2 resultados para Metaheuristic


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This doctoral Thesis defines and develops a new methodology for feeder reconfiguration in distribution networks with Distributed Energy Resources (DER). The proposed methodology is based on metaheuristic Ant Colony Optimization (ACO) algorithms. The methodology is called Item Oriented Ant System (IOAS) and the doctoral Thesis also defines three variations of the original methodology, Item Oriented Ant Colony System (IOACS), Item Oriented Max-min Ant System (IOMMAS) y Item Oriented Max-min Ant Colony System (IOACS). All methodologies pursue a twofold objective, to minimize the power losses and maximize DER penetration in distribution networks. The aim of the variations is to find the algorithm that adapts better to the present optimization problem, solving it most efficiently. The main feature of the methodology lies in the fact that the heuristic information and the exploitation information (pheromone) are attached to the item not to the path. Besides, the doctoral Thesis proposes to use feeder reconfiguration in order to increase the distribution network capacity of accepting a major degree of DER. The proposed methodology and its three variations have been tested and verified in two distribution networks well documented in the existing bibliography. These networks have been modeled and used to test all proposed methodologies for different scenarios with various DER penetration degrees.

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[EU]Proiektu honen helburua sare ezberdinetan algoritmo metaheuristikoen erabileraren bitartez bideratze arazoak ebaztea eta aztertzea da. Helburu honetarako erabiliko diren algoritmoak Coral Reefs Optimization eta Firefly Algorithm dira. Bi algoritmoak Python erabiliz inplementatuko dira, baita sareak simulatzen dituen programa ere. Modu honetan, algoritmo bakoitzaren gaitasuna aztertuko da sareko bi punturen arteko bide bideragarri bat, zeinek ezarritako murrizketak betetzen dituen, aurkitzeko; prozesu hau ausaz sortutako simulatutako sare batean oinarrituz garatuko da. Honen bitartez, arazo honen ebazpenerako algoritmo bakoitza egokia den eta bietariko zein den egokiena ondorioztatu ahalko da.