Spinning reverve and emission unit commitment through stochastic optimization
| dc.contributor.author | Melicio, Rui | |
| dc.contributor.author | Laia, Rui | |
| dc.contributor.author | Pousinho, Hugo | |
| dc.contributor.author | Mendes, Victor | |
| dc.contributor.author | Collares-Pereira, Manuel | |
| dc.date.accessioned | 2015-02-24T15:53:22Z | |
| dc.date.available | 2015-02-24T15:53:22Z | |
| dc.date.issued | 2014-06-18 | |
| dc.description.abstract | This paper proposes a stochastic mixed-integer linear approach to deal with a short-term unit commitment problem with uncertainty on a deregulated electricity market that includes day-ahead bidding and bilateral contracts. The proposed approach considers the typically operation constraints on the thermal units and a spinning reserve. The uncertainty is due to the electricity prices, which are modeled by a scenario set, allowing an acceptable computation. Moreover, emission allowances are considered in a manner to allow for the consideration of environmental constraints. A case study to illustrate the usefulness of the proposed approach is presented and an assessment of the cost for the spinning reserve is obtained by a comparison between the situation with and without spinning reserve. | por |
| dc.identifier.authoremail | ruimelicio@gmail.com | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.scientificarea | 482 | por |
| dc.identifier.uri | http://hdl.handle.net/10174/12875 | |
| dc.identifier.withinvitedoralpresentation | nao | por |
| dc.identifier.withoralpresentation | nao | por |
| dc.identifier.withposter | nao | por |
| dc.language.iso | eng | por |
| dc.publisher | IEEE International Symposium on Power Electronics, Electrical Drives and Motion | por |
| dc.rights | restrictedAccess | por |
| dc.subject | spinning reserve | por |
| dc.subject | unit commitment | por |
| dc.title | Spinning reverve and emission unit commitment through stochastic optimization | por |
| dc.type | lecture | por |