Publicação
Unit commitment based on risk assessment to systems with variable power sources
| Resumo: | This paper presents the development of a complete methodology for power systems scheduling with highly variable sources based on a risk assessment model. The methodology is tested in a real case study, namely an island with high penetration of renewable energy production. The uncertainty of renewable power production forecasts and load demand are defined by the probability distribution function, which can be a good alternative to the scenarios approach. The production mix chosen for each hour results from the costs associated to the operation risks, such as load shed and renewable production curtailment. The results to a seven days case study allow concluding about the difficulty to achieve a complete robust solution. |
|---|---|
| Autores principais: | Fonte, Pedro M |
| Outros Autores: | Monteiro, Cláudio; Barbosa, Fernando Maciel |
| Assunto: | Power generation scheduling Risk assessment Uncertainty |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | documento de conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Instituto Politécnico de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Lisboa |
| _version_ | 1866887459877421056 |
|---|---|
| author | Fonte, Pedro M |
| author2 | Monteiro, Cláudio Barbosa, Fernando Maciel |
| author2_role | author author |
| author_facet | Fonte, Pedro M Monteiro, Cláudio Barbosa, Fernando Maciel |
| author_role | author |
| contributor_name_str_mv | RCIPL |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Fonte, Pedro M\",\"Person.identifier.orcid\":\"0000-0001-5858-203X\"},{\"Person.name\":\"Monteiro, Cláudio\"},{\"Person.name\":\"Barbosa, Fernando Maciel\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | RCIPL |
| datacite.creators.creator.creatorName.fl_str_mv | Fonte, Pedro M Monteiro, Cláudio Barbosa, Fernando Maciel |
| datacite.date.Accepted.fl_str_mv | 2016-12-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2018-07-09T09:22:50Z |
| datacite.date.embargoed.fl_str_mv | 2018-07-09T09:22:50Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| datacite.subjects.subject.fl_str_mv | Power generation scheduling Risk assessment Uncertainty |
| datacite.titles.title.fl_str_mv | Unit commitment based on risk assessment to systems with variable power sources |
| dc.contributor.none.fl_str_mv | RCIPL |
| dc.creator.none.fl_str_mv | Fonte, Pedro M Monteiro, Cláudio Barbosa, Fernando Maciel |
| dc.date.Accepted.fl_str_mv | 2016-12-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2018-07-09T09:22:50Z |
| dc.date.embargoed.fl_str_mv | 2018-07-09T09:22:50Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.21/8675 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Institute of Electrical and Electronics Engineers |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| dc.subject.none.fl_str_mv | Power generation scheduling Risk assessment Uncertainty |
| dc.title.fl_str_mv | Unit commitment based on risk assessment to systems with variable power sources |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_c94f |
| description | This paper presents the development of a complete methodology for power systems scheduling with highly variable sources based on a risk assessment model. The methodology is tested in a real case study, namely an island with high penetration of renewable energy production. The uncertainty of renewable power production forecasts and load demand are defined by the probability distribution function, which can be a good alternative to the scenarios approach. The production mix chosen for each hour results from the costs associated to the operation risks, such as load shed and renewable production curtailment. The results to a seven days case study allow concluding about the difficulty to achieve a complete robust solution. |
| dirty | 0 |
| eu_rights_str_mv | restrictedAccess |
| format | conferenceObject |
| fulltext.url.fl_str_mv | https://repositorio.ipl.pt/bitstreams/f3a7e336-ffd2-439c-86f1-23c6ecab44a2/download |
