9 days). During the ED treatment the SSA was suspended in distilled water in the anolyte, which was separated from the catholyte by a cation exchange membrane. From both ashes 90% of P was successfully extracted after 6 days of treatment. Regarding the heavy metals removal, one of the SSAs had a better removal than the other. Therefore, it was possible to conclude that SSAs from different seasons can be submitted to ED process under the same parameters. In the second phase, the two SSAs were exposed to humidity and air prior to ED, in order to carbonate them. Although this procedure was not successful, ED experiments were carried out varying the duration of the treatment (2 and 6 days) and the period of air exposure that SSAs were submitted to (7, 14 and 30 days). After 6 days of treatment and 30 days of air exposure, 90% of phosphorus was successfully extracted from both ashes. No differences were identified between carbonated and non-carbonated SSAs. Thus, SSAs that were exposed to the air and humidity, e.g. SSAs stored for 30 days in an open deposit, can be treated under the same parameters as the SSAs directly collected from the incineration process. In the third phase, ED experiments were carried out during 6 days varying the stirring time (0, 1, 2 and 4 h/day) in order to investigate if energy can be saved on the stirring process. After 6 days of treatment and 4 h/day stirring, 80% and 90% of P was successfully extracted from SSA-A and SSA-B, respectively. This value is very similar to the one obtained for 6 days of treatment stirring 24 h/day.