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Felipe Campelo França Pintohttp://lattes.cnpq.br/6799982843395323Eduardo Gontijo CarranoLucas de Souza BatistaMartín Gómez RavettiElizângela Martins de SáElizabeth Fialho Wannerhttp://lattes.cnpq.br/9685472895445408André Luiz Maravilha Silva2024-02-15T17:01:03Z2024-02-15T17:01:03Z2018-10-22http://hdl.handle.net/1843/63981During a fault in a power distribution network, energy utilities can change the network topology to reconnect all or at least a portion of disconnected clients, then minimizing the area affected by the fault. These changes in the network are defined by a restoration plan that specifies a set of switches to be maneuvered. The faster energy utilitiesreconnectdisconnectedclients, thelighterthepenaltiesappliedtothem. Then, the energy utilities have a tight time frame to define the restoration plan before dispatching maintenance teams to perform the required maneuvers. Besides, the total time needed to perform the maneuvers has to be considered when determining the restoration plan, since the new topology that restores/minimizes the affected clients willbefullyoperationalonlyafterthemaneuversarecompleted. Althoughtheproblem of restoring power distribution networks is widely studied in the literature, no study has considered both the existence of multiple maintenance teams working in parallel and the time taken by the teams to move between locations where the maneuverable switches are located. Ignoring these characteristics results in inefficient restoration plans, taking longer than expected. In this work, we address the problem of providing a better estimation of the time to perform the restoration plan by modeling the assignment and sequencing of maneuver operations as a scheduling problem that minimizes the makespan, i.e., the total time required to complete all maneuver operations. Furthermore, we present specific heuristics for its solution that are fast enough to be incorporated into existing restoration algorithms without compromising their performance, since they already need to perform other time-consuming routines, e.g., power flow algorithms. Computational experiments with different fault scenarios showed that incorporating the proposed strategy in a restoration algorithm led to more efficient restoration plans.Na ocorrência de falhas em uma rede de distribuição de energia elétrica, as concessionárias de energia podem alterar a topologia da rede para reconectar clientes desconectados, minimizando a área afetada pela falha. Essas alterações na rede são definidas por um plano de restauração que especifica um conjunto de chaves a serem manobradas. Quanto mais rápido os forem clientes desconectados, menores serão as penalidades aplicadas à concessionária. Portanto, as concessionárias têm um curto período de tempo para definir um plano de restauração e enviarem equipes de manutenção para realizarem as manobras de chaveamento. Além disso, o tempo total necessário para realização das manobras deve ser considerado ao determinar o plano de restauração, uma vez que a nova topologia que restaura/minimiza os clientes afetados estará totalmente operacional somente após as manobras estarem concluídas. Embora o problema de restauração de redes de distribuição de energia elétrica seja amplamente estudado na literatura, nenhum estudo considerou, simultaneamente, a existência de múltiplas equipes de manutenção trabalhando em paralelo e o tempo demandado pelas equipes para se descolarem entre os locais onde as chaves de manobra se encontram. Ignorar essas características resulta em planos de restauração ineficientes, levando mais tempo do que o esperado. Neste trabalho, é proposta uma abordagem parafornecermelhoresestimativasdetempodeexecuçãodeplanosderestauração. Isso é feito através da modelagem da atribuição e sequenciamento das tarefas de chaveamento como um problema de sequenciamento de tarefas que minimiza o makespan, ou seja, o tempo total para conclusão de todas as operações de manobra na rede. Além disso, heurísticas específicas são apresentadas para solução desse problema de sequenciamento. As heurísticas apresentadas são rápidas o suficiente para serem incorporadas em algoritmos de restauração existentes sem que a eficiência desses algoritmos seja comprometida, uma vez que eles já devem realizar outras rotinas que consomem tempo, por exemplo, algoritmos de fluxo de potência. Experimentos computacionais considerando diferentes cenários de falhas mostraram que o uso da estrategia proposta em um algoritmo de restauração resultou em planos de restauração mais eficientes.engUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em Engenharia ElétricaUFMGBrasilENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICAhttp://creativecommons.org/licenses/by-nc-nd/3.0/pt/info:eu-repo/semantics/openAccessEngenharia elétricaEnergia elétrica - DistribuiçãoHeurísticaEnergy utilitiesElectricityDistribution networksScheduling maneuvers for the restoration of electric power distribution networksinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALANDRÉ LUIZ MARAVILHA SILVA-D.PDFANDRÉ LUIZ MARAVILHA SILVA-D.PDFapplication/pdf1366797https://repositorio.ufmg.br/bitstream/1843/63981/1/ANDR%c3%89%20LUIZ%20MARAVILHA%20SILVA-D.PDFdbdba043cb45844b8378e1a7de634892MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.ufmg.br/bitstream/1843/63981/2/license_rdfcfd6801dba008cb6adbd9838b81582abMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82118https://repositorio.ufmg.br/bitstream/1843/63981/3/license.txtcda590c95a0b51b4d15f60c9642ca272MD531843/639812024-02-15 14:01:03.691oai:repositorio.ufmg.br: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ório InstitucionalPUBhttps://repositorio.ufmg.br/oaiopendoar:2024-02-15T17:01:03Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
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