| id | ripl_6f22bfa96db4ffbfcd0595ce9f2e75b7 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.21/8675 |
| instacron_str | ipl |
| institution | Instituto Politécnico de Lisboa |
| instname_str | Instituto Politécnico de Lisboa |
| language | eng |
| network_acronym_str | ripl |
| network_name_str | Repositório Científico do Instituto Politécnico de Lisboa |
| oai_identifier_str | oai:repositorio.ipl.pt:10400.21/8675 |
| organization_str_mv | urn:organizationAcronym:ipl |
| person_str_mv | Fonte, Pedro M Fonte, Pedro M https://www.ciencia-id.pt/4D17-2B29-38BB 4D17-2B29-38BB http://orcid.org/0000-0001-5858-203X 0000-0001-5858-203X Monteiro, Cláudio Barbosa, Fernando Maciel |
| publishDate | 2016 |
| publisher.none.fl_str_mv | Institute of Electrical and Electronics Engineers |
| reponame_str | Repositório Científico do Instituto Politécnico de Lisboa |
| repository_id_str | urn:repositoryAcronym:ripl |
| service_str_mv | urn:repositoryAcronym:ripl |
| spelling | engInstitute of Electrical and Electronics Engineerspt_PTThis paper presents the development of a complete methodology for power systems scheduling with highly variable sources based on a risk assessment model. The methodology is tested in a real case study, namely an island with high penetration of renewable energy production. The uncertainty of renewable power production forecasts and load demand are defined by the probability distribution function, which can be a good alternative to the scenarios approach. The production mix chosen for each hour results from the costs associated to the operation risks, such as load shed and renewable production curtailment. The results to a seven days case study allow concluding about the difficulty to achieve a complete robust solution.application/pdfpt_PTUnit commitment based on risk assessment to systems with variable power sourcesPersonalFonte, Pedro MDSpacehttp://dspace.org/items/7da87fed-6d70-4191-b26a-d0fd64965d29DSpacehttp://dspace.org/items/7da87fed-6d70-4191-b26a-d0fd64965d29FontePedro MCiência IDhttps://www.ciencia-id.pt4D17-2B29-38BBORCIDhttp://orcid.org0000-0001-5858-203XScopus Author IDhttps://www.scopus.com8507639300Scopus Author IDhttps://www.scopus.com57196324820Monteiro, CláudioBarbosa, Fernando MacielHostingInstitutionOrganizationalRCIPLe-mailmailto:rcaap@sp.ipl.ptrcaap@sp.ipl.ptISBNIsPartOf978-1-5090-3474-1ISBNIsPartOf978-1-5090-3475-8DOIIsPartOf10.1109/IECON.2016.77935332018-07-09T09:22:50Z2016-122016-12-01T00:00:00ZHandlehttp://hdl.handle.net/10400.21/8675http://purl.org/coar/access_right/c_16ecrestricted accessPower generation schedulingRisk assessmentUncertainty1218474 bytesother research producthttp://purl.org/coar/resource_type/c_c94fconference objecthttp://purl.org/coar/access_right/c_16ecapplication/pdffulltexthttps://repositorio.ipl.pt/bitstreams/f3a7e336-ffd2-439c-86f1-23c6ecab44a2/downloadIECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society3924392923-26 Oct. 2016 - Florence, Italy |
| spellingShingle | Unit commitment based on risk assessment to systems with variable power sources Fonte, Pedro M Power generation scheduling Risk assessment Uncertainty |
| status | SINGLETON |
| subject.fl_str_mv | Power generation scheduling Risk assessment Uncertainty |
| title | Unit commitment based on risk assessment to systems with variable power sources |
| title_full | Unit commitment based on risk assessment to systems with variable power sources |
| title_fullStr | Unit commitment based on risk assessment to systems with variable power sources |
| title_full_unstemmed | Unit commitment based on risk assessment to systems with variable power sources |
| title_short | Unit commitment based on risk assessment to systems with variable power sources |
| title_sort | Unit commitment based on risk assessment to systems with variable power sources |
| topic | Power generation scheduling Risk assessment Uncertainty |
| topic_facet | Power generation scheduling Risk assessment Uncertainty |
| url | http://hdl.handle.net/10400.21/8675 |
| visible | 1 |