Quantum Computing for Optimizing Power Flow in Energy Grids

Detalhes bibliográficos
Autor(a) principal: Silva, Pedro Miguel Dias da
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://hdl.handle.net/10316/98073
Resumo: Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia
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spelling Quantum Computing for Optimizing Power Flow in Energy GridsComputação Quântica para Otimizar o Fluxo de Carga em Redes ElétricasUnit Commitment ProblemMixed-Integer Linear ProgrammingQuantum ComputingQuadratic Unconstrained Binary OptimizationOptimizationProblema Unit CommitmentProgramação Linear Inteira MistaComputação QuânticaOtimização Binária Quadrática IrrestritaOtimizaçãoDissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e TecnologiaQuantum Computing is beginning to gather even more attention at a time where efforts are being made into familiarizing younger audiences into not only learning programming on a classical computer, but also on a quantum one.This new paradigm of computation is set to revolutionize several industries as the hardware keeps developing, with the potential to solve problems that a classical computer would consider intangible, as well as giving some specific problems a so sought after speed-up. This is done by applying the properties of quantum physics, like superposition and entanglement, for computation. These properties not only allow to process a larger amount of data simultaneously, but also allows to tackle problems in a completely different way that would not be possible in a classical computer.This thesis focuses on solving a known and relevant problem in the electrical industry and studying its application on a quantum environment. The Unit Commitment Problem, the problem in question, consists in minimizing the cost of power production, for a certain time horizon, by scheduling different generating units in order to meet a certain demand given by a valid forecast. Given that this is an NP-hard problem, it quickly becomes intractable on classical computers when considering real world scenarios on a large scale.A test scenario was also designed to study, by conducting an experimental analysis, the influences that each of the parameters have on the solution quality. To that end, the formulation of the Unit Commitment Problem was also translated to a suitable QUBO form which is then solved through a quantum annealer from D-Wave. For that test scenario, both the parameters from the problem formulation as well as the parameters related to the quantum computer were considered.The results from the experimental analysis suggest that most parameters do have an impact on the solution quality. With some having a greater impact overall such as Grids, that are representing how accurate the linearization of the problem is, as well the delta value associated with the first constraint, a value that is tied to how much of a weight the first constraint, that restricts each unit to a single production level, has. While the parameters with the overall greater impact are tied to the formulation of the problem, parameters like chain strength that affects the strength of coupling between qubits representing a single variable also have a significant impact on the solution quality. While most parameters have a statistical impact on the solution quality, the delta associated with the second constraint, that restricts power generation to equal the demand, fails to have an impact.Quantum Computing is beginning to gather even more attention at a time where efforts are being made into familiarizing younger audiences into not only learning programming on a classical computer, but also on a quantum one.This new paradigm of computation is set to revolutionize several industries as the hardware keeps developing, with the potential to solve problems that a classical computer would consider intangible, as well as giving some specific problems a so sought after speed-up. This is done by applying the properties of quantum physics, like superposition and entanglement, for computation. These properties not only allow to process a larger amount of data simultaneously, but also allows to tackle problems in a completely different way that would not be possible in a classical computer.This thesis focuses on solving a known and relevant problem in the electrical industry and studying its application on a quantum environment. The Unit Commitment Problem, the problem in question, consists in minimizing the cost of power production, for a certain time horizon, by scheduling different generating units in order to meet a certain demand given by a valid forecast. Given that this is an NP-hard problem, it quickly becomes intractable on classical computers when considering real world scenarios on a large scale.A test scenario was also designed to study, by conducting an experimental analysis, the influences that each of the parameters have on the solution quality. To that end, the formulation of the Unit Commitment Problem was also translated to a suitable QUBO form which is then solved through a quantum annealer from D-Wave. For that test scenario, both the parameters from the problem formulation as well as the parameters related to the quantum computer were considered.The results from the experimental analysis suggest that most parameters do have an impact on the solution quality. With some having a greater impact overall such as Grids, that are representing how accurate the linearization of the problem is, as well the delta value associated with the first constraint, a value that is tied to how much of a weight the first constraint, that restricts each unit to a single production level, has. While the parameters with the overall greater impact are tied to the formulation of the problem, parameters like chain strength that affects the strength of coupling between qubits representing a single variable also have a significant impact on the solution quality. While most parameters have a statistical impact on the solution quality, the delta associated with the second constraint, that restricts power generation to equal the demand, fails to have an impact.2021-11-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttps://hdl.handle.net/10316/98073https://hdl.handle.net/10316/98073TID:202921336engSilva, Pedro Miguel Dias dainfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2022-05-25T05:13:09Zoai:estudogeral.uc.pt:10316/98073Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:46:55.068806Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Quantum Computing for Optimizing Power Flow in Energy Grids
Computação Quântica para Otimizar o Fluxo de Carga em Redes Elétricas
title Quantum Computing for Optimizing Power Flow in Energy Grids
spellingShingle Quantum Computing for Optimizing Power Flow in Energy Grids
Silva, Pedro Miguel Dias da
Unit Commitment Problem
Mixed-Integer Linear Programming
Quantum Computing
Quadratic Unconstrained Binary Optimization
Optimization
Problema Unit Commitment
Programação Linear Inteira Mista
Computação Quântica
Otimização Binária Quadrática Irrestrita
Otimização
title_short Quantum Computing for Optimizing Power Flow in Energy Grids
title_full Quantum Computing for Optimizing Power Flow in Energy Grids
title_fullStr Quantum Computing for Optimizing Power Flow in Energy Grids
title_full_unstemmed Quantum Computing for Optimizing Power Flow in Energy Grids
title_sort Quantum Computing for Optimizing Power Flow in Energy Grids
author Silva, Pedro Miguel Dias da
author_facet Silva, Pedro Miguel Dias da
author_role author
dc.contributor.author.fl_str_mv Silva, Pedro Miguel Dias da
dc.subject.por.fl_str_mv Unit Commitment Problem
Mixed-Integer Linear Programming
Quantum Computing
Quadratic Unconstrained Binary Optimization
Optimization
Problema Unit Commitment
Programação Linear Inteira Mista
Computação Quântica
Otimização Binária Quadrática Irrestrita
Otimização
topic Unit Commitment Problem
Mixed-Integer Linear Programming
Quantum Computing
Quadratic Unconstrained Binary Optimization
Optimization
Problema Unit Commitment
Programação Linear Inteira Mista
Computação Quântica
Otimização Binária Quadrática Irrestrita
Otimização
description Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia
publishDate 2021
dc.date.none.fl_str_mv 2021-11-10
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/98073
https://hdl.handle.net/10316/98073
TID:202921336
url https://hdl.handle.net/10316/98073
identifier_str_mv TID:202921336
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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