Publication
Ant colony search algorithm for the optimal power flow problem
| dc.contributor.author | Soares, João | |
| dc.contributor.author | Sousa, Tiago | |
| dc.contributor.author | Vale, Zita | |
| dc.contributor.author | Morais, H. | |
| dc.contributor.author | Faria, Pedro | |
| dc.date.accessioned | 2013-04-19T10:34:24Z | |
| dc.date.available | 2013-04-19T10:34:24Z | |
| dc.date.issued | 2011 | |
| dc.date.updated | 2013-04-12T16:44:11Z | |
| dc.description.abstract | To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature. | por |
| dc.identifier | DOI 10.1109/PES.2011.6039840 | |
| dc.identifier.isbn | 978-1-4577-1000-1 | |
| dc.identifier.issn | 978-1-4577-1001-8 | |
| dc.identifier.issn | 1944-9925 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/1421 | |
| dc.language.iso | eng | por |
| dc.publisher | IEEE | por |
| dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6039840 | por |
| dc.subject | Ant colony search | por |
| dc.subject | Artificial intelligence | por |
| dc.subject | Economic dispatch | por |
| dc.subject | Optimal power flow | por |
| dc.subject | Optimization method | por |
| dc.title | Ant colony search algorithm for the optimal power flow problem | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Detroit, MI, USA, 2011 | por |
| oaire.citation.title | IEEE Power and Energy Society General Meeting | por |
| person.familyName | Soares | |
| person.familyName | Vale | |
| person.familyName | Faria | |
| person.givenName | João | |
| person.givenName | Zita | |
| person.givenName | Pedro | |
| person.identifier | 1043580 | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | 1612-8EA8-D0E8 | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.ciencia-id | B212-2309-F9C3 | |
| person.identifier.orcid | 0000-0002-4172-4502 | |
| person.identifier.orcid | 0000-0002-4560-9544 | |
| person.identifier.orcid | 0000-0002-5982-8342 | |
| person.identifier.rid | A-5824-2012 | |
| person.identifier.scopus-author-id | 35436109600 | |
| person.identifier.scopus-author-id | 7004115775 | |
| rcaap.rights | closedAccess | por |
| rcaap.type | conferenceObject | por |
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