A new MILP-based approach for unit commitment in power production planning
| Main Author: | |
|---|---|
| Publication Date: | 2013 |
| Other Authors: | |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://repositorio.inesctec.pt/handle/123456789/4129 http://dx.doi.org/10.1016/j.ijepes.2012.08.046 |
Summary: | s This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum: this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances. including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective. |
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A new MILP-based approach for unit commitment in power production plannings This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum: this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances. including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.2017-12-14T19:20:29Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4129http://dx.doi.org/10.1016/j.ijepes.2012.08.046engAna VianaJoão Pedro Pedrosoinfo:eu-repo/semantics/embargoedAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-10-12T02:21:41Zoai:repositorio.inesctec.pt:123456789/4129Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:57:49.648583Repositórios 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 |
A new MILP-based approach for unit commitment in power production planning |
| title |
A new MILP-based approach for unit commitment in power production planning |
| spellingShingle |
A new MILP-based approach for unit commitment in power production planning Ana Viana |
| title_short |
A new MILP-based approach for unit commitment in power production planning |
| title_full |
A new MILP-based approach for unit commitment in power production planning |
| title_fullStr |
A new MILP-based approach for unit commitment in power production planning |
| title_full_unstemmed |
A new MILP-based approach for unit commitment in power production planning |
| title_sort |
A new MILP-based approach for unit commitment in power production planning |
| author |
Ana Viana |
| author_facet |
Ana Viana João Pedro Pedroso |
| author_role |
author |
| author2 |
João Pedro Pedroso |
| author2_role |
author |
| dc.contributor.author.fl_str_mv |
Ana Viana João Pedro Pedroso |
| description |
s This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum: this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances. including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013-01-01T00:00:00Z 2013 2017-12-14T19:20:29Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://repositorio.inesctec.pt/handle/123456789/4129 http://dx.doi.org/10.1016/j.ijepes.2012.08.046 |
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http://repositorio.inesctec.pt/handle/123456789/4129 http://dx.doi.org/10.1016/j.ijepes.2012.08.046 |
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eng |
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eng |
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