12 resultados para CO2 laser annealing
em Instituto Politécnico do Porto, Portugal
Resumo:
Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.
Resumo:
The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.
Resumo:
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.
Resumo:
The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.
Resumo:
O elevado nível de integração e miniaturização dos componentes existente nos dias de hoje, criam novos desafios na concepção de circuitos impressos. Neste trabalho são apresentados métodos para interligação entre componentes, em circuitos impressos com elevado número de ligações, recorrendo a tecnologia laser. Foi desenvolvida uma máquina CNC de três eixos, para posicionamento de um laser, mantendo o suporte para as operações tradicionais com ferramentas. O sistema foi concebido para a produção de circuitos impressos por laser (fresagem e furação), no entanto a compatibilidade com outras ferramentas e acessórios presentes, possibilitam a execução de outros processos no mesmo equipamento, como remoção da máscara de solda, soldadura de componentes, colocação de pasta de solda, gravação, inspecção visual, entre outros. Com este trabalho, demonstra-se a importância dos circuitos impressos na evolução da electrónica, assim como se apresentam soluções para a sua concepção.
Resumo:
Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.
Resumo:
Background: Physiotherapy has a very important role in the maintenance of the integumentary system integrity. There is very few evidence in humans. Nevertheless, there are some studies about tissue regeneration using low-level laser therapy (LLLT). Aim: To analyze the effectiveness of LLLT on scar tissue. Methods: Seventeen volunteers were stratified by age of their scars, and then randomly assigned to an experimental group (EG) — n = 9 – and a placebo group (PG) – n = 8. Fifteen sessions were conducted to both the groups thrice a week. However, in the PG, the laser device was switched off. Scars’ thickness, length, width, macroscopic aspect, pain threshold, pain perception, and itching were measured. Results: After 5 weeks, there were no statistically significant differences in any variable between both the groups. However, analyzing independently each group, EG showed a significant improvement in macroscopic aspect (p = 0.003) using LLLT. Taking into account the scars’ age, LLLT showed a tendency to decrease older scars’ thickness in EG. Conclusion: The intervention with LLLT appears to have a positive effect on the macroscopic scars’ appearance, and on old scars’ thickness, in the studied sample. However, it cannot be said for sure that LLLT has influence on scar tissue.
Resumo:
The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.
Resumo:
A exploração do meio subaquático utilizando visão computacional é ainda um processo complexo. Geralmente são utilizados sistemas de visão baseados em visão stereo, no entanto, esta abordagem apresenta limitações, é pouco precisa e é exigente em termos computacionais quando o meio de operação é o subaquático. Estas limitações surgem principalmente em dois cenários de aplicação: quando existe escassez de iluminação e em operações junto a infraestruturas subaquáticas. Consequentemente, a solução reside na utilização de fontes de informação sensorial alternativas ou complementares ao sistema de visão computacional. Neste trabalho propõe-se o desenvolvimento de um sistema de percepção subaquático que combina uma câmara e um projetor laser de um feixe em linha, onde o projetor de luz estruturada _e utilizado como fonte de informação. Em qualquer sistema de visão computacional, e ainda mais relevante em sistemas baseados em triangulação, a sua correta calibração toma um papel fulcral para a qualidade das medidas obtidas com o sistema. A calibração do sistema de visão laser foi dividida em duas etapas. A primeira etapa diz respeito à calibração da câmara, onde são definidos os parâmetros intrínsecos e os parâmetros extrínsecos relativos a este sensor. A segunda etapa define a relação entre a câmara e o laser, sendo esta etapa necessária para a obtenção de imagens tridimensionais. Assim, um dos principais desafios desta dissertação passou por resolver o problema da calibração inerente a este sistema. Desse modo, foi desenvolvida uma ferramenta que requer, pelo menos duas fotos do padrão de xadrez, com perspectivas diferentes. O método proposto foi caracterizado e validado em ambientes secos e subaquáticos. Os resultados obtidos mostram que o sistema _e preciso e os valores de profundidade obtidos apresentam um erro significativamente baixo (inferiores a 1 mm), mesmo com uma base-line (distância entre a centro óptico da câmara e o plano de incidência do laser) reduzida.
Resumo:
The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.
Resumo:
An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.
Resumo:
O presente trabalho visa apresentar a temática da otimização da produção de corte laser numa empresa do ramo da indústria metalomecânica, denominada Sermec Laser e situada no concelho da Maia no Distrito do Porto. Para alcançar este objetivo foi necessário conhecer o funcionamento atual do processo, como por exemplo, os seus intervenientes, as taxas de ocupação do equipamento de corte a laser e os procedimentos. Só depois de ser explorada essa vertente será possível desenvolver um plano com vista a melhorar esse processo. Este projeto espera criar um plano de melhoria que será testado e, quando for validado, será implementado. As melhorias propostas por este plano passam pelo aumento da eficiência do processo de corte a laser e a alteração de parte do layout da empresa de forma a facilitar e agilizar este mesmo processo. O objetivo final será acrescentar mais valor ao processo, reduzindo os seus desperdícios. Com esta melhoria a empresa ficará a ganhar, pois irá produzir de forma mais ajustada às suas necessidades.